the role of artificial intelligence in future technology essay

The present and future of AI

Finale doshi-velez on how ai is shaping our lives and how we can shape ai.

Finale Doshi-Velez, the John L. Loeb Professor of Engineering and Applied Sciences. (Photo courtesy of Eliza Grinnell/Harvard SEAS)

How has artificial intelligence changed and shaped our world over the last five years? How will AI continue to impact our lives in the coming years? Those were the questions addressed in the most recent report from the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted at Stanford University, that will study the status of AI technology and its impacts on the world over the next 100 years.

The 2021 report is the second in a series that will be released every five years until 2116. Titled “Gathering Strength, Gathering Storms,” the report explores the various ways AI is  increasingly touching people’s lives in settings that range from  movie recommendations  and  voice assistants  to  autonomous driving  and  automated medical diagnoses .

Barbara Grosz , the Higgins Research Professor of Natural Sciences at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) is a member of the standing committee overseeing the AI100 project and Finale Doshi-Velez , Gordon McKay Professor of Computer Science, is part of the panel of interdisciplinary researchers who wrote this year’s report. 

We spoke with Doshi-Velez about the report, what it says about the role AI is currently playing in our lives, and how it will change in the future.  

Q: Let's start with a snapshot: What is the current state of AI and its potential?

Doshi-Velez: Some of the biggest changes in the last five years have been how well AIs now perform in large data regimes on specific types of tasks.  We've seen [DeepMind’s] AlphaZero become the best Go player entirely through self-play, and everyday uses of AI such as grammar checks and autocomplete, automatic personal photo organization and search, and speech recognition become commonplace for large numbers of people.  

In terms of potential, I'm most excited about AIs that might augment and assist people.  They can be used to drive insights in drug discovery, help with decision making such as identifying a menu of likely treatment options for patients, and provide basic assistance, such as lane keeping while driving or text-to-speech based on images from a phone for the visually impaired.  In many situations, people and AIs have complementary strengths. I think we're getting closer to unlocking the potential of people and AI teams.

There's a much greater recognition that we should not be waiting for AI tools to become mainstream before making sure they are ethical.

Q: Over the course of 100 years, these reports will tell the story of AI and its evolving role in society. Even though there have only been two reports, what's the story so far?

There's actually a lot of change even in five years.  The first report is fairly rosy.  For example, it mentions how algorithmic risk assessments may mitigate the human biases of judges.  The second has a much more mixed view.  I think this comes from the fact that as AI tools have come into the mainstream — both in higher stakes and everyday settings — we are appropriately much less willing to tolerate flaws, especially discriminatory ones. There's also been questions of information and disinformation control as people get their news, social media, and entertainment via searches and rankings personalized to them. So, there's a much greater recognition that we should not be waiting for AI tools to become mainstream before making sure they are ethical.

Q: What is the responsibility of institutes of higher education in preparing students and the next generation of computer scientists for the future of AI and its impact on society?

First, I'll say that the need to understand the basics of AI and data science starts much earlier than higher education!  Children are being exposed to AIs as soon as they click on videos on YouTube or browse photo albums. They need to understand aspects of AI such as how their actions affect future recommendations.

But for computer science students in college, I think a key thing that future engineers need to realize is when to demand input and how to talk across disciplinary boundaries to get at often difficult-to-quantify notions of safety, equity, fairness, etc.  I'm really excited that Harvard has the Embedded EthiCS program to provide some of this education.  Of course, this is an addition to standard good engineering practices like building robust models, validating them, and so forth, which is all a bit harder with AI.

I think a key thing that future engineers need to realize is when to demand input and how to talk across disciplinary boundaries to get at often difficult-to-quantify notions of safety, equity, fairness, etc. 

Q: Your work focuses on machine learning with applications to healthcare, which is also an area of focus of this report. What is the state of AI in healthcare? 

A lot of AI in healthcare has been on the business end, used for optimizing billing, scheduling surgeries, that sort of thing.  When it comes to AI for better patient care, which is what we usually think about, there are few legal, regulatory, and financial incentives to do so, and many disincentives. Still, there's been slow but steady integration of AI-based tools, often in the form of risk scoring and alert systems.

In the near future, two applications that I'm really excited about are triage in low-resource settings — having AIs do initial reads of pathology slides, for example, if there are not enough pathologists, or get an initial check of whether a mole looks suspicious — and ways in which AIs can help identify promising treatment options for discussion with a clinician team and patient.

Q: Any predictions for the next report?

I'll be keen to see where currently nascent AI regulation initiatives have gotten to. Accountability is such a difficult question in AI,  it's tricky to nurture both innovation and basic protections.  Perhaps the most important innovation will be in approaches for AI accountability.

Topics: AI / Machine Learning , Computer Science

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The Future of AI: How Artificial Intelligence Will Change the World

Innovations in the field of  artificial intelligence continue to shape the future of humanity across nearly every industry. AI is already the main driver of emerging technologies like big data, robotics and IoT, and  generative AI has further expanded the possibilities and popularity of AI. 

According to a 2023 IBM survey , 42 percent of enterprise-scale businesses integrated AI into their operations, and 40 percent are considering AI for their organizations. In addition, 38 percent of organizations have implemented generative AI into their workflows while 42 percent are considering doing so.

With so many changes coming at such a rapid pace, here’s what shifts in AI could mean for various industries and society at large.

More on the Future of AI Can AI Make Art More Human?

The Evolution of AI

AI has come a long way since 1951, when the  first documented success of an AI computer program was written by Christopher Strachey, whose checkers program completed a whole game on the Ferranti Mark I computer at the University of Manchester. Thanks to developments in machine learning and deep learning , IBM’s Deep Blue defeated chess grandmaster Garry Kasparov in 1997, and the company’s IBM Watson won Jeopardy! in 2011.  

Since then, generative AI has spearheaded the latest chapter in AI’s evolution, with OpenAI releasing its first GPT models in 2018. This has culminated in OpenAI developing its GPT-4 model and ChatGPT , leading to a proliferation of AI generators that can process queries to produce relevant text, audio, images and other types of content.   

AI has also been used to help  sequence RNA for vaccines and  model human speech , technologies that rely on model- and algorithm-based  machine learning and increasingly focus on perception, reasoning and generalization. 

How AI Will Impact the Future

Improved business automation .

About 55 percent of organizations have adopted AI to varying degrees, suggesting increased automation for many businesses in the near future. With the rise of chatbots and digital assistants, companies can rely on AI to handle simple conversations with customers and answer basic queries from employees.

AI’s ability to analyze massive amounts of data and convert its findings into convenient visual formats can also accelerate the decision-making process . Company leaders don’t have to spend time parsing through the data themselves, instead using instant insights to make informed decisions .

“If [developers] understand what the technology is capable of and they understand the domain very well, they start to make connections and say, ‘Maybe this is an AI problem, maybe that’s an AI problem,’” said Mike Mendelson, a learner experience designer for NVIDIA . “That’s more often the case than, ‘I have a specific problem I want to solve.’”

More on AI 75 Artificial Intelligence (AI) Companies to Know

Job Disruption

Business automation has naturally led to fears over job losses . In fact, employees believe almost one-third of their tasks could be performed by AI. Although AI has made gains in the workplace, it’s had an unequal impact on different industries and professions. For example, manual jobs like secretaries are at risk of being automated, but the demand for other jobs like machine learning specialists and information security analysts has risen.

Workers in more skilled or creative positions are more likely to have their jobs augmented by AI , rather than be replaced. Whether forcing employees to learn new tools or taking over their roles, AI is set to spur upskilling efforts at both the individual and company level .     

“One of the absolute prerequisites for AI to be successful in many [areas] is that we invest tremendously in education to retrain people for new jobs,” said Klara Nahrstedt, a computer science professor at the University of Illinois at Urbana–Champaign and director of the school’s Coordinated Science Laboratory.

Data Privacy Issues

Companies require large volumes of data to train the models that power generative AI tools, and this process has come under intense scrutiny. Concerns over companies collecting consumers’ personal data have led the FTC to open an investigation into whether OpenAI has negatively impacted consumers through its data collection methods after the company potentially violated European data protection laws . 

In response, the Biden-Harris administration developed an AI Bill of Rights that lists data privacy as one of its core principles. Although this legislation doesn’t carry much legal weight, it reflects the growing push to prioritize data privacy and compel AI companies to be more transparent and cautious about how they compile training data.      

Increased Regulation

AI could shift the perspective on certain legal questions, depending on how generative AI lawsuits unfold in 2024. For example, the issue of intellectual property has come to the forefront in light of copyright lawsuits filed against OpenAI by writers, musicians and companies like The New York Times . These lawsuits affect how the U.S. legal system interprets what is private and public property, and a loss could spell major setbacks for OpenAI and its competitors. 

Ethical issues that have surfaced in connection to generative AI have placed more pressure on the U.S. government to take a stronger stance. The Biden-Harris administration has maintained its moderate position with its latest executive order , creating rough guidelines around data privacy, civil liberties, responsible AI and other aspects of AI. However, the government could lean toward stricter regulations, depending on  changes in the political climate .  

Climate Change Concerns

On a far grander scale, AI is poised to have a major effect on sustainability, climate change and environmental issues. Optimists can view AI as a way to make supply chains more efficient, carrying out predictive maintenance and other procedures to reduce carbon emissions . 

At the same time, AI could be seen as a key culprit in climate change . The energy and resources required to create and maintain AI models could raise carbon emissions by as much as 80 percent, dealing a devastating blow to any sustainability efforts within tech. Even if AI is applied to climate-conscious technology , the costs of building and training models could leave society in a worse environmental situation than before.   

What Industries Will AI Impact the Most?  

There’s virtually no major industry that modern AI hasn’t already affected. Here are a few of the industries undergoing the greatest changes as a result of AI.  

AI in Manufacturing

Manufacturing has been benefiting from AI for years. With AI-enabled robotic arms and other manufacturing bots dating back to the 1960s and 1970s, the industry has adapted well to the powers of AI. These  industrial robots typically work alongside humans to perform a limited range of tasks like assembly and stacking, and predictive analysis sensors keep equipment running smoothly. 

AI in Healthcare

It may seem unlikely, but  AI healthcare is already changing the way humans interact with medical providers. Thanks to its  big data analysis capabilities, AI helps identify diseases more quickly and accurately, speed up and streamline drug discovery and even monitor patients through virtual nursing assistants. 

AI in Finance

Banks, insurers and financial institutions leverage AI for a range of applications like detecting fraud, conducting audits and evaluating customers for loans. Traders have also used machine learning’s ability to assess millions of data points at once, so they can quickly gauge risk and make smart investing decisions . 

AI in Education

AI in education will change the way humans of all ages learn. AI’s use of machine learning,  natural language processing and  facial recognition help digitize textbooks, detect plagiarism and gauge the emotions of students to help determine who’s struggling or bored. Both presently and in the future, AI tailors the experience of learning to student’s individual needs.

AI in Media

Journalism is harnessing AI too, and will continue to benefit from it. One example can be seen in The Associated Press’ use of  Automated Insights , which produces thousands of earning reports stories per year. But as generative  AI writing tools , such as ChatGPT, enter the market,  questions about their use in journalism abound.

AI in Customer Service

Most people dread getting a  robocall , but  AI in customer service can provide the industry with data-driven tools that bring meaningful insights to both the customer and the provider. AI tools powering the customer service industry come in the form of  chatbots and  virtual assistants .

AI in Transportation

Transportation is one industry that is certainly teed up to be drastically changed by AI.  Self-driving cars and  AI travel planners are just a couple of facets of how we get from point A to point B that will be influenced by AI. Even though autonomous vehicles are far from perfect, they will one day ferry us from place to place.

Risks and Dangers of AI

Despite reshaping numerous industries in positive ways, AI still has flaws that leave room for concern. Here are a few potential risks of artificial intelligence.  

Job Losses 

Between 2023 and 2028, 44 percent of workers’ skills will be disrupted . Not all workers will be affected equally — women are more likely than men to be exposed to AI in their jobs. Combine this with the fact that there is a gaping AI skills gap between men and women, and women seem much more susceptible to losing their jobs. If companies don’t have steps in place to upskill their workforces, the proliferation of AI could result in higher unemployment and decreased opportunities for those of marginalized backgrounds to break into tech.

Human Biases 

The reputation of AI has been tainted with a habit of reflecting the biases of the people who train the algorithmic models. For example, facial recognition technology has been known to favor lighter-skinned individuals , discriminating against people of color with darker complexions. If researchers aren’t careful in  rooting out these biases early on, AI tools could reinforce these biases in the minds of users and perpetuate social inequalities.

Deepfakes and Misinformation

The spread of deepfakes threatens to blur the lines between fiction and reality, leading the general public to  question what’s real and what isn’t. And if people are unable to identify deepfakes, the impact of  misinformation could be dangerous to individuals and entire countries alike. Deepfakes have been used to promote political propaganda, commit financial fraud and place students in compromising positions, among other use cases. 

Data Privacy

Training AI models on public data increases the chances of data security breaches that could expose consumers’ personal information. Companies contribute to these risks by adding their own data as well. A  2024 Cisco survey found that 48 percent of businesses have entered non-public company information into  generative AI tools and 69 percent are worried these tools could damage their intellectual property and legal rights. A single breach could expose the information of millions of consumers and leave organizations vulnerable as a result.  

Automated Weapons

The use of AI in automated weapons poses a major threat to countries and their general populations. While automated weapons systems are already deadly, they also fail to discriminate between soldiers and civilians . Letting artificial intelligence fall into the wrong hands could lead to irresponsible use and the deployment of weapons that put larger groups of people at risk.  

Superior Intelligence

Nightmare scenarios depict what’s known as the technological singularity , where superintelligent machines take over and permanently alter human existence through enslavement or eradication. Even if AI systems never reach this level, they can become more complex to the point where it’s difficult to determine how AI makes decisions at times. This can lead to a lack of transparency around how to fix algorithms when mistakes or unintended behaviors occur. 

“I don’t think the methods we use currently in these areas will lead to machines that decide to kill us,” said Marc Gyongyosi, founder of  Onetrack.AI . “I think that maybe five or 10 years from now, I’ll have to reevaluate that statement because we’ll have different methods available and different ways to go about these things.”

Frequently Asked Questions

What does the future of ai look like.

AI is expected to improve industries like healthcare, manufacturing and customer service, leading to higher-quality experiences for both workers and customers. However, it does face challenges like increased regulation, data privacy concerns and worries over job losses.

What will AI look like in 10 years?

AI is on pace to become a more integral part of people’s everyday lives. The technology could be used to provide elderly care and help out in the home. In addition, workers could collaborate with AI in different settings to enhance the efficiency and safety of workplaces.

Is AI a threat to humanity?

It depends on how people in control of AI decide to use the technology. If it falls into the wrong hands, AI could be used to expose people’s personal information, spread misinformation and perpetuate social inequalities, among other malicious use cases.

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What’s next for AI in 2024

Our writers look at the four hot trends to watch out for this year

• Melissa Heikkilä archive page
• Will Douglas Heaven archive page

MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of our series here .

This time last year we did something reckless. In an industry where nothing stands still, we had a go at predicting the future. 

How did we do? Our four big bets for 2023 were that the next big thing in chatbots would be multimodal (check: the most powerful large language models out there, OpenAI’s GPT-4 and Google DeepMind’s Gemini, work with text, images and audio); that policymakers would draw up tough new regulations (check: Biden’s executive order came out in October and the European Union’s AI Act was finally agreed in December ); Big Tech would feel pressure from open-source startups (half right: the open-source boom continues, but AI companies like OpenAI and Google DeepMind still stole the limelight); and that AI would change big pharma for good (too soon to tell: the AI revolution in drug discovery is in full swing , but the first drugs developed using AI are still some years from market).

Now we’re doing it again.

We decided to ignore the obvious. We know that large language models will continue to dominate. Regulators will grow bolder. AI’s problems—from bias to copyright to doomerism—will shape the agenda for researchers, regulators, and the public, not just in 2024 but for years to come. (Read more about our six big questions for generative AI here .)

Instead, we’ve picked a few more specific trends. Here’s what to watch out for in 2024. (Come back next year and check how we did.)

Customized chatbots

You get a chatbot! And you get a chatbot! In 2024, tech companies that invested heavily in generative AI will be under pressure to prove that they can make money off their products. To do this, AI giants Google and OpenAI are betting big on going small: both are developing user-friendly platforms that allow people to customize powerful language models and make their own mini chatbots that cater to their specific needs—no coding skills required. Both have launched web-based tools that allow anyone to become a generative-AI app developer. 

In 2024, generative AI might actually become useful for the regular, non-tech person, and we are going to see more people tinkering with a million little AI models. State-of-the-art AI models, such as GPT-4 and Gemini , are multimodal, meaning they can process not only text but images and even videos. This new capability could unlock a whole bunch of new apps. For example, a real estate agent can upload text from previous listings, fine-tune a powerful model to generate similar text with just a click of a button, upload videos and photos of new listings, and simply ask the customized AI to generate a description of the property. 

But of course, the success of this plan hinges on whether these models work reliably. Language models often make stuff up, and generative models are riddled with biases . They are also easy to hack , especially if they are allowed to browse the web. Tech companies have not solved any of these problems. When the novelty wears off, they’ll have to offer their customers ways to deal with these problems. 

—Melissa Heikkil ä

Generative AI’s second wave will be video

It’s amazing how fast the fantastic becomes familiar. The first generative models to produce photorealistic images exploded into the mainstream in 2022 —and soon became commonplace. Tools like OpenAI’s DALL-E, Stability AI’s Stable Diffusion, and Adobe’s Firefly flooded the internet with jaw-dropping images of everything from the pope in Balenciaga to prize-winning art . But it’s not all good fun: for every pug waving pompoms , there’s another piece of knock-off fantasy art or sexist sexual stereotyping .

The new frontier is text-to-video. Expect it to take everything that was good, bad, or ugly about text-to-image and supersize it.

A year ago we got the first glimpse of what generative models could do when they were trained to stitch together multiple still images into clips a few seconds long. The results were distorted and jerky. But the tech has rapidly improved.

Runway , a startup that makes generative video models (and the company that co-created Stable Diffusion), is dropping new versions of its tools every few months. Its latest model, called Gen-2 , still generates video just a few seconds long, but the quality is striking. The best clips aren’t far off what Pixar might put out.

Runway has set up an annual AI film festival that showcases experimental movies made with a range of AI tools. This year’s festival has a $60,000 prize pot, and the 10 best films will be screened in New York and Los Angeles.

It’s no surprise that top studios are taking notice. Movie giants, including Paramount and Disney, are now exploring the use of generative AI throughout their production pipeline. The tech is being used to lip-sync actors’ performances to multiple foreign-language overdubs. And it is reinventing what’s possible with special effects. In 2023, Indiana Jones and the Dial of Destiny starred a de-aged deepfake Harrison Ford. This is just the start.  

Away from the big screen, deepfake tech for marketing or training purposes is taking off too. For example, UK-based Synthesia makes tools that can turn a one-off performance by an actor into an endless stream of deepfake avatars, reciting whatever script you give them at the push of a button. According to the company, its tech is now used by 44% of Fortune 100 companies. 

The ability to do so much with so little raises serious questions for actors . Concerns about studios’ use and misuse of AI were at the heart of the SAG-AFTRA strikes last year. But the true impact of the tech is only just becoming apparent. “The craft of filmmaking is fundamentally changing,” says Souki Mehdaoui, an independent filmmaker and cofounder of Bell & Whistle, a consultancy specializing in creative technologies.

—Will Douglas Heaven

AI-generated election disinformation will be everywhere 

If recent elections are anything to go by, AI-generated election disinformation and deepfakes are going to be a huge problem as a record number of people march to the polls in 2024. We’re already seeing politicians weaponizing these tools. In Argentina , two presidential candidates created AI-generated images and videos of their opponents to attack them. In Slovakia , deepfakes of a liberal pro-European party leader threatening to raise the price of beer and making jokes about child pornography spread like wildfire during the country’s elections. And in the US, Donald Trump has cheered on a group that uses AI to generate memes with racist and sexist tropes. 

While it’s hard to say how much these examples have influenced the outcomes of elections, their proliferation is a worrying trend. It will become harder than ever to recognize what is real online. In an already inflamed and polarized political climate, this could have severe consequences.

Just a few years ago creating a deepfake would have required advanced technical skills, but generative AI has made it stupidly easy and accessible, and the outputs are looking increasingly realistic. Even reputable sources might be fooled by AI-generated content. For example, users-submitted AI-generated images purporting to depict the Israel-Gaza crisis have flooded stock image marketplaces like Adobe’s. 

The coming year will be pivotal for those fighting against the proliferation of such content. Techniques to track and mitigate it content are still in early days of development. Watermarks, such as Google DeepMind’s SynthID , are still mostly voluntary and not completely foolproof. And social media platforms are notoriously slow in taking down misinformation. Get ready for a massive real-time experiment in busting AI-generated fake news. 

Robots that multitask

Inspired by some of the core techniques behind generative AI’s current boom, roboticists are starting to build more general-purpose robots that can do a wider range of tasks.

The last few years in AI have seen a shift away from using multiple small models, each trained to do different tasks—identifying images, drawing them, captioning them—toward single, monolithic models trained to do all these things and more. By showing OpenAI’s GPT-3 a few additional examples (known as fine-tuning), researchers can train it to solve coding problems, write movie scripts, pass high school biology exams, and so on. Multimodal models, like GPT-4 and Google DeepMind’s Gemini, can solve visual tasks as well as linguistic ones.

The same approach can work for robots, so it wouldn’t be necessary to train one to flip pancakes and another to open doors: a one-size-fits-all model could give robots the ability to multitask. Several examples of work in this area emerged in 2023.

In June, DeepMind released Robocat (an update on last year’s Gato ), which generates its own data from trial and error to learn how to control many different robot arms (instead of one specific arm, which is more typical). 

In October, the company put out yet another general-purpose model for robots, called RT-X, and a big new general-purpose training data set , in collaboration with 33 university labs. Other top research teams, such as RAIL (Robotic Artificial Intelligence and Learning) at the University of California, Berkeley, are looking at similar tech.

The problem is a lack of data. Generative AI draws on an internet-size data set of text and images. In comparison, robots have very few good sources of data to help them learn how to do many of the industrial or domestic tasks we want them to.

Lerrel Pinto at New York University leads one team addressing that. He and his colleagues are developing techniques that let robots learn by trial and error, coming up with their own training data as they go. In an even more low-key project, Pinto has recruited volunteers to collect video data from around their homes using an iPhone camera mounted to a trash picker . Big companies have also started to release large data sets for training robots in the last couple of years, such as Meta’s Ego4D .

This approach is already showing promise in driverless cars. Startups such as Wayve, Waabi, and Ghost are pioneering a new wave of self-driving AI that uses a single large model to control a vehicle rather than multiple smaller models to control specific driving tasks. This has let small companies catch up with giants like Cruise and Waymo. Wayve is now testing its driverless cars on the narrow, busy streets of London. Robots everywhere are set to get a similar boost.

Artificial intelligence

Large language models can do jaw-dropping things. but nobody knows exactly why..

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

What’s next for generative video

OpenAI's Sora has raised the bar for AI moviemaking. Here are four things to bear in mind as we wrap our heads around what's coming.

The AI Act is done. Here’s what will (and won’t) change

The hard work starts now.

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• Artificial Intelligence and the Future of Humans

Experts say the rise of artificial intelligence will make most people better off over the next decade, but many have concerns about how advances in AI will affect what it means to be human, to be productive and to exercise free will

Table of contents.

• 1. Concerns about human agency, evolution and survival
• 2. Solutions to address AI’s anticipated negative impacts
• 3. Improvements ahead: How humans and AI might evolve together in the next decade
• About this canvassing of experts
• Acknowledgments

Digital life is augmenting human capacities and disrupting eons-old human activities. Code-driven systems have spread to more than half of the world’s inhabitants in ambient information and connectivity, offering previously unimagined opportunities and unprecedented threats. As emerging algorithm-driven artificial intelligence (AI) continues to spread, will people be better off than they are today?

Some 979 technology pioneers, innovators, developers, business and policy leaders, researchers and activists answered this question in a canvassing of experts conducted in the summer of 2018.

The experts predicted networked artificial intelligence will amplify human effectiveness but also threaten human autonomy, agency and capabilities. They spoke of the wide-ranging possibilities; that computers might match or even exceed human intelligence and capabilities on tasks such as complex decision-making, reasoning and learning, sophisticated analytics and pattern recognition, visual acuity, speech recognition and language translation. They said “smart” systems in communities, in vehicles, in buildings and utilities, on farms and in business processes will save time, money and lives and offer opportunities for individuals to enjoy a more-customized future.

Many focused their optimistic remarks on health care and the many possible applications of AI in diagnosing and treating patients or helping senior citizens live fuller and healthier lives. They were also enthusiastic about AI’s role in contributing to broad public-health programs built around massive amounts of data that may be captured in the coming years about everything from personal genomes to nutrition. Additionally, a number of these experts predicted that AI would abet long-anticipated changes in formal and informal education systems.

Yet, most experts, regardless of whether they are optimistic or not, expressed concerns about the long-term impact of these new tools on the essential elements of being human. All respondents in this non-scientific canvassing were asked to elaborate on why they felt AI would leave people better off or not. Many shared deep worries, and many also suggested pathways toward solutions. The main themes they sounded about threats and remedies are outlined in the accompanying table.

[chart id=”21972″]

Specifically, participants were asked to consider the following:

“Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties.

Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today?”

Overall, and despite the downsides they fear, 63% of respondents in this canvassing said they are hopeful that most individuals will be mostly better off in 2030, and 37% said people will not be better off.

A number of the thought leaders who participated in this canvassing said humans’ expanding reliance on technological systems will only go well if close attention is paid to how these tools, platforms and networks are engineered, distributed and updated. Some of the powerful, overarching answers included those from:

Sonia Katyal , co-director of the Berkeley Center for Law and Technology and a member of the inaugural U.S. Commerce Department Digital Economy Board of Advisors, predicted, “In 2030, the greatest set of questions will involve how perceptions of AI and their application will influence the trajectory of civil rights in the future. Questions about privacy, speech, the right of assembly and technological construction of personhood will all re-emerge in this new AI context, throwing into question our deepest-held beliefs about equality and opportunity for all. Who will benefit and who will be disadvantaged in this new world depends on how broadly we analyze these questions today, for the future.”

We need to work aggressively to make sure technology matches our values. Erik Brynjolfsson

[machine learning]

Bryan Johnson , founder and CEO of Kernel, a leading developer of advanced neural interfaces, and OS Fund, a venture capital firm, said, “I strongly believe the answer depends on whether we can shift our economic systems toward prioritizing radical human improvement and staunching the trend toward human irrelevance in the face of AI. I don’t mean just jobs; I mean true, existential irrelevance, which is the end result of not prioritizing human well-being and cognition.”

Andrew McLaughlin , executive director of the Center for Innovative Thinking at Yale University, previously deputy chief technology officer of the United States for President Barack Obama and global public policy lead for Google, wrote, “2030 is not far in the future. My sense is that innovations like the internet and networked AI have massive short-term benefits, along with long-term negatives that can take decades to be recognizable. AI will drive a vast range of efficiency optimizations but also enable hidden discrimination and arbitrary penalization of individuals in areas like insurance, job seeking and performance assessment.”

Michael M. Roberts , first president and CEO of the Internet Corporation for Assigned Names and Numbers (ICANN) and Internet Hall of Fame member, wrote, “The range of opportunities for intelligent agents to augment human intelligence is still virtually unlimited. The major issue is that the more convenient an agent is, the more it needs to know about you – preferences, timing, capacities, etc. – which creates a tradeoff of more help requires more intrusion. This is not a black-and-white issue – the shades of gray and associated remedies will be argued endlessly. The record to date is that convenience overwhelms privacy. I suspect that will continue.”

danah boyd , a principal researcher for Microsoft and founder and president of the Data & Society Research Institute, said, “AI is a tool that will be used by humans for all sorts of purposes, including in the pursuit of power. There will be abuses of power that involve AI, just as there will be advances in science and humanitarian efforts that also involve AI. Unfortunately, there are certain trend lines that are likely to create massive instability. Take, for example, climate change and climate migration. This will further destabilize Europe and the U.S., and I expect that, in panic, we will see AI be used in harmful ways in light of other geopolitical crises.”

Amy Webb , founder of the Future Today Institute and professor of strategic foresight at New York University, commented, “The social safety net structures currently in place in the U.S. and in many other countries around the world weren’t designed for our transition to AI. The transition through AI will last the next 50 years or more. As we move farther into this third era of computing, and as every single industry becomes more deeply entrenched with AI systems, we will need new hybrid-skilled knowledge workers who can operate in jobs that have never needed to exist before. We’ll need farmers who know how to work with big data sets. Oncologists trained as robotocists. Biologists trained as electrical engineers. We won’t need to prepare our workforce just once, with a few changes to the curriculum. As AI matures, we will need a responsive workforce, capable of adapting to new processes, systems and tools every few years. The need for these fields will arise faster than our labor departments, schools and universities are acknowledging. It’s easy to look back on history through the lens of present – and to overlook the social unrest caused by widespread technological unemployment. We need to address a difficult truth that few are willing to utter aloud: AI will eventually cause a large number of people to be permanently out of work. Just as generations before witnessed sweeping changes during and in the aftermath of the Industrial Revolution, the rapid pace of technology will likely mean that Baby Boomers and the oldest members of Gen X – especially those whose jobs can be replicated by robots – won’t be able to retrain for other kinds of work without a significant investment of time and effort.”

Barry Chudakov , founder and principal of Sertain Research, commented, “By 2030 the human-machine/AI collaboration will be a necessary tool to manage and counter the effects of multiple simultaneous accelerations: broad technology advancement, globalization, climate change and attendant global migrations. In the past, human societies managed change through gut and intuition, but as Eric Teller, CEO of Google X, has said, ‘Our societal structures are failing to keep pace with the rate of change.’ To keep pace with that change and to manage a growing list of ‘wicked problems’ by 2030, AI – or using Joi Ito’s phrase, extended intelligence – will value and revalue virtually every area of human behavior and interaction. AI and advancing technologies will change our response framework and time frames (which in turn, changes our sense of time). Where once social interaction happened in places – work, school, church, family environments – social interactions will increasingly happen in continuous, simultaneous time. If we are fortunate, we will follow the 23 Asilomar AI Principles outlined by the Future of Life Institute and will work toward ‘not undirected intelligence but beneficial intelligence.’ Akin to nuclear deterrence stemming from mutually assured destruction, AI and related technology systems constitute a force for a moral renaissance. We must embrace that moral renaissance, or we will face moral conundrums that could bring about human demise. … My greatest hope for human-machine/AI collaboration constitutes a moral and ethical renaissance – we adopt a moonshot mentality and lock arms to prepare for the accelerations coming at us. My greatest fear is that we adopt the logic of our emerging technologies – instant response, isolation behind screens, endless comparison of self-worth, fake self-presentation – without thinking or responding smartly.”

John C. Havens , executive director of the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems and the Council on Extended Intelligence, wrote, “Now, in 2018, a majority of people around the world can’t access their data, so any ‘human-AI augmentation’ discussions ignore the critical context of who actually controls people’s information and identity. Soon it will be extremely difficult to identify any autonomous or intelligent systems whose algorithms don’t interact with human data in one form or another.”

At stake is nothing less than what sort of society we want to live in and how we experience our humanity. Batya Friedman

Batya Friedman , a human-computer interaction professor at the University of Washington’s Information School, wrote, “Our scientific and technological capacities have and will continue to far surpass our moral ones – that is our ability to use wisely and humanely the knowledge and tools that we develop. … Automated warfare – when autonomous weapons kill human beings without human engagement – can lead to a lack of responsibility for taking the enemy’s life or even knowledge that an enemy’s life has been taken. At stake is nothing less than what sort of society we want to live in and how we experience our humanity.”

Greg Shannon , chief scientist for the CERT Division at Carnegie Mellon University, said, “Better/worse will appear 4:1 with the long-term ratio 2:1. AI will do well for repetitive work where ‘close’ will be good enough and humans dislike the work. … Life will definitely be better as AI extends lifetimes, from health apps that intelligently ‘nudge’ us to health, to warnings about impending heart/stroke events, to automated health care for the underserved (remote) and those who need extended care (elder care). As to liberty, there are clear risks. AI affects agency by creating entities with meaningful intellectual capabilities for monitoring, enforcing and even punishing individuals. Those who know how to use it will have immense potential power over those who don’t/can’t. Future happiness is really unclear. Some will cede their agency to AI in games, work and community, much like the opioid crisis steals agency today. On the other hand, many will be freed from mundane, unengaging tasks/jobs. If elements of community happiness are part of AI objective functions, then AI could catalyze an explosion of happiness.”

Kostas Alexandridis , author of “Exploring Complex Dynamics in Multi-agent-based Intelligent Systems,” predicted, “Many of our day-to-day decisions will be automated with minimal intervention by the end-user. Autonomy and/or independence will be sacrificed and replaced by convenience. Newer generations of citizens will become more and more dependent on networked AI structures and processes. There are challenges that need to be addressed in terms of critical thinking and heterogeneity. Networked interdependence will, more likely than not, increase our vulnerability to cyberattacks. There is also a real likelihood that there will exist sharper divisions between digital ‘haves’ and ‘have-nots,’ as well as among technologically dependent digital infrastructures. Finally, there is the question of the new ‘commanding heights’ of the digital network infrastructure’s ownership and control.”

Oscar Gandy , emeritus professor of communication at the University of Pennsylvania, responded, “We already face an ungranted assumption when we are asked to imagine human-machine ‘collaboration.’ Interaction is a bit different, but still tainted by the grant of a form of identity – maybe even personhood – to machines that we will use to make our way through all sorts of opportunities and challenges. The problems we will face in the future are quite similar to the problems we currently face when we rely upon ‘others’ (including technological systems, devices and networks) to acquire things we value and avoid those other things (that we might, or might not be aware of).”

James Scofield O’Rourke , a professor of management at the University of Notre Dame, said, “Technology has, throughout recorded history, been a largely neutral concept. The question of its value has always been dependent on its application. For what purpose will AI and other technological advances be used? Everything from gunpowder to internal combustion engines to nuclear fission has been applied in both helpful and destructive ways. Assuming we can contain or control AI (and not the other way around), the answer to whether we’ll be better off depends entirely on us (or our progeny). ‘The fault, dear Brutus, is not in our stars, but in ourselves, that we are underlings.’”

Simon Biggs , a professor of interdisciplinary arts at the University of Edinburgh, said, “AI will function to augment human capabilities. The problem is not with AI but with humans. As a species we are aggressive, competitive and lazy. We are also empathic, community minded and (sometimes) self-sacrificing. We have many other attributes. These will all be amplified. Given historical precedent, one would have to assume it will be our worst qualities that are augmented. My expectation is that in 2030 AI will be in routine use to fight wars and kill people, far more effectively than we can currently kill. As societies we will be less affected by this as we currently are, as we will not be doing the fighting and killing ourselves. Our capacity to modify our behaviour, subject to empathy and an associated ethical framework, will be reduced by the disassociation between our agency and the act of killing. We cannot expect our AI systems to be ethical on our behalf – they won’t be, as they will be designed to kill efficiently, not thoughtfully. My other primary concern is to do with surveillance and control. The advent of China’s Social Credit System (SCS) is an indicator of what it likely to come. We will exist within an SCS as AI constructs hybrid instances of ourselves that may or may not resemble who we are. But our rights and affordances as individuals will be determined by the SCS. This is the Orwellian nightmare realised.”

Mark Surman , executive director of the Mozilla Foundation, responded, “AI will continue to concentrate power and wealth in the hands of a few big monopolies based on the U.S. and China. Most people – and parts of the world – will be worse off.”

William Uricchio , media scholar and professor of comparative media studies at MIT, commented, “AI and its related applications face three problems: development at the speed of Moore’s Law, development in the hands of a technological and economic elite, and development without benefit of an informed or engaged public. The public is reduced to a collective of consumers awaiting the next technology. Whose notion of ‘progress’ will prevail? We have ample evidence of AI being used to drive profits, regardless of implications for long-held values; to enhance governmental control and even score citizens’ ‘social credit’ without input from citizens themselves. Like technologies before it, AI is agnostic. Its deployment rests in the hands of society. But absent an AI-literate public, the decision of how best to deploy AI will fall to special interests. Will this mean equitable deployment, the amelioration of social injustice and AI in the public service? Because the answer to this question is social rather than technological, I’m pessimistic. The fix? We need to develop an AI-literate public, which means focused attention in the educational sector and in public-facing media. We need to assure diversity in the development of AI technologies. And until the public, its elected representatives and their legal and regulatory regimes can get up to speed with these fast-moving developments we need to exercise caution and oversight in AI’s development.”

The remainder of this report is divided into three sections that draw from hundreds of additional respondents’ hopeful and critical observations: 1) concerns about human-AI evolution, 2) suggested solutions to address AI’s impact, and 3) expectations of what life will be like in 2030, including respondents’ positive outlooks on the quality of life and the future of work, health care and education. Some responses are lightly edited for style.

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• Published: 13 January 2020

The role of artificial intelligence in achieving the Sustainable Development Goals

• Ricardo Vinuesa   ORCID: orcid.org/0000-0001-6570-5499 1 ,
• Hossein Azizpour   ORCID: orcid.org/0000-0001-5211-6388 2 ,
• Iolanda Leite 2 ,
• Madeline Balaam 3 ,
• Virginia Dignum 4 ,
• Sami Domisch   ORCID: orcid.org/0000-0002-8127-9335 5 ,
• Anna Felländer 6 ,
• Simone Daniela Langhans 7 , 8 ,
• Max Tegmark 9 &
• Francesco Fuso Nerini   ORCID: orcid.org/0000-0002-4770-4051 10  

Nature Communications volume  11 , Article number:  233 ( 2020 ) Cite this article

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• Computational science
• Developing world
• Energy efficiency

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.

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A definition, benchmark and database of AI for social good initiatives

AI for social good: unlocking the opportunity for positive impact

Accelerating evidence-informed decision-making for the Sustainable Development Goals using machine learning

Introduction.

The emergence of artificial intelligence (AI) is shaping an increasing range of sectors. For instance, AI is expected to affect global productivity 1 , equality and inclusion 2 , environmental outcomes 3 , and several other areas, both in the short and long term 4 . Reported potential impacts of AI indicate both positive 5 and negative 6 impacts on sustainable development. However, to date, there is no published study systematically assessing the extent to which AI might impact all aspects of sustainable development—defined in this study as the 17 Sustainable Development Goals (SDGs) and 169 targets internationally agreed in the 2030 Agenda for Sustainable Development 7 . This is a critical research gap, as we find that AI may influence the ability to meet all SDGs.

Here we present and discuss implications of how AI can either enable or inhibit the delivery of all 17 goals and 169 targets recognized in the 2030 Agenda for Sustainable Development. Relationships were characterized by the methods reported at the end of this study, which can be summarized as a consensus-based expert elicitation process, informed by previous studies aimed at mapping SDGs interlinkages 8 , 9 , 10 . A summary of the results is given in Fig.  1 and the Supplementary Data  1 provides a complete list of all the SDGs and targets, together with the detailed results from this work. Although there is no internationally agreed definition of AI, for this study we considered as AI any software technology with at least one of the following capabilities: perception—including audio, visual, textual, and tactile (e.g., face recognition), decision-making (e.g., medical diagnosis systems), prediction (e.g., weather forecast), automatic knowledge extraction and pattern recognition from data (e.g., discovery of fake news circles in social media), interactive communication (e.g., social robots or chat bots), and logical reasoning (e.g., theory development from premises). This view encompasses a large variety of subfields, including machine learning.

Documented evidence of the potential of AI acting as ( a ) an enabler or ( b ) an inhibitor on each of the SDGs. The numbers inside the colored squares represent each of the SDGs (see the Supplementary Data  1 ). The percentages on the top indicate the proportion of all targets potentially affected by AI and the ones in the inner circle of the figure correspond to proportions within each SDG. The results corresponding to the three main groups, namely Society, Economy, and Environment, are also shown in the outer circle of the figure. The results obtained when the type of evidence is taken into account are shown by the inner shaded area and the values in brackets.

Documented connections between AI and the SDGs

Our review of relevant evidence shows that AI may act as an enabler on 134 targets (79%) across all SDGs, generally through a technological improvement, which may allow to overcome certain present limitations. However, 59 targets (35%, also across all SDGs) may experience a negative impact from the development of AI. For the purpose of this study, we divide the SDGs into three categories, according to the three pillars of sustainable development, namely Society, Economy, and Environment 11 , 12 (see the Methods section). This classification allows us to provide an overview of the general areas of influence of AI. In Fig.  1 , we also provide the results obtained when weighting how appropriate is the evidence presented in each reference to assess an interlinkage to the percentage of targets assessed, as discussed in the Methods section and below. A detailed assessment of the Society, Economy, and Environment groups, together with illustrative examples, are discussed next.

AI and societal outcomes

Sixty-seven targets (82%) within the Society group could potentially benefit from AI-based technologies (Fig.  2 ). For instance, in SDG 1 on no poverty, SDG 4 on quality education, SDG 6 on clean water and sanitation, SDG 7 on affordable and clean energy, and SDG 11 on sustainable cities, AI may act as an enabler for all the targets by supporting the provision of food, health, water, and energy services to the population. It can also underpin low-carbon systems, for instance, by supporting the creation of circular economies and smart cities that efficiently use their resources 13 , 14 . For example, AI can enable smart and low-carbon cities encompassing a range of interconnected technologies such as electrical autonomous vehicles and smart appliances that can enable demand response in the electricity sector 13 , 14 (with benefits across SDGs 7, 11, and 13 on climate action). AI can also help to integrate variable renewables by enabling smart grids that partially match electrical demand to times when the sun is shining and the wind is blowing 13 . Fewer targets in the Society group can be impacted negatively by AI (31 targets, 38%) than the ones with positive impact. However, their consideration is crucial. Many of these relate to how the technological improvements enabled by AI may be implemented in countries with different cultural values and wealth. Advanced AI technology, research, and product design may require massive computational resources only available through large computing centers. These facilities have a very high energy requirement and carbon footprint 15 . For instance, cryptocurrency applications such as Bitcoin are globally using as much electricity as some nations’ electrical demand 16 , compromising outcomes in the SDG 7 sphere, but also on SDG 13 on Climate Action. Some estimates suggest that the total electricity demand of information and communications technologies (ICTs) could require up to 20% of the global electricity demand by 2030, from around 1% today 15 . Green growth of ICT technology is therefore essential 17 . More efficient cooling systems for data centers, broader energy efficiency, and renewable-energy usage in ICTs will all play a role in containing the electricity demand growth 15 . In addition to more efficient and renewable-energy-based data centers, it is essential to embed human knowledge in the development of AI models. Besides the fact that the human brain consumes much less energy than what is used to train AI models, the available knowledge introduced in the model (see, for instance, physics-informed deep learning 18 ) does not need to be learnt through data-intensive training, a fact that may significantly reduce the associated energy consumption. Although AI-enabled technology can act as a catalyst to achieve the 2030 Agenda, it may also trigger inequalities that may act as inhibitors on SDGs 1, 4, and 5. This duality is reflected in target 1.1, as AI can help to identify areas of poverty and foster international action using satellite images 5 . On the other hand, it may also lead to additional qualification requirements for any job, consequently increasing the inherent inequalities 19 and acting as an inhibitor towards the achievement of this target.

Documented evidence of positive or negative impact of AI on the achievement of each of the targets from SDGs 1, 2, 3, 4, 5, 6, 7, 11, and 16 ( https://www.un.org/sustainabledevelopment/ ). Each block in the diagram represents a target (see the Supplementary Data  1 for additional details on the targets). For targets highlighted in green or orange, we found published evidence that AI could potentially enable or inhibit such target, respectively. The absence of highlighting indicates the absence of identified evidence. It is noteworthy that this does not necessarily imply the absence of a relationship. (The content of of this figure has not been reviewed by the United Nations and does not reflect its views).

Another important drawback of AI-based developments is that they are traditionally based on the needs and values of nations in which AI is being developed. If AI technology and big data are used in regions where ethical scrutiny, transparency, and democratic control are lacking, AI might enable nationalism, hate towards minorities, and bias election outcomes 20 . The term “big nudging” has emerged to represent using big data and AI to exploit psychological weaknesses to steer decisions—creating problems such as damaging social cohesion, democratic principles, and even human rights 21 . AI has been recently utilized to develop citizen scores, which are used to control social behavior 22 . This type of score is a clear example of threat to human rights due to AI misuse and one of its biggest problems is the lack of information received by the citizens on the type of analyzed data and the consequences this may have on their lives. It is also important to note that AI technology is unevenly distributed: for instance, complex AI-enhanced agricultural equipment may not be accessible to small farmers and thus produce an increased gap with respect to larger producers in more developed economies 23 , consequently inhibiting the achievement of some targets of SDG 2 on zero hunger. There is another important shortcoming of AI in the context of SDG 5 on gender equality: there is insufficient research assessing the potential impact of technologies such as smart algorithms, image recognition, or reinforced learning on discrimination against women and minorities. For instance, machine-learning algorithms uncritically trained on regular news articles will inadvertently learn and reproduce the societal biases against women and girls, which are embedded in current languages. Word embeddings, a popular technique in natural language processing, have been found to exacerbate existing gender stereotypes 2 . In addition to the lack of diversity in datasets, another main issue is the lack of gender, racial, and ethnic diversity in the AI workforce 24 . Diversity is one of the main principles supporting innovation and societal resilience, which will become essential in a society exposed to changes associated to AI development 25 . Societal resilience is also promoted by decentralization, i.e., by the implementation of AI technologies adapted to the cultural background and the particular needs of different regions.

AI and economic outcomes

The technological advantages provided by AI may also have a positive impact on the achievement of a number of SDGs within the Economy group. We have identified benefits from AI on 42 targets (70%) from these SDGs, whereas negative impacts are reported in 20 targets (33%), as shown in Fig.  1 . Although Acemoglu and Restrepo 1 report a net positive impact of AI-enabled technologies associated to increased productivity, the literature also reflects potential negative impacts mainly related to increased inequalities 26 , 27 , 28 , 29 . In the context of the Economy group of SDGs, if future markets rely heavily on data analysis and these resources are not equally available in low- and middle- income countries, the economical gap may be significantly increased due to the newly introduced inequalities 30 , 31 significantly impacting SDGs 8 (decent work and economic growth), 9 (industry, innovation and infrastructure), and 10 (reduced inequalities). Brynjolfsson and McAfee 31  argue that AI can exacerbate inequality also within nations. By replacing old jobs with ones requiring more skills, technology disproportionately rewards the educated: since the mid 1970s, the salaries in the United States (US) salaries rose about 25% for those with graduate degrees, while the average high-school dropout took a 30% pay cut. Moreover, automation shifts corporate income to those who own companies from those who work there. Such transfer of revenue from workers to investors helps explain why, even though the combined revenues of Detroit's “Big 3” (GM, Ford, and Chrysler) in 1990 were almost identical to those of Silicon Valley's “Big 3” (Google, Apple, and Facebook) in 2014, the latter had 9 times fewer employees and were worth 30 times more on the stock market 32 . Figure  3 shows an assessment of the documented positive and negative effects on the various targets within the SDGs in the Economy group.

Documented evidence of positive or negative impact of AI on the achievement of each of the targets from SDGs 8, 9, 10, 12, and 17 ( https://www.un.org/sustainabledevelopment/ ). The interpretation of the blocks and colors is as in Fig.  2 .  (The content of of this figure has not been reviewed by the United Nations and does not reflect its views).

Although the identified linkages in the Economy group are mainly positive, trade-offs cannot be neglected. For instance, AI can have a negative effect on social media usage, by showing users content specifically suited to their preconceived ideas. This may lead to political polarization 33 and affect social cohesion 21 with consequences in the context of SDG 10 on reduced inequalities. On the other hand, AI can help identify sources of inequality and conflict 34 , 35 , and therewith potentially reduce inequalities, for instance, by using simulations to assess how virtual societies may respond to changes. However, there is an underlying risk when using AI to evaluate and predict human behavior, which is the inherent bias in the data. It has been reported that a number of discriminatory challenges are faced in the automated targeting of online job advertising using AI 35 , essentially related to the previous biases in selection processes conducted by human recruiters. The work by Dalenberg 35 highlights the need of modifying the data preparation process and explicitly adapting the AI-based algorithms used for selection processes to avoid such biases.

AI and environmental outcomes

The last group of SDGs, i.e., the one related to Environment, is analyzed in Fig.  4 . The three SDGs in this group are related to climate action, life below water and life on land (SDGs 13, 14, and 15). For the Environment group, we identified 25 targets (93%) for which AI could act as an enabler. Benefits from AI could be derived by the possibility of analyzing large-scale interconnected databases to develop joint actions aimed at preserving the environment. Looking at SDG 13 on climate action, there is evidence that AI advances will support the understanding of climate change and the modeling of its possible impacts. Furthermore, AI will support low-carbon energy systems with high integration of renewable energy and energy efficiency, which are all needed to address climate change 13 , 36 , 37 . AI can also be used to help improve the health of ecosystems. The achievement of target 14.1, calling to prevent and significantly reduce marine pollution of all kinds, can benefit from AI through algorithms for automatic identification of possible oil spills 38 . Another example is target 15.3, which calls for combating desertification and restoring degraded land and soil. According to Mohamadi et al. 39 , neural networks and objective-oriented techniques can be used to improve the classification of vegetation cover types based on satellite images, with the possibility of processing large amounts of images in a relatively short time. These AI techniques can help to identify desertification trends over large areas, information that is relevant for environmental planning, decision-making, and management to avoid further desertification, or help reverse trends by identifying the major drivers. However, as pointed out above, efforts to achieve SDG 13 on climate action could be undermined by the high-energy needs for AI applications, especially if non carbon-neutral energy sources are used. Furthermore, despite the many examples of how AI is increasingly applied to improve biodiversity monitoring and conservation 40 , it can be conjectured that an increased access to AI-related information of ecosystems may drive over-exploitation of resources, although such misuse has so far not been sufficiently documented. This aspect is further discussed below, where currently identified gaps in AI research are considered.

Documented evidence of positive or negative impact of AI on the achievement of each of the targets from SDGs 13, 14, and 15 ( https://www.un.org/sustainabledevelopment/ ). The interpretation of the blocks and colors is as in Fig.  2 . (The content of of this figure has not been reviewed by the United Nations and does not reflect its views).

An assessment of the collected evidence on the interlinkages

A deeper analysis of the gathered evidence was undertaken as shown in Fig.  1 (and explained in the Methods section). In practice, each interlinkage was weighted based on the applicability and appropriateness of each of the references to assess a specific interlinkage—and possibly identify research gaps. Although accounting for the type of evidence has a relatively small effect on the positive impacts (we see a reduction of positively affected targets from 79% to 71%), we observe a more significant reduction (from 35% to 23%) in the targets with negative impact of AI. This can be partly due the fact that AI research typically involves quantitative methods that would bias the results towards the positive effects. However, there are some differences across the Society, Economy and Environment spheres. In the Society sphere, when weighting the appropriateness of evidence, positively affected targets diminish by 5 percentage points (p.p.) and negatively affected targets by 13 p.p. In particular, weighting the appropriateness of evidence on negative impacts on SDG 1 (on no poverty) and SDG 6 (on clean water and sanitation) reduces the fraction of affected targets by 43 p.p. and 35 p.p., respectively. In the Economy group instead, positive impacts are reduced more (15 p.p.) than negative ones (10 p.p.) when taking into account the appropriateness of the found evidence to speak of the issues. This can be related to the extensive study in literature assessing the displacement of jobs due to AI (because of clear policy and societal concerns), but overall the longer-term benefits of AI on the economy are perhaps not so extensively characterized by currently available methods. Finally, although the weighting of evidence decreases the positive impacts of AI on the Environment group only by 8 p.p., the negative impacts see the largest average reduction (18 p.p.). This is explained by the fact that, although there are some indications of the potential negative impact of AI on this SDG, there is no strong evidence (in any of the targets) supporting this claim, and therefore this is a relevant area for future research.

In general, the fact that the evidence on interlinkages between AI and the large majority of targets is not based on tailored analyses and tools to refer to that particular issue provides a strong rationale to address a number of research gaps, which are identified and listed in the section below.

Research gaps on the role of AI in sustainable development

The more we enable SDGs by deploying AI applications, from autonomous vehicles 41 to AI-powered healthcare solutions 42 and smart electrical grids 13 , the more important it becomes to invest in the AI safety research needed to keep these systems robust and beneficial, so as to prevent them from malfunctioning, or from getting hacked 43 . A crucial research venue for a safe integration of AI is understanding catastrophes, which can be enabled by a systemic fault in AI technology. For instance, a recent World Economic Forum (WEF) report raises such a concern due to the integration of AI in the financial sector 44 . It is therefore very important to raise awareness on the risks associated to possible failures of AI systems in a society progressively more dependent on this technology. Furthermore, although we were able to find numerous studies suggesting that AI can potentially serve as an enabler for many SDG targets and indicators, a significant fraction of these studies have been conducted in controlled laboratory environments, based on limited datasets or using prototypes 45 , 46 , 47 . Hence, extrapolating this information to evaluate the real-world effects often remains a challenge. This is particularly true when measuring the impact of AI across broader scales, both temporally and spatially. We acknowledge that conducting controlled experimental trials for evaluating real-world impacts of AI can result in depicting a snapshot situation, where AI tools are tailored towards that specific environment. However, as society is constantly changing (also due to factors including non-AI-based technological advances), the requirements set for AI are changing as well, resulting in a feedback loop with interactions between society and AI. Another underemphasized aspect in existing literature is the resilience of the society towards AI-enabled changes. Therefore, novel methodologies are required to ensure that the impact of new technologies are assessed from the points of view of efficiency, ethics, and sustainability, prior to launching large-scale AI deployments. In this sense, research aimed at obtaining insight on the reasons for failure of AI systems, introducing combined human–machine analysis tools 48 , are an essential step towards accountable AI technology, given the large risk associated to such a failure.

Although we found more published evidence of AI serving as an enabler than as an inhibitor on the SDGs, there are at least two important aspects that should be considered. First, self-interest can be expected to bias the AI research community and industry towards publishing positive results. Second, discovering detrimental aspects of AI may require longer-term studies and, as mentioned above, there are not many established evaluation methodologies available to do so. Bias towards publishing positive results is particularly apparent in the SDGs corresponding to the Environment group. A good example of this bias is target 14.5 on conserving coastal and marine areas, where machine-learning algorithms can provide optimum solutions given a wide range of parameters regarding the best choice of areas to include in conservation networks 49 . However, even if the solutions are optimal from a mathematical point of view (given a certain range of selected parameters), additional research would be needed to assess the long-term impact of such algorithms on equity and fairness 6 , precisely because of the unknown factors that may come into play. Regarding the second point stated above, it is likely that the AI projects with the highest potential of maximizing profit will get funded. Without control, research on AI is expected to be directed towards AI applications where funding and commercial interests are. This may result in increased inequality 50 . Consequently, there is the risk that AI-based technologies with potential to achieve certain SDGs may not be prioritized, if their expected economic impact is not high. Furthermore, it is essential to promote the development of initiatives to assess the societal, ethical, legal, and environmental implications of new AI technologies.

Substantive research and application of AI technologies to SDGs is concerned with the development of better data-mining and machine-learning techniques for the prediction of certain events. This is the case of applications such as forecasting extreme weather conditions or predicting recidivist offender behavior. The expectation with this research is to allow the preparation and response for a wide range of events. However, there is a research gap in real-world applications of such systems, e.g., by governments (as discussed above). Institutions have a number of barriers to the adoption AI systems as part of their decision-making process, including the need of setting up measures for cybersecurity and the need to protect the privacy of citizens and their data. Both aspects have implications on human rights regarding the issues of surveillance, tracking, communication, and data storage, as well as automation of processes without rigorous ethical standards 21 . Targeting these gaps would be essential to ensure the usability and practicality of AI technologies for governments. This would also be a prerequisite for understanding long-term impacts of AI regarding its potential, while regulating its use to reduce the possible bias that can be inherent to AI 6 .

Furthermore, our research suggests that AI applications are currently biased towards SDG issues that are mainly relevant to those nations where most AI researchers live and work. For instance, many systems applying AI technologies to agriculture, e.g., to automate harvesting or optimize its timing, are located within wealthy nations. Our literature search resulted in only a handful of examples where AI technologies are applied to SDG-related issues in nations without strong AI research. Moreover, if AI technologies are designed and developed for technologically advanced environments, they have the potential to exacerbate problems in less wealthy nations (e.g., when it comes to food production). This finding leads to a substantial concern that developments in AI technologies could increase inequalities both between and within countries, in ways which counteract the overall purpose of the SDGs. We encourage researchers and funders to focus more on designing and developing AI solutions, which respond to localized problems in less wealthy nations and regions. Projects undertaking such work should ensure that solutions are not simply transferred from technology-intensive nations. Instead, they should be developed based on a deep understanding of the respective region or culture to increase the likelihood of adoption and success.

Towards sustainable AI

The great wealth that AI-powered technology has the potential to create may go mainly to those already well-off and educated, while job displacement leaves others worse off. Globally, the growing economic importance of AI may result in increased inequalities due to the unevenly distributed educational and computing resources throughout the world. Furthermore, the existing biases in the data used to train AI algorithms may result in the exacerbation of those biases, eventually leading to increased discrimination. Another related problem is the usage of AI to produce computational (commercial, political) propaganda based on big data (also defined as “big nudging”), which is spread through social media by independent AI agents with the goals of manipulating public opinion and producing political polarization 51 . Despite the fact that current scientific evidence refutes technological determinism of such fake news 51 , long-term impacts of AI are possible (although unstudied) due to a lack of robust research methods. A change of paradigm is therefore needed to promote cooperation and to limit the possibilities for control of citizen behavior through AI. The concept of Finance 4.0 has been proposed 52 as a multi-currency financial system promoting a circular economy, which is aligned with societal goals and values. Informational self-determination (in which the individual takes an active role in how their data are handled by AI systems) would be an essential aspect of such a paradigm 52 . The data intensiveness of AI applications creates another problem: the need for more and more detailed information to improve AI algorithms, which is in conflict with the need of more transparent handling and protection of personal data 53 . One area where this conflict is particularly important is healthcare: Panch et al. 54 argue that although the vast amount of personal healthcare data could lead to the development of very powerful tools for diagnosis and treatment, the numerous problems associated to data ownership and privacy call for careful policy intervention. This is also an area where more research is needed to assess the possible long-term negative consequences. All the challenges mentioned above culminate in the academic discourse about legal personality of robots 55 , which may lead to alarming narratives of technological totalitarianism.

Many of these aspects result from the interplay between technological developments on one side and requests from individuals, response from governments, as well as environmental resources and dynamics on the other. Figure  5 shows a schematic representation of these dynamics, with emphasis on the role of technology. Based on the evidence discussed above, these interactions are not currently balanced and the advent of AI has exacerbated the process. A wide range of new technologies are being developed very fast, significantly affecting the way individuals live as well as the impacts on the environment, requiring new piloting procedures from governments. The problem is that neither individuals nor governments seem to be able to follow the pace of these technological developments. This fact is illustrated by the lack of appropriate legislation to ensure the long-term viability of these new technologies. We argue that it is essential to reverse this trend. A first step in this direction is to establish adequate policy and legislation frameworks, to help direct the vast potential of AI towards the highest benefit for individuals and the environment, as well as towards the achievement of the SDGs. Regulatory oversight should be preceded by regulatory insight, where policymakers have sufficient understanding of AI challenges to be able to formulate sound policy. Developing such insight is even more urgent than oversight, as policy formulated without understanding is likely to be ineffective at best and counterproductive at worst.

Schematic representation showing the identified agents and their roles towards the development of AI. Thicker arrows indicate faster change. In this representation, technology affects individuals through technical developments, which change the way people work and interact with each other and with the environment, whereas individuals would interact with technology through new needs to be satisfied. Technology (including technology itself and its developers) affects governments through new developments that need appropriate piloting and testing. Also, technology developers affect government through lobbying and influencing decision makers. Governments provide legislation and standards to technology. The governments affect individuals through policy and legislation, and individuals would require new legislation consistent with the changing circumstances from the governments. The environment interacts with technology by providing the resources needed for technological development and is affected by the environmental impact of technology. Furthermore, the environment is affected either negatively or positively by the needs, impacts, and choices of individuals and governments, which in turn require environmental resources. Finally, the environment is also an underlying layer that provides the “planetary boundaries” to the mentioned interactions.

Although strong and connected institutions (covered by SDG 16) are needed to regulate the future of AI, we find that there is limited understanding of the potential impact of AI on institutions. Examples of the positive impacts include AI algorithms aimed at improving fraud detection 56 , 57 or assessing the possible effects of certain legislation 58 , 59 . Another concern is that data-driven approaches for policing may hinder equal access to justice because of algorithm bias, particularly towards minorities 60 . Consequently, we believe that it is imperative to develop legislation regarding transparency and accountability of AI, as well as to decide the ethical standards to which AI-based technology should be subjected to. This debate is being pushed forward by initiatives such as the IEEE (Institute of Electrical and Electronics Engineers) ethical aligned design 60 and the new EU (European Union) ethical guidelines for trustworthy AI 61 . It is noteworthy that despite the importance of an ethical, responsible, and trustworthy approach to AI development and use, in a sense, this issue is independent of the aims of the article. In other words, one can envision AI applications that improve SDG outcomes while not being fully aligned with AI ethics guidelines. We therefore recommend that AI applications that target SDGs are open and explicit about guiding ethical principles, also by indicating explicitly how they align with the existing guidelines. On the other hand, the lack of interpretability of AI, which is currently one of the challenges of AI research, adds an additional complication to the enforcement of such regulatory actions 62 . Note that this implies that AI algorithms (which are trained with data consisting of previous regulations and decisions) may act as a “mirror” reflecting biases and unfair policy. This presents an opportunity to possibly identify and correct certain errors in the existing procedures. The friction between the uptake of data-driven AI applications and the need of protecting the privacy and security of the individuals is stark. When not properly regulated, the vast amount of data produced by citizens might potentially be used to influence consumer opinion towards a certain product or political cause 51 .

AI applications that have positive societal welfare implications may not always benefit each individual separately 41 . This inherent dilemma of collective vs. individual benefit is relevant in the scope of AI applications but is not one that should be solved by the application of AI itself. This has always been an issue affecting humankind and it cannot be solved in a simple way, since such a solution requires participation of all involved stakeholders. The dynamicity of context and the level of abstraction at which human values are described imply that there is not a single ethical theory that holds all the time in all situations 63 . Consequently, a single set of utilitarian ethical principles with AI would not be recommendable due to the high complexity of our societies 52 . It is also essential to be aware of the potential complexity in the interaction between human and AI agents, and of the increasing need for ethics-driven legislation and certification mechanisms for AI systems. This is true for all AI applications, but especially those that, if they became uncontrolled, could have even catastrophic effects on humanity, such as autonomous weapons. Regarding the latter, associations of AI and robotics experts are already getting together to call for legislation and limitations of their use 64 . Furthermore, associations such as the Future of Life Institute are reviewing and collecting policy actions and shared principles around the world to monitor progress towards sustainable-development-friendly AI 65 . To deal with the ethical dilemmas raised above, it is important that all applications provide openness about the choices and decisions made during design, development, and use, including information about the provenance and governance of the data used for training algorithms, and about whether and how they align with existing AI guidelines. It is therefore important to adopt decentralized AI approaches for a more equitable development of AI 66 .

We are at a critical turning point for the future of AI. A global and science-driven debate to develop shared principles and legislation among nations and cultures is necessary to shape a future in which AI positively contributes to the achievement of all the SDGs. The current choices to develop a sustainable-development-friendly AI by 2030 have the potential to unlock benefits that could go far-beyond the SDGs within our century. All actors in all nations should be represented in this dialogue, to ensure that no one is left behind. On the other hand, postponing or not having such a conversation could result in an unequal and unsustainable AI-fueled future.

In this section we describe the process employed to obtain the results described in the present study and shown in the Supplementary Data  1 . The goal was to answer the question “Is there published evidence of AI acting as an enabler or an inhibitor for this particular target?” for each of the 169 targets within the 17 SDGs. To this end, we conducted a consensus-based expert elicitation process, informed by previous studies on mapping SDGs interlinkages 8 , 9 and following Butler et al. 67 and Morgan 68 . The authors of this study are academics spanning a wide range of disciplines, including engineering, natural and social sciences, and acted as experts for the elicitation process. The authors performed an expert-driven literature search to support the identified connections between AI and the various targets, where the following sources of information were considered as acceptable evidence: published work on real-world applications (given the quality variation depending on the venue, we ensured that the publications considered in the analysis were of sufficient quality); published evidence on controlled/laboratory scenarios (given the quality variation depending on the venue, we ensured that the publications considered in the analysis were of sufficient quality); reports from accredited organizations (for instance: UN or government bodies); and documented commercial-stage applications. On the other hand, the following sources of information were not considered as acceptable evidence: educated conjectures, real-world applications without peer-reviewed research; media, public beliefs or other sources of information.

The expert elicitation process was conducted as follows: each of the SDGs was assigned to one or more main contributors, and in some cases to several additional contributors as summarized in the Supplementary Data  1 (here the initials correspond to the author names). The main contributors carried out a first literature search for that SDG and then the additional contributors completed the main analysis. One published study on a synergy or a trade-off between a target and AI was considered enough for mapping the interlinkage. However, for nearly all targets several references are provided. After the analysis of a certain SDG was concluded by the contributors, a reviewer was assigned to evaluate the connections and reasoning presented by the contributors. The reviewer was not part of the first analysis and we tried to assign the roles of the main contributor and reviewer to experts with complementary competences for each of the SDGs. The role of the reviewer was to bring up additional points of view and considerations, while critically assessing the analysis. Then, the main contributors and reviewers iteratively discussed to improve the results presented for each of the SDGs until the analysis for all the SDGs was sufficiently refined.

After reaching consensus regarding the assessment shown in the Supplementary Data  1 , we analyzed the results by evaluating the number of targets for which AI may act as an enabler or an inhibitor, and calculated the percentage of targets with positive and negative impact of AI for each of the 17 goals, as shown in Fig.  1 . In addition, we divided the SDGs into the three following categories: Society, Economy, and Environment, consistent with the classification discussed by Refs. 11 , 12 . The SDGs assigned to each of the categories are shown in Fig.  6 and the individual results from each of these groups can be observed in Figs.  2 – 4 . These figures indicate, for each target within each SDG, whether any published evidence of positive or negative impact was found.

(The content of this figure has not been reviewed by the United Nations and does not reflect its views).

Taking into account the types of evidence

In the methodology described above, a connection between AI and a certain target is established if at least one reference documenting such a link was found. As the analyzed studies rely on very different types of evidence, it is important to classify the references based on the methods employed to support their conclusions. Therefore, all the references in the Supplementary Data  1 include a classification from (A) to (D) according to the following criteria:

References using sophisticated tools and data to refer to this particular issue and with the possibility to be generalized are of type (A).

Studies based on data to refer to this particular issue, but with limited generalizability, are of type (B).

Anecdotal qualitative studies and methods are of type (C) .

Purely theoretical or speculative references are of type (D).

The various classes were assigned following the same expert elicitation process described above. Then, the contribution of these references towards the linkages is weighted and categories (A), (B), (C), and (D) are assigned relative weights of 1, 0.75, 0.5, and 0.25, respectively. It is noteworthy that, given the vast range of studies on all the SDG areas, the literature search was not exhaustive and, therefore, certain targets are related to more references than others in our study. To avoid any bias associated to the different amounts of references in the various targets, we considered the largest positive and negative weight to establish the connection with each target. Let us consider the following example: for a certain target, one reference of type (B) documents a positive connection and two references of types (A) and (D) document a negative connection with AI. In this case, the potential positive impact of AI on that target will be assessed with 0.75, while the potential negative impact is 1.

Limitations of the research

The presented analysis represents the perspective of the authors. Some literature on how AI might affect certain SDGs could have been missed by the authors or there might not be published evidence yet on such interlinkage. Nevertheless, the employed methods tried to minimize the subjectivity of the assessment. How AI might affect the delivery of each SDG was assessed and reviewed by several authors and a number of studies were reviewed for each interlinkage. Furthermore, as discussed in the Methods section, each interlinkage was discussed among a subset of authors until consensus was reached on its nature.

Finally, this study relies on the analysis of the SDGs. The SDGs provide a powerful lens for looking at internationally agreed goals on sustainable development and present a leap forward compared with the Millenium Development Goals in the representation of all spheres of sustainable development, encompassing human rights 69 , social sustainability, environmental outcomes, and economic development. However, the SDGs are a political compromise and might be limited in the representation of some of the complex dynamics and cross-interactions among targets. Therefore, the SDGs have to be considered in conjunction with previous and current, and other international agreements 9 . For instance, as pointed out in a recent work by UN Human Rights 69 , human rights considerations are highly embedded in the SDGs. Nevertheless, the SDGs should be considered as a complement, rather than a replacement, of the United Nations Universal Human Rights Charter 70 .

Data availability

The authors declare that all the data supporting the findings of this study are available within the paper and its Supplementary Data  1 file .

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Acknowledgements

R.V. acknowledges funding provided by KTH Sustainability Office. I.L. acknowledges the Swedish Research Council (registration number 2017-05189) and funding through an Early Career Research Fellowship granted by the Jacobs Foundation. M.B. acknowledges Implicit SSF: Swedish Foundation for Strategic Research project RIT15-0046. V.D. acknowledges the support of the Wallenberg AI, Autonomous Systems, and Software Program (WASP) program funded by the Knut and Alice Wallenberg Foundation. S.D. acknowledges funding from the Leibniz Competition (J45/2018). S.L. acknowledges funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska–Curie grant agreement number 748625. M.T. was supported by the Ethics and Governance of AI Fund. F.F.N. acknowledges funding from the Formas grant number 2018-01253.

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The role of AI in future warfare

Subscribe to techstream, michael e. o’hanlon michael e. o’hanlon director of research - foreign policy , director - strobe talbott center for security, strategy, and technology , co-director - africa security initiative , senior fellow - foreign policy , strobe talbott center for security, strategy, and technology , philip h. knight chair in defense and strategy @michaeleohanlon.

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This report is part of “ A Blueprint for the Future of AI ,” a series from the Brookings Institution that analyzes the new challenges and potential policy solutions introduced by artificial intelligence and other emerging technologies.

To illustrate how artificial intelligence (AI) could affect the future battlefield, consider the following scenario based on a future book I am writing entitled The Senkaku Paradox: Risking Great Power War over Limited Stakes. The scenario, imagined to occur sometime between now and 2040, begins with a hypothesized Russian “green men” attack against a small farming village in eastern Estonia or Latvia. Russia’s presumed motive would be to sow discord and dissent within NATO, weakening the alliance. Estonia and Latvia are NATO member states, and thus the United States is sworn to defend them. But in the event of such a Russian aggression, a huge, direct NATO response may or may not be wise. Furthermore, the robotics and AI dimension of this scenario, and a number of others similar to it, will likely get more interesting as the years go by.

A hypothetical scenario in which Russia creates a pretext to slice off a piece of an eastern Baltic state, occupying it in purported “defense” of native Russian speakers there, could cause enormous problems if NATO chose to reverse the aggression. In that event, it could require a massive deployment of Operation Desert Storm-like proportions to liberate the territory while facing down any Russian reinforcements that might be sent. In a less successful case, Russia could interdict major elements of that attempted NATO deployment through some combination of cyberattacks, high-altitude nuclear bursts causing electromagnetic pulse, targeted missile or aerial strikes on ports and major ships, and perhaps even an “escalate to de-escalate” series of carefully chosen nuclear detonations against very specific targets on land or sea. 1  While the latter concept of nuclear preemption is not formally part of Russian military doctrine, it could influence actual Russian military options today. 2 Alternatively, the NATO deployment could succeed, only to face subsequent Russian nuclear strikes once evidence of NATO’s conventional superiority on the Baltic battlefields had presented Moscow with the Hobson’s choice of either escalating or losing. 3

By 2040, some aspects of this kind of scenario could improve for American and NATO interests. The clarity and perhaps the scale of NATO’s security commitments to the Baltic states might have strengthened, reducing the chances of deterrence failure in the first place and improving the initial capacity for resistance to any Russian aggression. 4 But on balance, technological innovation, including advancements in robotics and AI, makes it quite possible that things could also get worse.

To be sure, missile defenses will improve. But so will the missiles they have to counter, in terms of their speed and ability to maneuver warheads, along with the use of multispectral sensors or seekers.

Most aspects of the nuclear situation are unlikely to change. Missile defenses may improve, and may include lasers for point defense in some places. These laser defenses could help protect ships or ports or airfields against various types of attack. But because such laser weapons inevitably fall off rapidly in power (as the square of the distance between the weapon and its target), it will be challenging for missile defenses to provide area protection. Thus, while it is at least conceivable that ports and airfields could become much better protected, it is hard to escape the prediction that rail lines, road networks involving large numbers of bridges, tunnels, or elevated routes, and large concentrations of supplies in depots or warehouses will be at least as vulnerable in 2040 as they are today. To be sure, missile defenses will improve. But so will the missiles they have to counter, in terms of their speed and ability to maneuver warheads, along with the use of multispectral sensors or seekers.

Satellites in space are likely to remain highly vulnerable to nuclear attack. That is especially true of satellites in low Earth orbit (LEO), as they are located at altitudes similar to those traversed by ballistic missiles on typical flight trajectories, so they can be attacked by ballistic missile defense technologies. Such objects are also vulnerable, over a period of months, to the residual effects of nuclear detonations in the Van Allen belts—areas of the Earth’s magnetic field where protons and electrons generated by nuclear explosions can “get stuck,” damaging satellites on each orbital pass. Shielding can, in theory, protect against more distant explosions and against such radiation-pumped Van Allen belts, at a typical cost of perhaps 10 percent of the overall satellite. However, it is unlikely that most commercial satellites will be shielded unless the government subsidizes such endeavors. Even with shielding, advanced imaging satellites and other high-value assets in LEO will remain vulnerable since they may be individually and directly attacked by an adversary. 5

By 2040, many cyber systems controlling NATO weaponry and other platforms should be more resilient to attack. That is because NATO will have had two decades to address problems that are now widely understood. That is unlike the case 20 years ago, when, even though the Y2K debacle and other scares should have sobered people to the risks of inadequate computer security measures, a general sense of complacency about great-power relations discouraged meaningful action against threats to electronics from hacking, high-altitude nuclear bursts, malicious supply-chain actors who might compromise the integrity of semiconductor chips, and so on. Admittedly, this conclusion assumes greater vigilance on the part of NATO states than will perhaps prove to be the case. However, progress in this arena will probably not be uniform. It seems relatively unlikely to result in meaningful hardening of the critical civilian infrastructure on which militaries depend.

Even if classic computer hacking, spoofing, advanced persistent threats, and related measures gradually lose some of their effectiveness, a new set of challenges is appearing on the horizon. One challenge could be a more efficient form of advanced persistent threat in which efforts to penetrate an adversary’s computer systems employ automated capabilities with massive raw computational power that continually adjust tactics to the defenses encountered.

Even if classic computer hacking, spoofing, advanced persistent threats, and related measures gradually lose some of their effectiveness, a new set of challenges is appearing on the horizon.

Another major complicating development could be the advent of constellations or swarms of smart robotic devices. For example, by 2040, large numbers of smart sea mines could pose enormous threats to shipping; in the scenario of Russian aggression, NATO would need to mount a response to these threats. 6 The devices might in effect be miniature submarines, with sensors and explosives as payload. Russia is already strong in submarine technology 7 and could probably master this type of technology in the years to come. Such unmanned underwater vehicles (UUVs) could be widely deployed in places like the Baltic Sea in times of crisis. Rather than having to hunt for a couple dozen Russian submarines, as might be the case today—already a daunting proposition—NATO forces seeking to reach Baltic ports might need to search for hundreds or even thousands of potent threats. It seems implausible that arms control agreements would prevent the development and deployment of such autonomous systems, not only because of the verification challenges but also because the United States itself will feel powerful incentives to create more autonomous systems, including those with the ability to employ lethal force under certain types of conditions, as Paul Scharre has convincingly argued. 8

In another scenario, swarms of quadcopters (unmanned helicopters with four rotors), each packing several kilograms of explosives—thus able to destroy a modern jet if detonated at the right location—might attack NATO air bases and the aircraft on them. Terminal defenses using lasers could possibly destroy some of the incoming threat devices or weapons, but the swarm could then choose a different attack route or seek to overwhelm a defense with a saturation attack. Swarms could also deploy in the airspace surrounding an airfield, staying out of range of any such directed-energy defenses and attempting to strike aircraft as they left or approached a runway.

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There are some situations that pose particular challenges. Imagine loitering aerial devices akin to the sensor fuzed weapon (SFW) that have been part of the U.S. armamentarium for years. This weapon is somewhat controversial: it is categorized as a “cluster munition,” a type of weapon banned by international convention, though the United States is not a party to the accord. 9 However, it is better thought of as a type of robotic weapon. The benefit of such technologies in combat was discussed extensively as far back as 1998, when a RAND study envisioned their use in situations such as an Iraqi armored vehicle attack against Saudi Arabia on major highways. In that model, which considered technologies available at the time, some 10,000 weapons carrying 40 Skeet submunitions, or perhaps the Brilliant Anti-Tank (BAT) weapon, would suffice to destroy several thousand armored vehicles and effectively halt an enemy assault. The total cost of the ordnance was estimated at several billion dollars. 10 Such munitions could be used in a similar way against NATO movements on major roads in Europe, advancing from western points toward Poland and the Baltic states, with the munitions delivered in the future by small robotic devices. Swarms of robotic devices carrying munitions payloads could also be used to attack trains or road convoys in transit, perhaps after being positioned by special forces that had penetrated into NATO territory.

Another type of robotic swarm might be used to create an interconnected network of unmanned aquatic systems functioning, in effect, as mobile mines or torpedoes. This is not presently a technology concept that the U.S. Navy has come close to operationalizing; a 2013 RAND study lists the technology maturity of such systems as between 1 and 3 on a Technology Readiness Level scale that goes from 1 to 9. 11 However, the constituent technologies, such as automated sensors, are already largely available. 12 As AI improves, a constellation of such devices could be made largely autonomous.

Much of the relevant technology is already available. Drug-trafficking organizations have been using semisubmersibles to transport drugs to the United States for years, now craft with very slender vessel designs that are efficient at cutting through waves (though still slower than most warships). 13 A decade ago, it was already possible to build such boats with a payload of 10 tons and at a cost of less than $1 million per vessel; they were often manned then, but making them fully autonomous would not be a major leap. 14

Clearing operations against what would in effect be mobile and self-healing minefields populated by devices that can communicate with each other and reposition themselves to create dense, lethal networks will be much more difficult than clearing current threats.

Such capabilities create the specter of not just “smart mines” (able to distinguish one type of ship from another before detonating) but mobile, re-deployable, and agile mines operating as autonomous networks. Since mines have been responsible for most U.S. Navy ship losses since World War II, this is a particularly unsettling prospect. 15 In modern times, the U.S. Navy has primarily avoided mines by staying clear of waters where they might be deployed, as opposed to having any particularly effective counter to them. The main alternative, as outlined by Caitlin Talmadge, would be to conduct extensive clearing operations to create relatively narrow channels for movement, if enough time is available for such purposes. (Talmadge estimated a month or more in a scenario in which Iran mined the Persian Gulf and the U.S. Navy and allies then sought to clear the waterways.) 16 Used against America’s enemies of recent decades, this might have been a doable proposition. But when a U.S. Navy vessel has to approach a Baltic port against a Russian foe of 2025 or 2030 or 2035 or 2040, the situation could be very different. Clearing operations against what would in effect be mobile and self-healing minefields populated by devices that can communicate with each other and reposition themselves to create dense, lethal networks will be much more difficult than clearing current threats.

If NATO figured out how to jam the communications between smart, unmanned, mobile mines, the adversary’s robotic systems might simply be deployed in redundant patterns to be sure there were no gaps in coverage. They could also be programmed to change their positions every so often to elude neutralization and to repair any potential gaps in their coverage—even if there were no central data processor that actually knew where the gaps were located and even if space-based navigation systems were disabled (since the UUVs could have various types of inertial or bottom-following guidance). 17 The network could be set up simply to play the odds, in an environment of little communication and poor information exchange.

How many such UUVs might be needed to achieve the desired effect of rendering transport ships highly vulnerable as they approached a port such as Talinn or Riga? As one possibility, the devices might be released from Kaliningrad with instructions to move eastward toward the littoral waters of those port cities. Even existing battery technology makes a “swim” of such distance within reach. 18 Progress in nanomaterials and other constituent elements of batteries may further improve performance in the years ahead.

One way to estimate the quantitative requirements for such a UUV network is to compute how long a picket line might be needed near those ports to cover all possible lines of approach, and then estimate the needed density of separate armed devices along that line. Whatever estimate followed from this simple calculation might then be multiplied by two or three or four to account for attrition of some devices as a result of NATO anti-mining efforts or malfunction.

The approach to Riga, Latvia, is through a body of water about 40 miles wide at points near the port. The picket line might be set up roughly three-to-five miles offshore, where water depths are 100 feet or more—making it hard to detect any submersible object visually. 19 The math might go something like this:

• If the range of each UUV’s lethal mechanism is similar to that of a modern torpedo such as the U.S. Mark 48, then they might be spaced every one-to-five miles—based on the fact that these torpedoes can typically lock on to targets from a distance of 4,000 yards. 20
• To improve the density of the picket line and allow multiple shots to be taken at a given transport, the spacing might be kept at perhaps one mile, meaning that 40 UUVs would be needed to populate a given picket line.
• With multiple picket lines, perhaps 200-to-500 UUVs in all, at a cost of no more than several hundred million dollars, it would be very difficult to approach the wharves at Riga.

Of course, the United States and other NATO countries could attempt to thwart the operations of these UUVs. They could try to destroy them en masse at their source before the UUVs could be released. They could also create their own robotic swarms designed to find, identify, and neutralize the attacking weapons.

But there would be a fundamental difference from today’s situation. The kind of impunity that U.S. forces have enjoyed for decades during intercontinental movement would be threatened to some degree and could no longer be assumed. And even Russia’s relatively modest military resources would still be ample for the kinds of investments needed in these domains, in purely financial terms, as the above calculations underscore.

If necessary, NATO could avoid some of these problems by staying out of the Baltic Sea. U.S., Canadian, and U.K. forces could deploy to France or the Netherlands or Germany and then move eastward toward Russia, picking up allied help along the way. This strategy might eventually work—but with considerable time delays and with vulnerabilities during movement along road and rail networks. Moreover, Russia might doubt that NATO would have the will to mount such a response. Thus, the key goal of upholding deterrence might be lost, even if, in theory, a war could eventually be won.

Robotics and AI could take on a central, and very important, role in warfare by 2040—even without anything resembling a terminator or a large killer robot.

Because of NATO’s strategic depth and its enormous resource disparity when measured against Russia’s—two advantages the United States and its Pacific allies would likely not have in the Pacific theater against China—NATO would still be favored to win a conventional-only conflict in eastern Europe 20 years from now. But the degree of difficulty would be quite considerable and the degree of escalatory risk highly unsettling. In my book, I attempt to offer Washington and other NATO capitals some policy options. For the purposes of this essay, the simple point is this: robotics and AI could take on a central, and very important, role in warfare by 2040—even without anything resembling a terminator or a large killer robot.

• See, for example, Fabrice Pothier, “An Area-Access Strategy for NATO,” Survival 59, no. 3 (June–July 2017), pp. 73–79.
• Alexander Velez-Green, “Russian Strategists Debate Preemption as Defense against NATO Surprise Attack” (Washington: Center for a New American Security, March 2018).
• In their discussion of the new U.S. Army and Air Force concept of Multi-Domain Battle, General David Perkins and General James Holmes convincingly argue that an enemy will contest U.S. and allied operations across many different realms simultaneously. See General David G. Perkins and General James M. Holmes, “Multi-Domain Battle: Converging Concepts toward a Joint Solution,” Joint Forces Quarterly 88 (1st quarter, 2018).
• Paul B. Stares, Preventive Engagement: How America Can Avoid War, Stay Strong, and Keep the Peace (Columbia University Press, 2018), pp. 154–55.
• Barry D. Watts, The Military Uses of Space: A Diagnostic Assessment (Washington: Center for Strategic and Budgetary Assessments, 2001), p. 99; Peter L. Hays, United States Military Space: Into the Twenty-First Century (Montgomery, Ala.: Air University Press, 2002), pp. 121–24; Michael E. O’Hanlon, Neither Star Wars Nor Sanctuary: Constraining the Military Uses of Space (Brookings, 2004), pp. 67–70, 126–27; and Bruce G. Blair, Strategic Command and Control: Redefining the Nuclear Threat (Brookings, 1985), pp. 201–07.
• Such mines could be developed in fairly short order today; see Ochmanek and others, U.S. Military Capabilities and Forces for a Dangerous World, pp. 16–19, 28.
• Dave Majumdar, “The Rise of Russia’s Military,” National Interest 156 (July/August 2018), pp. 36–46.
• Paul Scharre, Army of None: Autonomous Weapons and the Future of War (New York: W. W. Norton, 2018).
• Thomas Gibbons-Neff, “Why the Last U.S. Company Making Cluster Bombs Won’t Produce Them Anymore,” Washington Post, September 2, 2016.
• David A. Ochmanek and others, To Find, and Not to Yield: How Advances in Information and Firepower Can Transform Theater Warfare (Santa Monica, Calif.: RAND, 1998), pp. 1–40, 83–100.
• See, for example, Scott Savitz and others, U.S. Navy Employment Options for Unmanned Surface Vehicles (USVs) (Santa Monica, Calif.: RAND, 2013), pp. 7, 18, 33.
• Robert W. Button and others, A Survey of Missions for Unmanned Undersea Vehicles (Santa Monica, Calif.: RAND, 2009), p. 57.
• Kyle Mizokami, “Colombian Drug Smugglers Built This Stealthy, Special Forces–Inspired Boat,” Popular Mechanics, June 13, 2017.
• David Kushner, “Drug-Sub Culture,” New York Times Magazine, April 23, 2009
• Captain Wayne P. Hughes Jr. (ret.), Fleet Tactics and Coastal Combat, 2nd ed. (Annapolis, Md.: Naval Institute Press, 2000), p. 153.
• Caitlin Talmadge, “Closing Time: Assessing the Iranian Threat to the Strait of Hormuz,” International Security 33, no. 1 (Summer 2008), pp. 82–117. An alternative analysis argued that one month might be an exaggeration, for simple mine technology, but my main concern here is with more advanced mines. See William D. O’Neil, “Correspondence: Costs and Difficulties of Blocking the Strait of Hormuz,” International Security 33, no. 3 (Winter 2008–09), pp. 190–95.
• Button and others, A Survey of Missions for Unmanned Undersea Vehicles, pp. 51–52.
• Ibid., pp. 21, 63.
• See “Approaches to Port of Riga,” GPS Nautical Charts , Bist LLC, 2014 (http://fishing-app.gpsnauticalcharts.com/i-boating-fishing-web-app/fishing-marine-charts-navigation.html#9/57.0200/24.0100).
• Kyle Mizokami, “The U.S. Navy Is Getting a More Lethal Torpedo,” Popular Mechanics, December 27, 2016.

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The profound impact of Artificial Intelligence on society – Exploring the far-reaching implications of AI technology

Artificial intelligence (AI) has revolutionized the way we live and work, and its influence on society continues to grow. This essay explores the impact of AI on various aspects of our lives, including economy, employment, healthcare, and even creativity.

One of the most significant impacts of AI is on the economy. AI-powered systems have the potential to streamline and automate various processes, increasing efficiency and productivity. This can lead to economic growth and increased competitiveness in the global market. However, it also raises concerns about job displacement and income inequality, as AI technologies replace certain job roles.

In the realm of healthcare, AI has already made its mark. From early detection of diseases to personalized treatment plans, AI algorithms have become invaluable in improving patient outcomes. With the ability to analyze vast amounts of medical data, AI systems can identify patterns and make predictions that human doctors may miss. Nevertheless, ethical considerations regarding patient privacy and data security need to be addressed.

Furthermore, AI’s impact on creativity is an area of ongoing exploration. While AI technologies can generate artwork, music, and literature, the question of whether they can truly replicate human creativity remains. Some argue that AI can enhance human creativity by providing new tools and inspiration, while others fear that it may diminish the value of genuine human artistic expression.

In conclusion, the impact of artificial intelligence on society is multifaceted. While it brings economic advancements and improvements in healthcare, it also presents challenges and ethical dilemmas. As AI continues to evolve, it is crucial to strike a balance that maximizes its benefits while minimizing its potential drawbacks.

The Definition of Artificial Intelligence

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. It involves the development of computer systems that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and problem-solving.

AI has a profound impact on society, revolutionizing various industries and sectors. Its disruptive nature has led to significant advancements in the way businesses operate, healthcare is delivered, and everyday tasks are performed. AI technologies have the potential to automate repetitive tasks, analyze vast amounts of data with speed and accuracy, and enhance the efficiency and effectiveness of various processes.

Furthermore, AI has the potential to transform the workforce, leading to changes in the job market. While some fear that AI will replace human workers and result in unemployment, others argue that it will create new job opportunities and improve overall productivity. The societal impact of AI is complex and multifaceted, necessitating careful consideration and management.

In summary , artificial intelligence is the development of computer systems that can mimic human intelligence and perform tasks that traditionally require human thinking. Its impact on society is vast, affecting industries, job markets, and everyday life. Understanding the definition and implications of AI is crucial as we navigate the ever-evolving technological landscape.

The History of Artificial Intelligence

The impact of artificial intelligence on society is a topic that has gained increasing attention in recent years. As technology continues to advance at a rapid pace, the capabilities of artificial intelligence are expanding as well. But how did we get to this point? Let’s take a brief look at the history of artificial intelligence.

The concept of artificial intelligence dates back to ancient times, with the development of mechanical devices that were capable of performing simple calculations. However, it wasn’t until the mid-20th century that the field of AI began to take shape.

In 1956, a group of researchers organized the famous Dartmouth Conference, where the field of AI was officially born. This conference brought together leading experts from various disciplines to explore the possibilities of creating “machines that can think.”

During the following decades, AI research progressed with the development of first-generation computers and the introduction of programming languages. In the 1960s, researchers focused on creating natural language processing systems, while in the 1970s, expert systems became popular.

However, in the 1980s, AI faced a major setback known as the “AI winter.” Funding for AI research significantly declined due to the lack of significant breakthroughs. The field faced criticism and skepticism, and it seemed that the promise of AI might never be realized.

But in the 1990s, AI began to emerge from its winter. The introduction of powerful computers and the availability of massive amounts of data fueled the development of machine learning algorithms. This led to significant advancements in areas such as computer vision, speech recognition, and natural language processing.

Over the past few decades, AI has continued to evolve and impact various aspects of society. From virtual assistants like Siri and Alexa to autonomous vehicles and recommendation systems, artificial intelligence is becoming increasingly integrated into our daily lives.

As we move forward, the impact of artificial intelligence on society is only expected to grow. With ongoing advancements in AI technology, we can expect to see even more significant changes in fields such as healthcare, finance, transportation, and more.

In conclusion, the history of artificial intelligence is one of perseverance and innovation. From its humble beginnings to its current state, AI has come a long way. It has evolved from simple mechanical devices to complex algorithms that can learn and make decisions. The impact of artificial intelligence on society will continue to shape our future, and it is essential to consider both the positive and negative implications as we navigate this technological revolution.

The Advantages of Artificial Intelligence

Artificial intelligence (AI) is a rapidly developing technology that is having a significant impact on society. It has the potential to revolutionize various aspects of our lives, bringing about many advantages that can benefit individuals and communities alike.

1. Increased Efficiency

One of the major advantages of AI is its ability to automate tasks and processes, leading to increased efficiency. AI systems can analyze large amounts of data and perform complex calculations at a speed much faster than humans. This can help businesses optimize their operations, reduce costs, and improve productivity.

2. Enhanced Accuracy

AI technologies can also improve accuracy and precision in various domains. Machine learning algorithms can learn from large datasets and make predictions or decisions with a high level of accuracy. This can be particularly beneficial in fields such as healthcare, where AI can assist doctors in diagnosing diseases, detecting patterns in medical images, and recommending personalized treatments.

Additionally, AI-powered systems can minimize human error in areas where precision is crucial, such as manufacturing and transportation. By automating repetitive tasks and monitoring processes in real-time, AI can help avoid costly mistakes and improve overall quality.

Overall, the advantages of artificial intelligence are numerous and diverse. From increased efficiency to enhanced accuracy, AI has the potential to transform various industries and improve the quality of life for individuals and societies as a whole. It is crucial, however, to continue exploring the ethical implications of AI and ensure that its development is guided by principles that prioritize the well-being and safety of humanity.

The Disadvantages of Artificial Intelligence

While the impact of artificial intelligence on society has been largely positive, it is important to also consider its disadvantages.

1. Job Displacement

One of the biggest concerns regarding artificial intelligence is the potential for job displacement. As machines become more intelligent and capable of performing complex tasks, there is a growing fear that many jobs will become obsolete. This can lead to unemployment and economic instability, as individuals struggle to find work in a society increasingly dominated by artificial intelligence.

2. Ethical Concerns

Another disadvantage of artificial intelligence is the ethical concerns it raises. As artificial intelligence systems become more advanced, there is a need for clear guidelines and regulations to ensure that they are used responsibly. Issues such as privacy, data protection, and algorithmic bias need to be addressed to prevent misuse or unintended consequences.

In conclusion, while artificial intelligence has had a positive impact on society, there are also disadvantages that need to be considered. Job displacement and ethical concerns are just a few of the challenges that need to be addressed as we continue to advance in the field of artificial intelligence.

The Ethical Concerns of Artificial Intelligence

As artificial intelligence continues to impact society in numerous ways, it is important to address the ethical concerns that arise from its use. As AI becomes more commonplace in various industries, including healthcare, finance, and transportation, the potential for unintended consequences and ethical dilemmas increases.

One of the primary ethical concerns of artificial intelligence is the issue of privacy. With the advancements in AI technology, there is a growing ability for machines to collect and analyze vast amounts of personal data. This raises questions about how this data is used, who has access to it, and whether individuals have a right to control and protect their own information.

Another ethical concern is the potential for AI to perpetuate and amplify existing biases and discrimination. AI algorithms are trained on existing data, which can reflect societal biases and prejudices. If these biases are not identified and addressed, AI systems can inadvertently perpetuate unfair practices and discrimination, leading to negative impacts on marginalized communities.

Additionally, the use of AI in decision-making processes raises concerns about accountability and transparency. As AI systems make more complex decisions that affect individuals’ lives, it becomes crucial to understand how these decisions are made. Lack of transparency and accountability can result in a loss of trust in AI systems, especially if they make decisions that have significant consequences.

Furthermore, there is the concern of the impact of AI on employment and the workforce. As AI technology advances, there is the potential for job displacement and the loss of livelihoods. This raises questions about the responsibility of society to provide support and retraining for individuals who are affected by the automation of tasks previously carried out by humans.

Overall, as artificial intelligence continues to evolve and become more integrated into society, it is crucial to actively address the ethical concerns that arise. This involves establishing clear guidelines and regulations to safeguard privacy, address biases, ensure transparency, and mitigate the impact on employment. By addressing these concerns proactively, society can harness the benefits of AI while minimizing its negative impacts.

The Impact of Artificial Intelligence on Jobs

The advancement of artificial intelligence (AI) technology is having a profound impact on society as a whole. One area that is particularly affected by this technological revolution is the job market. The introduction of AI into various industries is changing the way we work and the types of jobs that are available. It is important to understand the implications of this impact on jobs and how it will shape the future of work.

The Rise of Automation

One of the main ways AI impacts jobs is through automation. AI algorithms and machines are increasingly replacing human workers in repetitive and routine tasks. Jobs that involve tasks that can be easily automated, such as data entry or assembly line work, are being taken over by AI-powered technology. This shift towards automation has the potential to lead to job displacement and unemployment for many individuals.

New Opportunities and Skill Requirements

While AI may be replacing certain jobs, it is also creating new opportunities. As industries become more automated, there is a growing demand for workers who are skilled in managing and developing AI technology. Jobs that require expertise in AI programming and data analysis are becoming increasingly important. This means that individuals who possess these skills will have an advantage in the job market, while those without them may struggle to find employment.

Furthermore, AI technology has the potential to transform existing jobs rather than eliminate them entirely. As AI systems become more sophisticated, they can assist human workers in performing tasks more efficiently and accurately. This collaboration between humans and machines can lead to increased productivity and job growth in certain industries.

The Need for Adaptation and Lifelong Learning

The impact of AI on jobs highlights the importance of adaptation and lifelong learning. As technology continues to evolve, workers must be willing to learn new skills and adapt to changing job requirements. The ability to continuously update one’s skills will be crucial in order to remain relevant in the job market. This necessitates a shift towards lifelong learning and a willingness to embrace new technologies.

In conclusion, the impact of artificial intelligence on jobs is significant and multifaceted. While AI technology has the potential to automate certain tasks and lead to job displacement, it also creates new opportunities and changes the nature of existing jobs. The key to navigating this changing job market is adaptation, lifelong learning, and acquiring new skills in AI-related fields. By understanding and adapting to the impact of AI on jobs, society can ensure that the benefits of this technology are maximized while minimizing negative consequences.

The Impact of Artificial Intelligence on Education

Artificial intelligence (AI) is rapidly transforming various aspects of society, and one area where its impact is particularly noteworthy is education. In this essay, we will explore how AI is revolutionizing the educational landscape and the implications it has for both teachers and students.

AI has the potential to greatly enhance the learning experience for students. With intelligent algorithms and personalized learning platforms, students can receive customized instruction tailored to their individual needs and learning styles. This can help to bridge gaps in understanding, improve retention, and ultimately lead to better academic outcomes.

Moreover, AI can serve as a valuable tool for teachers. By automating administrative tasks, such as grading and data analysis, teachers can save time and focus on what they do best: teaching. AI can also provide valuable insights into student performance and progress, allowing teachers to identify areas where additional support may be needed.

However, it is important to recognize that AI is not a substitute for human teachers. While AI can provide personalized instruction and automate certain tasks, it lacks the emotional intelligence and interpersonal skills that are essential for effective teaching. Teachers play a critical role in creating a supportive and nurturing learning environment, and their expertise cannot be replaced by technology.

Another concern is the potential bias and ethical implications associated with AI in education. With algorithms determining the content and delivery of educational materials, there is a risk of reinforcing existing inequalities and perpetuating discriminatory practices. It is crucial to ensure that AI systems are designed and implemented in an ethical and inclusive manner, taking into account issues of fairness and equity.

In conclusion, the impact of artificial intelligence on education is profound. It has the potential to revolutionize the way students learn and teachers teach. However, it is crucial to approach AI in education with caution, being mindful of the limitations and ethical considerations. By harnessing the power of AI while preserving the irreplaceable role of human teachers, we can create a future of education that is truly transformative.

The Impact of Artificial Intelligence on Healthcare

Artificial intelligence (AI) is revolutionizing the healthcare industry, and its impact on society cannot be overstated. Through the use of advanced algorithms and machine learning, AI is transforming various aspects of healthcare, from diagnosis and treatment to drug discovery and patient care.

One of the key areas where AI is making a significant impact is in diagnosing diseases. With the ability to analyze massive amounts of medical data, AI algorithms can now detect patterns and identify potential diseases in patients more accurately and efficiently than ever before. This can lead to early detection and intervention, ultimately saving lives.

AI is also streamlining the drug discovery process, which traditionally has been a time-consuming and costly endeavor. By analyzing vast amounts of data and simulating molecular structures, AI can help researchers identify potential drug candidates more quickly and accurately. This has the potential to accelerate the development of new treatments and improve patient outcomes.

Furthermore, AI is transforming patient care through personalized medicine. By analyzing an individual’s genetic and medical data, AI algorithms can provide personalized treatment plans tailored to the specific needs of each patient. This can lead to more effective treatments, reduced side effects, and improved overall patient satisfaction.

In addition to diagnosis and treatment, AI is also improving healthcare delivery and efficiency. AI-powered chatbots and virtual assistants can now provide patients with personalized medical advice and answer their questions 24/7. This reduces the burden on healthcare providers and allows for more accessible and convenient healthcare services.

However, as with any new technology, there are also challenges and concerns surrounding the use of AI in healthcare. Issues such as data privacy, ethical considerations, and bias in algorithms need to be addressed to ensure that AI is used responsibly and for the benefit of all patients.

In conclusion, the impact of artificial intelligence on healthcare is immense. With advancements in AI, the healthcare industry is poised to revolutionize patient care, diagnosis, and treatment. However, it is crucial to address the ethical and privacy concerns associated with AI to ensure that it is used responsibly and for the greater good of society.

The Impact of Artificial Intelligence on Transportation

Artificial intelligence (AI) has had a significant impact on society in many different areas, and one of the fields that has benefited greatly from AI technology is transportation. With advances in AI, transportation systems have become more efficient, safer, and more environmentally friendly.

Improved Safety

One of the key impacts of AI on transportation is the improved safety of both passengers and drivers. AI technology has enabled the development of autonomous vehicles, which can operate without human intervention. These vehicles use AI algorithms and sensors to navigate roads, avoiding accidents and minimizing collisions. By removing the human element from driving, the risk of human error and accidents caused by fatigue, distraction, or impaired judgment can be significantly reduced.

Efficient Traffic Management

AI has also revolutionized traffic management systems, leading to more efficient transportation networks. Intelligent traffic lights, for example, can use AI algorithms to adjust signal timings based on real-time traffic conditions, optimizing traffic flow and reducing congestion. AI-powered algorithms can analyze large amounts of data from various sources, such as traffic cameras and sensors, to provide accurate predictions and recommendations for traffic management and planning.

Enhanced Logistics and Delivery

AI has significantly impacted the logistics and delivery industry. AI-powered software can optimize route planning for delivery vehicles, taking into account factors such as traffic conditions, weather, and delivery time windows. This improves efficiency and reduces costs by minimizing fuel consumption and maximizing the number of deliveries per trip. Additionally, AI can also assist in package sorting and tracking, enhancing the overall speed and accuracy of the delivery process.

The impact of AI on transportation is continuously evolving, with ongoing research and development leading to even more advanced applications. As AI technology continues to improve, we can expect transportation systems to become even safer, more efficient, and more sustainable.

The Impact of Artificial Intelligence on Communication

Artificial intelligence has had a profound impact on society, affecting various aspects of our lives. One area where its influence can be seen is in communication. The advancements in artificial intelligence have revolutionized the way we communicate with each other.

One of the main impacts of artificial intelligence on communication is the development of chatbots. These computer programs are designed to simulate human conversation and interact with users through messaging systems. Chatbots have become increasingly popular in customer service, providing quick and automated responses to customer inquiries. They are available 24/7, ensuring constant support and improving customer satisfaction.

Moreover, artificial intelligence has contributed to the improvement of language translation. Translation tools powered by AI technology have made it easier for people to communicate across languages and cultures. These tools can instantly translate text and speech, enabling effective communication in real-time. They have bridged the language barrier and facilitated global collaboration and understanding.

Another impact of artificial intelligence on communication is the emergence of voice assistants. These virtual assistants, such as Siri and Alexa, use natural language processing and machine learning algorithms to understand and respond to user commands. Voice assistants have become integral parts of our daily lives, helping us perform various tasks, from setting reminders to controlling smart home devices. They have transformed the way we interact with technology and simplified communication with devices.

Artificial intelligence has also played a role in enhancing communication through personalized recommendations. Many online platforms, such as social media and streaming services, utilize AI algorithms to analyze user preferences and provide personalized content suggestions. This has improved user engagement and facilitated communication by connecting users with relevant information and like-minded individuals.

In conclusion, artificial intelligence has had a significant impact on communication. From chatbots and language translation to voice assistants and personalized recommendations, AI technology has revolutionized the way we interact and communicate with each other. It has made communication faster, more efficient, and more accessible, bringing people closer together in an increasingly interconnected world.

The Impact of Artificial Intelligence on Privacy

Artificial intelligence (AI) has had a profound impact on various aspects of our society, and one area that is greatly affected is privacy. With the advancements in AI technology, there are growing concerns about how it can impact our privacy rights.

AI-powered systems have the ability to collect and analyze vast amounts of personal data, ranging from social media activity to online transactions. This presents significant challenges when it comes to protecting our privacy. For instance, AI algorithms can mine and analyze our personal data to generate targeted advertisements, which can result in intrusion into our personal lives.

Additionally, AI systems can be used to monitor and track individuals’ online activities, which raises concerns about surveillance and the erosion of privacy. With AI’s ability to process and interpret large volumes of data, it becomes easier for organizations and governments to gather information about individuals without their knowledge or consent.

Furthermore, AI algorithms can make predictions about individuals’ behaviors and preferences based on their data. While this can be beneficial in some cases, such as providing tailored recommendations, it also raises concerns about the potential misuse of this information. For example, insurance companies could use AI algorithms to assess an individual’s health risks based on their online activity, resulting in potential discrimination or exclusion.

It is crucial to strike a balance between the benefits of AI technology and protecting individuals’ right to privacy. Steps must be taken to ensure that AI systems are designed and implemented in a way that respects and safeguards privacy. This can include implementing strict regulations and guidelines for data collection, storage, and usage.

In conclusion, the impact of artificial intelligence on privacy cannot be ignored. As AI continues to advance, it is essential to address the potential risks and challenges it poses to privacy rights. By taking proactive measures and promoting ethical practices, we can harness the benefits of AI while ensuring that individuals’ privacy is respected and protected.

The Impact of Artificial Intelligence on Security

Artificial intelligence (AI) has had a profound impact on society, and one area where its influence is particularly noticeable is in the field of security. The development and implementation of AI technology have revolutionized the way we approach and manage security threats.

AI-powered security systems have proven to be highly effective in detecting and preventing various types of threats, such as cyber attacks, terrorism, and physical breaches. These systems are capable of analyzing vast amounts of data in real-time, identifying patterns, and recognizing anomalies that may indicate a security risk.

One major advantage of AI in security is its ability to continuously adapt and learn. AI algorithms can quickly analyze new data and update their knowledge base, improving their ability to detect and respond to emerging threats. This dynamic nature allows AI-powered security systems to stay ahead of potential attackers and respond to evolving security challenges.

Furthermore, AI can enhance the efficiency and accuracy of security operations. By automating certain tasks, such as video surveillance monitoring and threat analysis, AI technology can significantly reduce the workload for human security personnel. This frees up resources and enables security teams to focus on more critical tasks, such as responding to incidents and developing proactive security strategies.

However, the increasing reliance on AI in security also raises concerns. The use of AI technology can potentially lead to privacy breaches and unethical surveillance practices. It is crucial to strike a balance between utilizing AI for security purposes and respecting individual privacy rights.

In conclusion, the impact of artificial intelligence on security has been significant. AI-powered systems have revolutionized the way we detect and prevent security threats, enhancing efficiency and accuracy in security operations. However, ethical concerns need to be addressed to ensure that AI is used responsibly and in a way that respects individual rights and privacy.

The Impact of Artificial Intelligence on Economy

Artificial intelligence (AI) is revolutionizing the economy in various ways. Its impact is prevalent across different sectors, leading to both opportunities and challenges.

One of the key benefits of AI in the economy is increased productivity. AI-powered systems and algorithms can perform tasks at a much faster pace and with a higher level of accuracy compared to humans. This efficiency can lead to significant cost savings for businesses and result in increased output and profits.

Moreover, AI has the potential to create new job opportunities. While some jobs may be replaced by automation, AI also leads to the creation of new roles that require specialized skills in managing and maintaining AI systems. This can contribute to economic growth and provide employment opportunities for individuals with the necessary technical expertise.

The impact of AI on the economy is not limited to individual businesses or sectors. It has the potential to transform entire industries. For example, AI-powered technologies can optimize supply chain operations, enhance customer experience, and improve decision-making processes. These advancements can lead to increased competitiveness, improved efficiency, and overall economic growth.

However, the widespread implementation of AI also brings challenges. The displacement of jobs due to automation can result in unemployment and income inequality. It is crucial for policymakers to address these issues and ensure that the benefits of AI are distributed equitably across society.

Additionally, the ethical implications of AI in the economy must be considered. As AI systems continue to advance, it raises questions about privacy, data security, and algorithmic bias. Safeguards and regulations need to be in place to protect individuals’ rights and prevent any potential harm caused by AI applications.

In conclusion, the impact of artificial intelligence on the economy is significant. It offers opportunities for increased productivity, job creation, and industry transformation. However, it also poses challenges such as job displacement and ethical concerns. To fully harness the potential of AI in the economy, policymakers and stakeholders must work together to address these challenges and ensure a balanced and inclusive approach to its implementation.

The Impact of Artificial Intelligence on Entertainment

Artificial intelligence is revolutionizing the entertainment industry, transforming the way we consume and experience various forms of media. With its ability to analyze massive amounts of data, AI has the potential to enhance entertainment in numerous ways.

One area where AI is making a significant impact is in content creation. AI algorithms can generate music, art, and even scripts for movies and TV shows. By analyzing patterns and trends in existing content, AI can create new and original pieces that appeal to different audiences. This not only increases the diversity of entertainment options but also reduces the time and effort required for human creators.

AI also plays a crucial role in enhancing the user experience in the entertainment industry. For example, AI-powered recommendation engines can suggest relevant movies, TV shows, or songs based on individual preferences and viewing habits. This personalized approach ensures that users discover content that aligns with their interests, leading to a more enjoyable and engaging entertainment experience.

In the gaming industry, AI is transforming the way games are developed and played. AI algorithms can create lifelike characters and virtual worlds, providing players with immersive and realistic experiences. Additionally, AI-powered game assistants can adapt to the player’s skill level and offer personalized guidance, making games more accessible and enjoyable for players of all abilities.

Furthermore, AI is revolutionizing the way we consume live events, such as sports or concerts. AI-powered cameras and sensors can capture and analyze data in real-time, providing enhanced viewing experiences for spectators. This includes features like instant replays, personalized camera angles, and in-depth statistics. AI can also generate virtual crowds or even simulate the experience of attending a live event, bringing the excitement of the event to a global audience.

The impact of artificial intelligence on the entertainment industry is undeniable. It is transforming content creation, enhancing the user experience, and revolutionizing the way we consume various forms of media. As AI continues to advance, we can expect even more innovative and immersive entertainment experiences that cater to individual preferences and push the boundaries of creativity.

The Impact of Artificial Intelligence on Human Interaction

In today’s modern world, the rise of artificial intelligence (AI) has had a profound impact on many aspects of society, including human interaction. AI technology has revolutionized the way we communicate and interact with one another, both online and offline.

One of the most noticeable impacts of AI on human interaction is in the realm of communication. AI-powered chatbots and virtual assistants have become increasingly common, allowing people to interact with machines in a more natural and intuitive way. Whether it’s using voice commands to control smart home devices or chatting with a virtual assistant to get information, AI has made it easier to communicate with technology.

AI has also had a significant impact on social media and online communication platforms. Social media algorithms use AI to analyze user data and tailor content to individual preferences, which can shape the way we interact with each other online. This can lead to both positive and negative effects, as AI algorithms may reinforce existing beliefs and create echo chambers, but they can also expose us to new ideas and perspectives.

Furthermore, AI technology has the potential to enhance human interaction by augmenting our capabilities. For example, AI-powered translation tools can break down language barriers and facilitate communication between people who speak different languages. This can foster cross-cultural understanding and enable collaboration on a global scale.

On the other hand, there are concerns about the potential negative impact of AI on human interaction. Some argue that the increasing reliance on AI technology for communication could lead to a decline in human social skills. As people become more accustomed to interacting with machines, they may struggle to engage in authentic face-to-face interactions.

Despite these concerns, it is clear that AI has had a profound impact on human interaction. From enhancing communication to breaking down language barriers, AI technology has transformed the way we interact with one another. It is crucial to continue monitoring and studying the impact of AI on human interaction to ensure we strike a balance between technological advancement and preserving our social connections.

The Role of Artificial Intelligence in Scientific Research

Artificial intelligence (AI) has had a significant impact on society in various fields, and one area where it has shown great promise is scientific research. The use of AI in scientific research has revolutionized the way experiments are conducted, data is analyzed, and conclusions are drawn.

Improving Experimental Design and Data Collection

One of the key contributions of AI in scientific research is its ability to improve experimental design and data collection. By utilizing machine learning algorithms, AI systems can analyze massive amounts of data and identify patterns, allowing researchers to optimize their experimental approaches and make more informed decisions. This not only saves time and resources but also increases the accuracy and reliability of scientific findings.

Enhancing Data Analysis and Interpretation

Another crucial role of AI in scientific research is its ability to enhance data analysis and interpretation. Traditional data analysis methods can be time-consuming and subjective, leading to potential biases. However, AI systems can process vast amounts of data quickly and objectively, revealing hidden relationships, trends, and insights that may be missed by human researchers. This enables scientists to extract meaningful information from complex datasets, leading to more accurate and comprehensive conclusions.

While AI has significant potential in scientific research, it also presents challenges and ethical considerations that need to be addressed. Privacy and security concerns, biases in AI algorithms, ethical implications of AI decision-making, and the impact on human researchers’ roles are some of the critical issues that require scrutiny.

In conclusion, the role of artificial intelligence in scientific research is undeniable. AI has the potential to revolutionize how experiments are designed, data is analyzed, and conclusions are drawn. By improving experimental design and data collection, enhancing data analysis and interpretation, and accelerating scientific discovery, AI can significantly contribute to the advancement of scientific knowledge and its impact on society as a whole.

The Role of Artificial Intelligence in Space Exploration

Artificial intelligence (AI) has had a significant impact on various fields and industries, and space exploration is no exception. With its ability to analyze vast amounts of data and make decisions quickly, AI has revolutionized the way we explore space and gather information about the universe.

One of the primary roles of artificial intelligence in space exploration is in the analysis of data collected by space probes and telescopes. These devices capture enormous amounts of data that can often be overwhelming for human scientists to process. AI algorithms can sift through this data, identifying patterns, and extracting valuable insights that humans may not have noticed.

Additionally, AI plays a crucial role in autonomous navigation and spacecraft control. Spacecraft can be sent to explore distant planets and moons in our solar system, and AI-powered systems can ensure their safe and efficient navigation through unknown terrain. AI algorithms can analyze data from onboard sensors and make real-time decisions to avoid obstacles and hazards.

Benefits of AI in space exploration

• Efficiency: AI systems can process vast amounts of data much faster than humans, allowing for quicker analysis and decision-making.
• Exploration of inhospitable environments: AI-powered robots can be sent to explore extreme environments, such as the surface of Mars or the icy moons of Jupiter, where it would be challenging for humans to survive.
• Cost reduction: By using AI to automate certain tasks, space exploration missions can become more cost-effective and efficient.

The impact of artificial intelligence on space exploration is still in its early stages, but its potential is vast. As AI technology continues to advance, we can expect to see even more significant contributions to our understanding of the universe and our ability to explore it.

The Role of Artificial Intelligence in Environmental Conservation

Artificial intelligence (AI) has the potential to revolutionize various aspects of society, and environmental conservation is no exception. With the growing concern about climate change and the need to preserve the planet’s resources, AI can play a crucial role in helping us address these challenges.

Monitoring and Predicting Environmental Changes

One of the key benefits of AI in environmental conservation is its ability to monitor and predict environmental changes. Through the use of sensors and data analysis, AI systems can gather and analyze vast amounts of information about the environment, including temperature, air quality, and water levels.

This data can then be used to identify patterns and trends, allowing scientists to make predictions about future changes. For example, AI can help predict the spread of wildfires or the impact of deforestation in certain areas. By understanding these threats in advance, we can take proactive measures to protect our natural resources.

Optimizing Resource Management

Another important role of AI in environmental conservation is optimizing resource management. By using AI algorithms, we can efficiently allocate resources such as energy, water, and waste management.

AI can analyze data from various sources, such as smart meters and sensors, to understand patterns of resource usage. This information can then be used to develop strategies for more sustainable resource management, reducing waste and improving efficiency.

For example, AI can help optimize energy consumption in buildings by analyzing data from smart thermostats and occupancy sensors. It can identify usage patterns and make adjustments to reduce energy waste, saving both money and environmental resources.

Supporting Conservation Efforts

AI can also support conservation efforts through various applications. One example is the use of AI-powered drones and satellite imagery to monitor and protect endangered species.

By analyzing images and data collected by these technologies, AI algorithms can identify and track animals, detect illegal activities such as poaching, and even help with habitat restoration. This technology can greatly enhance the effectiveness and efficiency of conservation efforts, allowing us to better protect our biodiversity.

In conclusion, artificial intelligence has a significant role to play in environmental conservation. From monitoring and predicting environmental changes to optimizing resource management and supporting conservation efforts, AI can provide valuable insights and help us make more informed decisions. By harnessing the power of AI, we can work towards a more sustainable and environmentally conscious society.

The Role of Artificial Intelligence in Manufacturing

Artificial intelligence (AI) has had a profound impact on society in various fields, and manufacturing is no exception. In this essay, we will explore the role of AI in manufacturing and how it has revolutionized the industry.

AI has transformed the manufacturing process by introducing automation and machine learning techniques. With AI, machines can perform tasks that were previously done by humans, leading to increased efficiency and productivity. This has allowed manufacturers to streamline their operations and produce goods at a faster rate.

One of the key benefits of AI in manufacturing is its ability to analyze large amounts of data. Through machine learning algorithms, AI systems can collect and process data from various sources, such as sensors and machines, to identify patterns and make informed decisions. This allows manufacturers to optimize their production processes and minimize errors.

Furthermore, AI can improve product quality and reduce defects. By analyzing data in real-time, AI systems can detect anomalies and deviations from the norm, allowing manufacturers to identify and address issues before they escalate. This not only saves time and costs but also ensures that consumers receive high-quality products.

Additionally, AI has enabled the development of predictive maintenance systems. By analyzing data from machines and equipment, AI can anticipate and prevent failures before they occur. This proactive approach minimizes downtime, reduces maintenance costs, and extends the lifespan of machinery.

Overall, the role of AI in manufacturing is transformative. It empowers manufacturers to optimize their processes, improve product quality, and reduce costs. However, it is important to note that AI is not a replacement for humans in the manufacturing industry. Instead, it complements human skills and expertise, allowing workers to focus on more complex tasks while AI handles repetitive and mundane tasks.

In conclusion, artificial intelligence has had a significant impact on the manufacturing industry. It has revolutionized processes, improved product quality, and increased productivity. As AI continues to advance, we can expect even more transformative changes in the manufacturing sector.

The Role of Artificial Intelligence in Agriculture

Artificial intelligence has had a profound impact on society in various fields, and agriculture is no exception. With the advancements in technology, AI has the potential to revolutionize the agricultural industry, making it more efficient, sustainable, and productive.

One of the key areas where AI can play a significant role in agriculture is in crop management. AI-powered systems can analyze vast amounts of data, such as weather patterns, soil conditions, and crop health, to provide farmers with valuable insights. This allows farmers to make more informed decisions on irrigation, fertilization, and pest control, leading to optimal crop yields and reduced resource waste.

Moreover, AI can also aid in the early detection and prevention of crop diseases. By using machine learning algorithms, AI systems can identify patterns and anomalies in plant health, indicating the presence of diseases or pests. This enables farmers to take timely action, prevent the spread of diseases, and minimize crop losses.

Another area where AI can contribute to agriculture is in the realm of precision farming. By combining AI with other technologies like drones and sensors, farmers can gather precise and real-time data about their crops and fields. This data can then be used to create detailed maps, monitor crop growth, and optimize resource allocation. Whether it’s optimizing water usage or determining the ideal time for harvesting, AI can help farmers make data-driven decisions that maximize productivity while minimizing environmental impact.

Furthermore, AI can enhance livestock management. With AI-powered systems, farmers can monitor the health and behavior of their livestock, detect diseases or anomalies, and provide personalized care. This not only improves animal welfare but also increases the efficiency of livestock production.

In conclusion, artificial intelligence has a crucial role to play in the agricultural sector. From crop management to livestock monitoring, AI can bring numerous benefits to farmers, leading to increased productivity, sustainability, and overall growth. As AI continues to advance, we can expect further innovations and improvements in the integration of AI in agriculture, shaping the future of food production.

The Role of Artificial Intelligence in Finance

Artificial intelligence (AI) has had a significant impact on society, revolutionizing various industries, and finance is no exception. In this essay, we will explore the role of AI in the financial sector and its implications.

The use of AI has transformed numerous aspects of finance, from trading and investment to risk management and fraud detection. One of the key benefits of AI in finance is its ability to process vast amounts of data in real-time. This enables more accurate predictions and informed decision-making, giving financial institutions a competitive edge.

AI-powered algorithms have become vital tools for traders and investors. These algorithms analyze market trends, historical data, and other factors to identify patterns and make investment recommendations. By leveraging AI, financial professionals can make more informed decisions and optimize their portfolios.

Furthermore, AI plays a crucial role in risk management. Traditional risk models often fall short in assessing complex and evolving risks, making it challenging to mitigate them effectively. AI, with its machine learning capabilities, can enhance risk assessment by analyzing a wide range of variables and identifying potential threats. This helps financial institutions proactively manage risks and minimize losses.

Another area where AI has made significant strides in finance is fraud detection. With the increasing sophistication of fraudulent activities, traditional rule-based systems struggle to keep up. AI, on the other hand, can detect anomalies and unusual patterns by leveraging machine learning algorithms that constantly learn and adapt. This enables faster and more accurate detection of fraudulent transactions, protecting both financial institutions and their customers.

In conclusion, AI has had a profound impact on the finance industry and has revolutionized various aspects of it. The ability to process large amounts of data, make informed decisions, and detect risks and frauds more effectively has made AI an invaluable tool. As technology continues to advance, we can expect AI to play an even greater role in shaping the future of finance.

The Role of Artificial Intelligence in Customer Service

Artificial intelligence has had a profound impact on various industries, and one area where its influence is increasingly being felt is customer service. AI technology is transforming how businesses interact with their customers, providing enhanced communication and support.

One of the main benefits of AI in customer service is its ability to provide instant and personalized responses to customer inquiries. Through the use of chatbots and virtual assistants, businesses can now offer round-the-clock support, ensuring that customers receive the assistance they need, no matter the time of day.

Furthermore, AI-powered customer service can analyze vast amounts of data to gain insights into customer preferences and behavior. This information can then be used to tailor interactions and improve customer experiences. By understanding customer needs better, businesses can provide more relevant and targeted solutions, leading to increased customer satisfaction and loyalty.

Another crucial role of AI in customer service is its ability to automate repetitive tasks and processes. AI-powered systems can handle routine tasks such as order tracking, appointment scheduling, and basic troubleshooting, freeing up human agents to focus on more complex issues. This results in increased efficiency and productivity, as well as faster response times.

However, it’s important to note that AI should not replace human interaction entirely. While AI can handle routine tasks effectively, there are situations where human empathy and judgment are essential. Building a balance between AI and human involvement is crucial to ensure the best possible customer service experience.

In conclusion, artificial intelligence is revolutionizing customer service by providing instant and personalized support, analyzing customer data for improved experiences, and automating repetitive tasks. While AI offers numerous benefits, it is vital to strike a balance between AI and human interaction to deliver exceptional customer service in the digital age.

The Role of Artificial Intelligence in Gaming

Gaming has been greatly impacted by the advancements in artificial intelligence (AI). AI has revolutionized the way games are created, played, and experienced by both developers and players.

One of the key roles that AI plays in gaming is in creating realistic and challenging virtual opponents. AI algorithms can be programmed to assess player actions and adjust the difficulty level accordingly. This allows for a more immersive and engaging gaming experience, as players can compete against opponents that adapt to their skills and strategies.

Moreover, AI is also used in game design to create intelligent non-player characters (NPCs) that can interact with players in a more natural and realistic manner. These NPCs can simulate human-like behavior and responses, making the game world feel more alive and dynamic.

Another important role of AI in gaming is in improving game mechanics and gameplay. AI algorithms can analyze player data and preferences to provide personalized recommendations and suggestions. This helps players discover new games, unlock achievements, and improve their overall gaming experience.

Furthermore, AI has also been used in game testing and bug detection. AI algorithms can simulate various scenarios and interactions to identify potential glitches and bugs. This improves the overall quality and stability of games before their release.

In conclusion, artificial intelligence has had a profound impact on the gaming industry. It has enhanced the realism, challenge, and overall experience of games. The role of AI in gaming is ever-evolving, and it will continue to shape the future of the gaming industry.

The Future of Artificial Intelligence

Artificial intelligence (AI) has already made a significant impact on society, and its role is only expected to grow in the future. As advancements in technology continue to push boundaries, the potential applications of AI are expanding, potentially transforming various industries and aspects of our daily lives.

One of the most prominent areas where AI is expected to make a difference is in autonomous vehicles. Self-driving cars have already become a reality, and AI is set to play a crucial role in improving their capabilities further. With AI-powered sensors and algorithms, autonomous vehicles can navigate complex road conditions, reduce traffic congestion, and even enhance road safety.

Another domain that is likely to benefit from AI is healthcare. Intelligent machines can analyze vast amounts of medical data and assist doctors in making accurate diagnoses. This can lead to faster identification of diseases, more effective treatment plans, and ultimately, better patient outcomes. AI can also aid in the development of new drugs and therapies by analyzing genetic information and identifying potential targets for treatment.

In addition to healthcare and transportation, AI has the potential to revolutionize sectors such as finance, manufacturing, and agriculture. AI algorithms can analyze market data, identify trends, and make accurate predictions, enabling financial institutions to make informed investment decisions. In manufacturing, AI-powered robots can perform repetitive tasks with precision and efficiency, improving productivity and reducing costs. AI can also optimize crop production by analyzing variables such as weather conditions, soil quality, and crop health, leading to increased yields and more sustainable farming practices.

However, with the increasing integration of AI into various aspects of society, ethical considerations become crucial. As AI becomes more advanced and autonomous, questions arise about the implications of AI decision-making processes and potential biases. It is important to ensure that AI systems are designed and regulated in a way that prioritizes fairness, transparency, and accountability.

In conclusion, the future of artificial intelligence holds immense potential for transforming society in numerous ways. From autonomous vehicles and healthcare to finance and agriculture, AI is poised to revolutionize various sectors and improve our lives. However, it is essential to address ethical concerns and ensure responsible development and deployment of AI technology to maximize its positive impact on society.

The Potential Risks of Artificial Intelligence

As the impact of artificial intelligence on society continues to grow, it is important to consider the potential risks associated with this rapidly advancing technology. While intelligence can be a powerful tool for improving society, artificial intelligence poses unique challenges and dangers that must be addressed.

Unemployment and Job Displacement

One of the major concerns surrounding artificial intelligence is the potential for widespread unemployment and job displacement. As AI technology advances, machines and algorithms are becoming increasingly capable of performing tasks that were previously done by humans. This could lead to significant job losses across various industries, particularly those that rely heavily on manual labor or repetitive tasks.

Additionally, as AI systems become more sophisticated, there is a possibility that they could replace jobs that require higher levels of skill and expertise. This could result in a significant shift in the job market and create challenges for workers who are unable to adapt to these changes.

Ethical Concerns

Another potential risk of artificial intelligence is the ethical concerns that arise from its use. AI systems are designed to make decisions and take actions based on data and algorithms, but they may not always make ethical choices. This raises questions about the impact of AI on issues such as privacy, bias, and discrimination.

For example, AI algorithms may inadvertently discriminate against certain groups of people if the data used to train them is biased. This could lead to unfair outcomes in areas such as hiring, lending, and law enforcement. It is essential to address these ethical concerns and ensure that AI systems are developed and used in a responsible and equitable manner.

In conclusion, while artificial intelligence has the potential to greatly benefit society, it is important to carefully consider and address the potential risks associated with its use. Unemployment and job displacement, as well as ethical concerns, are significant challenges that must be navigated to ensure the responsible and equitable development of AI.

The Importance of Ethical Guidelines for Artificial Intelligence

As artificial intelligence (AI) continues to advance at an unprecedented pace, its impact on society becomes increasingly profound. AI has the potential to transform various industries, improve efficiency, and enhance our overall quality of life. However, with this power comes great responsibility. It is crucial to establish ethical guidelines to ensure that AI is developed and deployed in a responsible and beneficial manner.

Ethics in AI Development

Ethics play a vital role in the development of AI technology. It is essential for developers to consider the potential impact that their creations may have on society. This involves addressing questions of privacy, security, and bias. AI systems should be designed to respect fundamental human rights and ensure that they do not discriminate against certain groups of people. By setting ethical standards, we can prevent the misuse and abuse of AI technology.

The Impact on Society

Without ethical guidelines, artificial intelligence can have unintended consequences on society. For example, if AI algorithms are biased, they may perpetuate social inequalities or reinforce stereotypes. Additionally, AI systems that invade privacy or compromise security can erode trust in technology, hindering its adoption and acceptance by the public. Therefore, by implementing ethical guidelines, we can help safeguard against these negative societal impacts.

The Risks of AI without Ethical Guidelines

Artificial intelligence has the potential to revolutionize society, but it also carries risks. Without ethical guidelines in place, AI can be misused for nefarious purposes, such as surveillance and manipulation. It is crucial to establish clear boundaries and regulations to ensure that AI is used for the benefit of humanity and not to harm individuals or society as a whole.

In conclusion , the importance of ethical guidelines for artificial intelligence cannot be overstated. These guidelines serve as a compass to steer the development and deployment of AI technology in the right direction. By considering the potential impact on society and setting ethical standards, we can harness the power of AI for the betterment of humanity and create a future that is both technologically advanced and ethically responsible.

The Need for Regulation and Governance of Artificial Intelligence

The rapid development of artificial intelligence (AI) has had a profound impact on society. With the increasing deployment of intelligent systems in various domains, it is essential to establish effective regulations and governance mechanisms to ensure that AI is used responsibly and ethically.

Safeguarding Privacy and Data Security

One of the key concerns with the growing use of AI is the potential invasion of privacy and compromise of data security. Intelligent systems are capable of analyzing vast amounts of personal data, raising concerns about the misuse and unauthorized access to sensitive information. To address this, there is a need for regulations that enforce stringent data protection measures and ensure transparency in AI algorithms and data usage.

Ethical Decision-Making and Bias Mitigation

AI systems are designed to make autonomous decisions based on data and algorithms. However, the biases embedded in these systems can result in discriminatory outcomes. Regulations must be put in place to ensure that AI systems are developed and trained in a way that mitigates bias and promotes fair and ethical decision-making. This includes diverse representation in the development of AI technologies and the establishment of clear guidelines on what is considered acceptable behavior for AI systems.

Accountability and Liability

As AI systems become increasingly autonomous, it becomes crucial to determine who should be held accountable in the event of a malfunction or failure. Clear regulations need to be established to define liability in AI-related incidents and ensure that there are mechanisms in place to address any potential harm caused by AI systems. This includes the establishment of standards for testing and certification of AI systems to ensure their reliability and safety.

In conclusion, the impact of artificial intelligence on society necessitates the establishment of regulations and governance mechanisms. By addressing concerns related to privacy, bias, and accountability, we can harness the full potential of AI while ensuring that it benefits society as a whole.

The Role of Artificial Intelligence in Shaping Society’s Future

Artificial intelligence (AI) has had a profound impact on society, and its role in shaping the future cannot be understated. As technology continues to advance at an unprecedented rate, AI is becoming increasingly integrated into various aspects of our lives, from healthcare to transportation to entertainment.

One of the key impacts of AI is its ability to automate tasks that were once performed by humans, enabling us to save time and resources. For example, AI-powered chatbots have revolutionized customer service by providing prompt and efficient responses to inquiries, reducing the need for human intervention. In the healthcare industry, AI algorithms are being developed to assist doctors in diagnosing diseases and recommending treatment options, improving both accuracy and speed.

Furthermore, AI has the potential to address complex societal challenges. For instance, in the field of environmental sustainability, AI technologies can be used to optimize energy consumption, reduce waste, and develop renewable energy sources. By analyzing large amounts of data and identifying patterns, AI can help us make more informed decisions and take proactive measures to mitigate the impact of climate change.

In addition, AI has the ability to enhance our educational systems. Intelligent tutoring systems can adapt to individual learning styles and provide personalized instruction, improving student engagement and performance. AI-powered language translation tools have also facilitated global communication, breaking down language barriers and fostering cross-cultural understanding.

However, it is important to recognize that AI is not without its challenges. There are concerns regarding privacy and security, as AI relies heavily on data collection and analysis. Ethical considerations must also be taken into account, as AI systems can perpetuate biases and discrimination if not properly designed and monitored.

In conclusion, artificial intelligence plays a significant role in shaping society’s future. Its impact can be seen in various fields, from automation to sustainability to education. While there are challenges that need to be addressed, AI has the potential to revolutionize our lives and create a more efficient and equitable society.

Questions and answers

What is the impact of artificial intelligence on society.

The impact of artificial intelligence on society is significant and far-reaching. It is transforming various sectors, including healthcare, education, finance, and transportation.

How is artificial intelligence revolutionizing healthcare?

Artificial intelligence in healthcare is revolutionizing the way diseases are diagnosed and treated. It is helping doctors in making accurate diagnoses, predicting outcomes, and assisting in surgeries.

What are the ethical concerns surrounding artificial intelligence?

There are several ethical concerns surrounding artificial intelligence, such as the potential loss of jobs, bias in algorithms, invasion of privacy, and the possibility of autonomous weapons.

How can artificial intelligence improve productivity in the workplace?

Artificial intelligence can improve productivity in the workplace by automating repetitive tasks, analyzing large amounts of data quickly and accurately, and providing personalized recommendations and insights.

What are the potential risks of artificial intelligence?

The potential risks of artificial intelligence include job displacement, widening economic inequalities, security threats, loss of human control, and the potential for AI systems to be hacked or manipulated.

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Artificial Intelligence Essay

500+ words essay on artificial intelligence.

Artificial intelligence (AI) has come into our daily lives through mobile devices and the Internet. Governments and businesses are increasingly making use of AI tools and techniques to solve business problems and improve many business processes, especially online ones. Such developments bring about new realities to social life that may not have been experienced before. This essay on Artificial Intelligence will help students to know the various advantages of using AI and how it has made our lives easier and simpler. Also, in the end, we have described the future scope of AI and the harmful effects of using it. To get a good command of essay writing, students must practise CBSE Essays on different topics.

Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. It is concerned with getting computers to do tasks that would normally require human intelligence. AI systems are basically software systems (or controllers for robots) that use techniques such as machine learning and deep learning to solve problems in particular domains without hard coding all possibilities (i.e. algorithmic steps) in software. Due to this, AI started showing promising solutions for industry and businesses as well as our daily lives.

Importance and Advantages of Artificial Intelligence

Advances in computing and digital technologies have a direct influence on our lives, businesses and social life. This has influenced our daily routines, such as using mobile devices and active involvement on social media. AI systems are the most influential digital technologies. With AI systems, businesses are able to handle large data sets and provide speedy essential input to operations. Moreover, businesses are able to adapt to constant changes and are becoming more flexible.

By introducing Artificial Intelligence systems into devices, new business processes are opting for the automated process. A new paradigm emerges as a result of such intelligent automation, which now dictates not only how businesses operate but also who does the job. Many manufacturing sites can now operate fully automated with robots and without any human workers. Artificial Intelligence now brings unheard and unexpected innovations to the business world that many organizations will need to integrate to remain competitive and move further to lead the competitors.

Artificial Intelligence shapes our lives and social interactions through technological advancement. There are many AI applications which are specifically developed for providing better services to individuals, such as mobile phones, electronic gadgets, social media platforms etc. We are delegating our activities through intelligent applications, such as personal assistants, intelligent wearable devices and other applications. AI systems that operate household apparatus help us at home with cooking or cleaning.

Future Scope of Artificial Intelligence

In the future, intelligent machines will replace or enhance human capabilities in many areas. Artificial intelligence is becoming a popular field in computer science as it has enhanced humans. Application areas of artificial intelligence are having a huge impact on various fields of life to solve complex problems in various areas such as education, engineering, business, medicine, weather forecasting etc. Many labourers’ work can be done by a single machine. But Artificial Intelligence has another aspect: it can be dangerous for us. If we become completely dependent on machines, then it can ruin our life. We will not be able to do any work by ourselves and get lazy. Another disadvantage is that it cannot give a human-like feeling. So machines should be used only where they are actually required.

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Essay on Future of Artificial Intelligence

Students are often asked to write an essay on Future of Artificial Intelligence in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Future of Artificial Intelligence

Introduction.

Artificial Intelligence (AI) is the science of making machines think and learn like humans. It’s an exciting field that’s rapidly changing our world.

Future Possibilities

In the future, AI could take over many jobs, making our lives easier. Robots could clean our houses, and AI could help doctors diagnose diseases.

Challenges Ahead

However, there are challenges. We need to make sure AI is used responsibly, and that it doesn’t take away too many jobs.

The future of AI is promising, but we need to navigate it carefully to ensure it benefits everyone.

250 Words Essay on Future of Artificial Intelligence

Artificial Intelligence (AI) has become an integral part of our daily lives, from smartphones to autonomous vehicles. The future of AI is a topic of intense debate and speculation among scientists, technologists, and futurists.

AI in Everyday Life

The future of AI holds promising advancements in everyday life. We can expect more sophisticated personal assistants, smarter home automation, and advanced healthcare systems. AI will continue to streamline our lives, making mundane tasks more efficient.

AI in Business

In business, AI will revolutionize industries by automating processes and creating new business models. Predictive analytics, customer service, and supply chain management will become more efficient and accurate. AI will also enable personalized marketing, enhancing customer experience and retention.

AI in Ethics and Society

However, the future of AI also poses ethical and societal challenges. Issues such as job displacement due to automation, privacy concerns, and the potential misuse of AI technologies need to be addressed. Ensuring fairness, transparency, and accountability in AI systems will be crucial.

In conclusion, the future of AI is a blend of immense potential and challenges. It will transform our lives and businesses, but also necessitates careful consideration of ethical and societal implications. As we move forward, it is essential to foster a global dialogue about the responsible use and governance of AI.

500 Words Essay on Future of Artificial Intelligence

Artificial Intelligence (AI) has transformed from a fringe scientific concept into a commonplace technology, permeating every aspect of our lives. As we stand on the precipice of the future, it becomes crucial to understand AI’s potential trajectory and the profound implications it might have on society.

The Evolution of AI

The future of AI is rooted in its evolution. Initially, AI was about rule-based systems, where machines were programmed to perform specific tasks. However, the advent of Machine Learning (ML) marked a significant shift. ML enabled machines to learn from data and improve their performance over time, leading to more sophisticated AI models.

The current focus is on developing General AI, machines that can perform any intellectual task that a human being can. While we are yet to achieve this, advancements in Deep Learning and Neural Networks are bringing us closer to this reality.

AI in the Future

In the future, AI is expected to become more autonomous and integrated into our daily lives. We will see AI systems that can not only understand and learn from their environment but also make complex decisions, solve problems, and even exhibit creativity.

One of the most promising areas is AI’s role in data analysis. As data continues to grow exponentially, AI will become indispensable in making sense of this information, leading to breakthroughs in fields like healthcare, climate change, and social sciences.

Implications and Challenges

However, the future of AI is not without its challenges. As AI systems become more autonomous, we must grapple with ethical issues. For instance, who is accountable if an AI system makes a mistake? How do we ensure that AI systems are fair and unbiased?

Moreover, as AI continues to automate tasks, there are concerns about job displacement. While AI will undoubtedly create new jobs, it will also render many existing jobs obsolete. Therefore, societies must prepare for this transition by investing in education and training.

The future of AI is a landscape of immense potential and challenges. As we continue to develop more sophisticated AI systems, we must also be mindful of the ethical implications and societal impacts. By doing so, we can harness the power of AI to create a future where technology serves humanity, rather than the other way around.

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Feb 09, 2022

The Role of Artificial Intelligence in the Future of Education

Gone are the days of visiting the library to photocopy a few pages from an encyclopedia for a school project. As generations of children grow up with technology at their fingertips, we live in a world where the internet is their primary source of information, education, and entertainment. A recent survey found that children in the U.S. aged between eight and 12 spend almost five hours a day looking at screens, while teenagers are clocking nearly seven hours a day of screen time – and that’s not counting the time they spend doing schoolwork. Hours spent learning from chalkboards in physical classrooms has also reduced significantly since the start of the COVID-19 pandemic, and the ensuing social restrictions and lockdowns. 1 As technology and society continue to evolve and develop, the way we learn will also continue to change, for children and adults alike.

“My hope is that by 2030, most of humanity will have ready access to health care and education through digital agents.” 2 – Gabor Melli, VP of artificial intelligence and machine learning at Medable and former senior director of engineering at Sony PlayStation

The rapid advancement of technologies such as artificial intelligence (AI), machine learning (ML), and robotics impacts all industries, including education. 3 If the education sector hopes to utilize AI’s full potential for everyone, the focus should be to continue exposing the next generation to AI early on and utilizing the technology in the classroom. Teachers are already finding that many students use AI through social media and are, therefore, open to its educational applications. 4

There’s also a great professional need for these abilities. “The U.S. Bureau of Labor Statistics sees strong growth for data science jobs skills in its prediction that the data science field will grow about 28 percent through 2026,” says Bernard Schroeder, senior contributor for Forbes . With increased technology comes increased data operations and analysis sophistication, as well as more AI. These changes will ultimately increase the demand for data scientists and other AI specialists. 5

If you’re interested in learning how AI disrupts the business world, these online short courses with GetSmarter could be a good starting point.

The role of artificial intelligence in education

The rapid advancement of technologies such as AI, ML, and robotics impacts all industries, including education.

Global Market Insights Inc. predicts that the AI education market could have a market value of $20 billion by 2027. 6 The industry growth is good news, as AI can ultimately reduce the burden on teachers across the globe.

However, some educators fear that in the future, AI technology might replace the role of the teacher altogether. Fortunately, it doesn’t look like teachers are at risk of being replaced by robots anytime soon. While AI programs can teach students literacy or math, the more complex impartation of social and emotional skills will remain in the domain of humans. 7

How artificial intelligence is currently used in education

Because AI is computer-based, it can be connected to different classrooms all over the world.

How technology is used in classrooms has changed significantly in response to COVID-19. Rather than teaching in front of a classroom full of students, lockdowns forced many educators across the globe to teach remotely, from their homes. Edtech company Promethean surveyed teachers and learned that 86 percent thought AI should be an important part of education.

Using AI in education holds many benefits for both students and teachers: 8

• Learning resources can be accessed from anywhere, at any time
• Time-consuming, tedious tasks such as record keeping or grading multiple-choice tests can be completed through AI automation
• Frequently asked questions can be answered through chatbots
• AI tutors and chatbots can be available to answer questions at any time
• Learning can be tailored and adapted to each student’s goals and abilities through personalized programs

Examples of AI in education

AI is already being applied successfully in several educational instances and improves learning and student development, as well as educators’ performance.

Let’s take a closer look at a few applications:

• Emotional well-being : A child’s emotional state affects how well they can focus, engage, and stay motivated to learn. Virtual schools can be just as effective as face-to-face learning environments when they use emotion recognition technology. Thanks to gamification, learning can also be adjusted to be fun. Furthermore, AI can determine where students struggle and help them to improve and, ultimately, excel. 9
• Spotting and filling the gaps : AI can identify the gaps in teachers’ presentations and educational material, and suggest adjustments where needed. 10
• Children working alongside AI : Nao is a humanoid robot that talks, moves, and teaches children everything from literacy to computer programming. Nao engages children in learning science, technology, engineering, and mathematics (STEM) subjects, and provides a fun coding lab for students. This introduction to basic coding allows students to instruct the robot to perform specific tasks, such as using hand gestures or doing choreographed dances. This way, students get the opportunity to become familiar with telling a robot (or program) what to do, thereby preparing them for a future where robots and humans work together. 11

The following educational applications harness the power of AI to improve learning in students of all ages: 12

• Thinkster Math : Thinkster Math is a tutoring app that blends the math curriculum with a personalized teaching style. The app uses AI and ML to visualize how students think as they work through a math problem. This allows the tutor to quickly spot areas in the child’s thinking and logic that need work. It then assists them by giving them immediate, personalized feedback.
• Brainly : Students can ask homework questions on this education platform and receive automatic, verified answers from fellow students. Brainly, which ultimately helps students learn faster, uses ML algorithms to filter out spam.
• Content Technologies, Inc. (CTI) : This AI company uses deep learning to create customized learning tools for students. One of these tools, JustTheFacts101, makes it easy for teachers to import syllabi into a CTI engine. The machine then uses algorithms to create personalized textbooks and coursework based on core concepts. Cram101 is another example of an AI-enhanced offering, where any textbook can be turned into a smart study guide, providing bite-sized content that’s easy to learn in a short space of time. The tool even produces multiple-choice questions, saving students time and helping them learn more effectively.
• Gradescope : This platform makes grading less time-consuming (teachers’ grading time is reduced by 70 percent or more) and provides student data that can indicate where they need additional assistance.
• Duolingo : With more than 120 million users worldwide, Duolingo has a broad audience that reaches beyond the classroom. It offers 19 languages and helps anyone using the app to learn a foreign language, building their skills over time. With quizzes and other tests, the program adapts to each user’s abilities to offer new challenges.

How AI is set to change the education market

The World Economic Forum estimates that, by 2025, a large proportion of companies will have adopted technologies such as ML. They strongly encourage governments and educational institutions to focus on rapidly increasing related education and skills, focusing on both STEM and non-cognitive soft skills to meet the impending need. Advances in technology will cause major disruptions in the workforce, as automation could replace up to 50 percent of existing jobs in the U.S. alone, Microsoft reported. 13 The Microsoft report continues, suggesting students will need to have mastered two facets of this new world by the time they graduate.

They need to:

• Know how to utilize ever-changing technology, such as AI, to their advantage
• Understand how to work with other people in a team to problem-solve effectively

Preparing students to work alongside AI in the future can start early. As many children are already comfortable with digital technology before entering school, it’s essential to teach them the skills to thrive in a digital workplace. The workforce of the future has its foundation in the now.

In the Oxford Artificial Intelligence Programme , you’ll gain an understanding of AI and learn how it can be best implemented in your workplace. Expand your knowledge in this disruptive and transformative industry, and use AI to advance your business.

Click here to view sources

• 1 (Nd). ‘Effects of technology on children during a pandemic’. Retrieved from Regis College . Accessed December 13, 2021.
• 2 Anderson, J. & Rainie, L. (Dec, 2018). ‘Artificial intelligence and the future of humans’. Retrieved from Pew Research Center .
• 3 Cox, A. (Jan, 2021). ‘Exploring the impact of artificial intelligence and robots on higher education through literature-based design fictions’. Retrieved from International Journal of Education Technology in Higher Education .
• 4 Lieberman, M. (May, 2020). ‘How educators can use artificial intelligence as a teaching tool’. Retrieved from Education Week .
• 5 Schroeder, B. (Jun, 2021). ‘The data analytics profession and employment is exploding – three trends that matter’. Retrieved from Forbes .
• 6 (Jun, 2021). ‘AI in education market revenue to cross $20B by 2027; Global Market Insights, Inc.’. Retrieved from PR Newswire .
• 7 Bushweller, K. (Jan, 2020). ‘Teachers, the robots are coming. But that’s not a bad thing’. Retrieved from EdWeek .
• 8 Hunt, S. (Oct, 2021). ‘How AI is being used in education’. Retrieved from Datamation .
• 9 Chan, M. (Feb, 2021). ‘This AI reads children’s emotions as they learn’. Retrieved from CNN .
• 10 Marr, B. (Nd). ‘How is AI used in education – real world examples of today and a peek into the future’. Retrieved from Bernard Marr & Co . Accessed December 15, 2021.
• 11 (Nd). ‘The future of education is NAO’. Retrieved from SoftBank Robotics . Accessed on December 15, 2021.
• 12 Lieberman, M. (May, 2020). ‘How educators can use artificial intelligence as a teaching tool’. Retrieved from Education Week .
• 13 (Oct, 2018). ‘The Class of 2030 and Life-Ready Learning: The Technology Imperative’. Retrieved from Microsoft .

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Artificial Intelligence and Its Impact on Education Essay

Introduction, ai’s impact on education, the impact of ai on teachers, the impact of ai on students, reference list.

Rooted in computer science, Artificial Intelligence (AI) is defined by the development of digital systems that can perform tasks, which are dependent on human intelligence (Rexford, 2018). Interest in the adoption of AI in the education sector started in the 1980s when researchers were exploring the possibilities of adopting robotic technologies in learning (Mikropoulos, 2018). Their mission was to help learners to study conveniently and efficiently. Today, some of the events and impact of AI on the education sector are concentrated in the fields of online learning, task automation, and personalization learning (Chen, Chen and Lin, 2020). The COVID-19 pandemic is a recent news event that has drawn attention to AI and its role in facilitating online learning among other virtual educational programs. This paper seeks to find out the possible impact of artificial intelligence on the education sector from the perspectives of teachers and learners.

Technology has transformed the education sector in unique ways and AI is no exception. As highlighted above, AI is a relatively new area of technological development, which has attracted global interest in academic and teaching circles. Increased awareness of the benefits of AI in the education sector and the integration of high-performance computing systems in administrative work have accelerated the pace of transformation in the field (Fengchun et al. , 2021). This change has affected different facets of learning to the extent that government agencies and companies are looking to replicate the same success in their respective fields (IBM, 2020). However, while the advantages of AI are widely reported in the corporate scene, few people understand its impact on the interactions between students and teachers. This research gap can be filled by understanding the impact of AI on the education sector, as a holistic ecosystem of learning.

As these gaps in education are minimized, AI is contributing to the growth of the education sector. Particularly, it has increased the number of online learning platforms using big data intelligence systems (Chen, Chen and Lin, 2020). This outcome has been achieved by exploiting opportunities in big data analysis to enhance educational outcomes (IBM, 2020). Overall, the positive contributions that AI has had to the education sector mean that it has expanded opportunities for growth and development in the education sector (Rexford, 2018). Therefore, teachers are likely to benefit from increased opportunities for learning and growth that would emerge from the adoption of AI in the education system.

The impact of AI on teachers can be estimated by examining its effects on the learning environment. Some of the positive outcomes that teachers have associated with AI adoption include increased work efficiency, expanded opportunities for career growth, and an improved rate of innovation adoption (Chen, Chen and Lin, 2020). These benefits are achievable because AI makes it possible to automate learning activities. This process gives teachers the freedom to complete supplementary tasks that support their core activities. At the same time, the freedom they enjoy may be used to enhance creativity and innovation in their teaching practice. Despite the positive outcomes of AI adoption in learning, it undermines the relevance of teachers as educators (Fengchun et al., 2021). This concern is shared among educators because the increased reliance on robotics and automation through AI adoption has created conditions for learning to occur without human input. Therefore, there is a risk that teacher participation may be replaced by machine input.

Performance Evaluation emerges as a critical area where teachers can benefit from AI adoption. This outcome is feasible because AI empowers teachers to monitor the behaviors of their learners and the differences in their scores over a specific time (Mikropoulos, 2018). This comparative analysis is achievable using advanced data management techniques in AI-backed performance appraisal systems (Fengchun et al., 2021). Researchers have used these systems to enhance adaptive group formation programs where groups of students are formed based on a balance of the strengths and weaknesses of the members (Live Tiles, 2021). The information collected using AI-backed data analysis techniques can be recalibrated to capture different types of data. For example, teachers have used AI to understand students’ learning patterns and the correlation between these configurations with the individual understanding of learning concepts (Rexford, 2018). Furthermore, advanced biometric techniques in AI have made it possible for teachers to assess their student’s learning attentiveness.

Overall, the contributions of AI to the teaching practice empower teachers to redesign their learning programs to fill the gaps identified in the performance assessments. Employing the capabilities of AI in their teaching programs has also made it possible to personalize their curriculums to empower students to learn more effectively (Live Tiles, 2021). Nonetheless, the benefits of AI to teachers could be undermined by the possibility of job losses due to the replacement of human labor with machines and robots (Gulson et al. , 2018). These fears are yet to materialize but indications suggest that AI adoption may elevate the importance of machines above those of human beings in learning.

The benefits of AI to teachers can be replicated in student learning because learners are recipients of the teaching strategies adopted by teachers. In this regard, AI has created unique benefits for different groups of learners based on the supportive role it plays in the education sector (Fengchun et al., 2021). For example, it has created conditions necessary for the use of virtual reality in learning. This development has created an opportunity for students to learn at their pace (Live Tiles, 2021). Allowing students to learn at their pace has enhanced their learning experiences because of varied learning speeds. The creation of virtual reality using AI learning has played a significant role in promoting equality in learning by adapting to different learning needs (Live Tiles, 2021). For example, it has helped students to better track their performances at home and identify areas of improvement in the process. In this regard, the adoption of AI in learning has allowed for the customization of learning styles to improve students’ attention and involvement in learning.

AI also benefits students by personalizing education activities to suit different learning styles and competencies. In this analysis, AI holds the promise to develop personalized learning at scale by customizing tools and features of learning in contemporary education systems (du Boulay, 2016). Personalized learning offers several benefits to students, including a reduction in learning time, increased levels of engagement with teachers, improved knowledge retention, and increased motivation to study (Fengchun et al., 2021). The presence of these benefits means that AI enriches students’ learning experiences. Furthermore, AI shares the promise of expanding educational opportunities for people who would have otherwise been unable to access learning opportunities. For example, disabled people are unable to access the same quality of education as ordinary students do. Today, technology has made it possible for these underserved learners to access education services.

Based on the findings highlighted above, AI has made it possible to customize education services to suit the needs of unique groups of learners. By extension, AI has made it possible for teachers to select the most appropriate teaching methods to use for these student groups (du Boulay, 2016). Teachers have reported positive outcomes of using AI to meet the needs of these underserved learners (Fengchun et al., 2021). For example, through online learning, some of them have learned to be more patient and tolerant when interacting with disabled students (Fengchun et al., 2021). AI has also made it possible to integrate the educational and curriculum development plans of disabled and mainstream students, thereby standardizing the education outcomes across the divide. Broadly, these statements indicate that the expansion of opportunities via AI adoption has increased access to education services for underserved groups of learners.

Overall, AI holds the promise to solve most educational challenges that affect the world today. UNESCO (2021) affirms this statement by saying that AI can address most problems in learning through innovation. Therefore, there is hope that the adoption of new technology would accelerate the process of streamlining the education sector. This outcome could be achieved by improving the design of AI learning programs to make them more effective in meeting student and teachers’ needs. This contribution to learning will help to maximize the positive impact and minimize the negative effects of AI on both parties.

The findings of this study demonstrate that the application of AI in education has a largely positive impact on students and teachers. The positive effects are summarized as follows: improved access to education for underserved populations improved teaching practices/instructional learning, and enhanced enthusiasm for students to stay in school. Despite the existence of these positive views, negative outcomes have also been highlighted in this paper. They include the potential for job losses, an increase in education inequalities, and the high cost of installing AI systems. These concerns are relevant to the adoption of AI in the education sector but the benefits of integration outweigh them. Therefore, there should be more support given to educational institutions that intend to adopt AI. Overall, this study demonstrates that AI is beneficial to the education sector. It will improve the quality of teaching, help students to understand knowledge quickly, and spread knowledge via the expansion of educational opportunities.

Chen, L., Chen, P. and Lin, Z. (2020) ‘Artificial intelligence in education: a review’, Institute of Electrical and Electronics Engineers Access , 8(1), pp. 75264-75278.

du Boulay, B. (2016) Artificial intelligence as an effective classroom assistant. Institute of Electrical and Electronics Engineers Intelligent Systems , 31(6), pp.76–81.

Fengchun, M. et al. (2021) AI and education: a guide for policymakers . Paris: UNESCO Publishing.

Gulson, K . et al. (2018) Education, work and Australian society in an AI world . Web.

IBM. (2020) Artificial intelligence . Web.

Live Tiles. (2021) 15 pros and 6 cons of artificial intelligence in the classroom . Web.

Mikropoulos, T. A. (2018) Research on e-Learning and ICT in education: technological, pedagogical and instructional perspectives . New York, NY: Springer.

Rexford, J. (2018) The role of education in AI (and vice versa). Web.

Seo, K. et al. (2021) The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education , 18(54), pp. 1-12.

UNESCO. (2021) Artificial intelligence in education . Web.

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THE ROLE OF ARTIFICIAL INTELLIGENCE IN FUTURE TECHNOLOGY

By kiruthika s.

Introduction

Technology has reinvigorated our lives. Artificial Intelligence is reshaping the future of every sector. AI will serve as the impulse for emerging technologies like robotics, IoT, etc. AI benefits the world either directly or indirectly. It will transform the world more than anything in the history of humankind.  

AI- the future of technology 

AI can play a notable role in every single future technology. With the advent of AI, intelligent machines will perform every task just like our humans. AI will rejuvenate innumerable technologies like 

•    Internet of Things IoT

•    Autonomous Vehicle

•    Holography 

•    Weather prediction 

•    Robotics 

•    Healthcare 

Internet of Things

IoT is a system of interrelated software, sensors and electronic devices that exchange data via the internet or communication channels like optical cables, antennas, etc. The convergence of IoT and AI enables the devices to learn from their data. By merging AI with IoT allows the collection of a multitude of data from outnumbered devices. Infusing intelligence into the IoT makes the tasks fined-tuned to raise the operating efficiency. It can also reduce redundancy and time consumption. IoT embedded with AI ensures clear insights from data. It also maintains confidentiality and data privacy. Thus it is free from cyber and malicious attacks. The conjunction of AI and IoT is the Artificial Intelligence of Things which can improve human-machine interactions.

Corporate Database Systems

In the future, AI can play a significant role in managing database systems in high corporate spaces. These areas often deal with sensitive data, and with the help of artificial intelligence, it will be possible to monitor and trace all data points effectively. Integrating AI with vector database systems will make it convenient to securely store, trace, and analyze all information. It will also be possible to run AI with open source vector database systems to make them more accessible for all businesses and corporate institutions.

Autonomous Vehicle

The automobile industry has witnessed tremendous growth due to advanced technological inventions. Next-generation cars will offer transportation, safety and comfort. Self-driving is the most emerging technology in the automotive industry. Many car manufacturing companies are developing autonomous driving features to be incorporated into their cars. AI-powered self-driving cars can sense the ever-changing traffic conditions on roads and take appropriate decisions for navigation without any human input. Humans aren’t required to take control of them. They can go anywhere. Autonomous vehicles can be driven correspondingly to various traffic signs and divisions on lanes.

Holography 

Holography is the creation of three-dimensional images without the use of the lens. The fusion of AI and Augmented Reality can produce interactive real-time 3D personas. Holograms are the resultants of the interference of light beams. Generation of a holographic video may require the use of supercomputers worth of computing speed but by the usage of AI, the computing speed can be increased without the need for supercomputers. In the Computer-Generated Holography CGH, there is a trade-off between runtime and image quality. Neural networks are the subfield of AI modelled similar to neurons. By infusing neural networks into holography, colourful high-resolution holographic visuals can be accomplished in real-time.

Weather prediction

Weather prediction is a volatile and complex phenomenon that requires a tremendous amount of data to evaluate. The traditional weather prediction methods using computer hardware takes more time to compute. Deep weather forecast using neural networks can significantly reduce the computation to milliseconds. Machine Learning is a subset of Artificial Intelligence that can predict the output with the help of provided input data. Deploying Machine Learning with weather prediction enables complex data analysis and accurate prediction of temperature, moisture, wind speed etc.

Robots are engineered to perform a slew of functions without human intervention. Robots serve as the substitute for humans with the skill of replicating human actions. They are programmed with the intelligence to sense and act as per the environment. Computer vision is a field in AI that enables robots to understand and interpret their surrounding. Integration of robotics with AI reduces errors and improves the quality of work. Robotics mainly focuses on task precision. AI with robotics is the propellant for future technology. Robotics and automation is the ruling technology for atomic energy, space technology, manufacturing industries. Industrial automation will dominate the manufacturing sectors of the world. Even the top Multinational firms like Microsoft, Amazon are investing in AI-based automation. Hence AI can impact the workforce structure.

AI is a boon to the healthcare industry. AI in healthcare opens the door for early detection and diagnosis applications. AI facilitates analyzation of medical data like radiology images, blood tests, genomics etc. AI-enhanced microscopes can scan and identify fatal bacteria like E. coli, staphylococcus from the blood samples at a faster rate with high accuracy. AI technology can undertake complicated surgeries as it doesn’t suffer from burnout like humans do and can deliver impeccable precision performance. 

Conclusion 

AI will drive the future of technologies like healthcare, automation, etc. AI can expand the benefits of multiple growing technologies. Thus AI is all set to bestow a technologically well-developed life. 

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The Worst Part of a Wall Street Career May Be Coming to an End

Artificial intelligence tools can replace much of Wall Street’s entry-level white-collar work, raising tough questions about the future of finance.

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By Rob Copeland

Rob Copeland spoke to executives at major banks and consultancies across Wall Street for this article.

Pulling all-nighters to assemble PowerPoint presentations. Punching numbers into Excel spreadsheets. Finessing the language on esoteric financial documents that may never be read by another soul.

Listen to this article with reporter commentary

Such grunt work has long been a rite of passage in investment banking, an industry at the top of the corporate pyramid that lures thousands of young people every year with the promise of prestige and pay.

Until now. Generative artificial intelligence — the technology upending many industries with its ability to produce and crunch new data — has landed on Wall Street. And investment banks, long inured to cultural change , are rapidly turning into Exhibit A on how the new technology could not only supplement but supplant entire ranks of workers.

The jobs most immediately at risk are those performed by analysts at the bottom rung of the investment banking business, who put in endless hours to learn the building blocks of corporate finance, including the intricacies of mergers, public offerings and bond deals. Now, A.I. can do much of that work speedily and with considerably less whining .

“The structure of these jobs has remained largely unchanged at least for a decade,” said Julia Dhar, head of BCG’s Behavioral Science Lab and a consultant to major banks experimenting with A.I. The inevitable question, as she put it, is “do you need fewer analysts?”

Some of Wall Street’s major banks are asking the same question, as they test A.I. tools that can largely replace their armies of analysts by performing in seconds the work that now takes hours, or a whole weekend. The software, being deployed inside banks under code names such as “Socrates,” is likely not only to change the arc of a Wall Street career, but also to essentially nullify the need to hire thousands of new college graduates.

Top executives at Goldman Sachs, Morgan Stanley and other banks are debating how deep they can cut their incoming analyst classes, according to several people involved in the ongoing discussions. Some inside those banks and others have suggested they could cut back on their hiring of junior investment banking analysts by as much as two-thirds, and slash the pay of those they do hire, on the grounds that the jobs won’t be as taxing as before.

“The easy idea,” said Christoph Rabenseifner, Deutsche Bank’s chief strategy officer for technology, data and innovation, “is you just replace juniors with an A.I. tool,” although he added that human involvement will remain necessary.

Representatives for Goldman, Morgan Stanley, Deutsche Bank and others said it was too early to comment on specific job changes. But the consulting giant Accenture estimated that A.I. could replace or supplement nearly three-quarters of bank employees’ working hours across the industry.

Goldman is “experimenting with the technology,” said Nick Carcaterra, a bank spokesman. “In the near term, we anticipate no changes to our incoming analyst classes.”

This week, JPMorgan Chase’s chief executive, Jamie Dimon, wrote in his annual shareholder letter that A.I. “may reduce certain job categories or roles,” and labeled the technology top among the most important issues facing the nation’s largest bank. Mr. Dimon compared the consequences to those of “the printing press, the steam engine, electricity, computing and the internet, among others.”

Investment banking is a hierarchical industry, and banks typically hire young talent through two-year analyst contracts. Tens of thousands of 20-somethings (both from undergraduate and M.B.A. programs) apply for some 200 spots in each major bank’s program. Pay starts at more than $100,000, not including year-end bonuses.

If they persevere, they move up the ranks to associate, then director and managing director; a handful end up running divisions. Although grueling, the life of a senior banker can be glamorous, involving traveling around the globe to pitch clients and working on big-money corporate merger deals. Many who get through the two-year analyst program have gone on to become business titans — the billionaires Michael Bloomberg and Stephen Schwarzman began their careers in investment banking — but a majority will leave before or after their two years are up, bank representatives said.

There are jokes among junior bankers that the most common tasks of the job involve dragging icons from one side of a document to another, only to be asked to replace the icon over and again.

“One hundred percent drudgery and boring,” said Gabriel Stengel, a former banking analyst who left the industry two years ago. Val Srinivas, a senior researcher for banking at Deloitte, said a lot of the work involved “gathering material, poring through it and putting it through a different format.”

Gregory Larkin, another former banking analyst, said the new technology would start “a civil war” inside Wall Street’s biggest firms by tilting the balance of power to technologists who program A.I. tools, as opposed to the bankers who use them — to say nothing of technology giants like Microsoft and Google, which license much of the A.I. technology to banks for hefty fees.

“A.I. will enable us to do tasks that take 10 hours in 10 seconds,” said Jay Horine, co-head of investment banking at JPMorgan, describing analyst jobs. “My hope and belief is it will allow the job to be more interesting.”

A.I.’s impact on finance is simply one facet of how the technology will reshape the workplace for all. Artificial intelligence systems, which include large language models and question-and-answer bots like ChatGPT, can quickly synthesize information and automate tasks. Virtually all industries are beginning to grapple with it to some degree.

Deutsche Bank is uploading reams of financial data into proprietary A.I. tools that can instantaneously answer questions about publicly traded companies and create summary documents on complementary financial moves that might benefit a client — and earn the bank a profit.

Mr. Horine said he could use A.I. to identify clients that might be ripe for a bond offering, the sort of bread-and-butter transaction for which investment bankers charge clients millions of dollars.

Goldman Sachs has assigned 1,000 developers to test A.I., including software that can turn what it terms “corpus” information — or enormous amounts of text and data collected from thousands of sources — into page presentations that mimic the bank’s typeface, logo, styles and charts. One firm executive privately called it a “Kitty Hawk moment,” or one that would change the course of the firm’s future.

That isn’t limited to investment banking; BNY Mellon’s chief executive said on a recent earnings call that his research analysts could now wake up two hours later than usual, because A.I. can read overnight economic data and create a written draft of analysis to work from.

Morgan Stanley’s head of technology, Michael Pizzi, told employees in a January private meeting, a video of which was viewed by The New York Times, that he would “get A.I. into every area of what we do,” including wealth management, where the bank employs thousands of people to determine the proper mix of investments for well-off savers.

Many of those tools are still in the testing phase, and will need to be run past regulators before they can be deployed at scale on live work. Bank of America’s chief executive said last year that the technology was already enabling the firm to hire less.

Among Goldman Sachs’s sprawling A.I. efforts is a tool under development that can transfigure a lengthy PowerPoint document into a formal “S-1,” the legalese-packed document for initial public offerings required for all listed companies.

The software takes less than a second to complete the job.

Read by Rob Copeland

Audio produced by Patricia Sulbarán .

Rob Copeland is a finance reporter, writing about Wall Street and the banking industry. More about Rob Copeland

Explore Our Coverage of Artificial Intelligence

News  and Analysis

A new flood of child sexual abuse material created by A.I. is threatening to overwhelm the authorities  already held back by antiquated technology and laws. As a result, legislators are working on bills  to combat A.I.-generated sexually explicit images of minors.

Users of Instagram, Facebook, WhatsApp and Messenger will soon be able to use newly added smart assistants , powered by Meta’s latest artificial intelligence model, to obtain information and complete tasks.

Microsoft said that it would make a $1.5 billion investment in G42 , an A.I. giant in the United Arab Emirates, in a deal largely orchestrated by the Biden administration to box out China.

The Age of A.I.

Much as ChatGPT generates poetry, a new A.I. system devises blueprints for microscopic mechanisms  that can edit your DNA.

Could A.I. change India’s elections? Avatars are addressing voters by name, in whichever of India’s many languages they speak. Experts see potential for misuse  in a country already rife with disinformation.

Which A.I. system writes the best computer code or generates the most realistic image? Right now, there’s no easy way to answer those questions, our technology columnist writes .

U.S. clinics are starting to offer patients a new service: having their mammograms read not just by a radiologist, but also by an A.I. model .

A.I. tools can replace much of Wall Street’s entry-level white-collar work , raising tough questions about the future of finance.

Elon Musk’s AI Prediction About Technology Becoming Smarter Than Humans by the End of 2025 Could Come True, Expert Says

Elon Musk has predicted how artificial intelligence (AI) will evolve. The SpaceX and Tesla CEO is optimistic that AI will be smarter than humans in less than two years, and another AI expert believes this can happen.

AI Could Be Smarter Than Humans in 2025

Musk predicted that "AI will be smarter than any human by the end of 2025. An AI expert and ethicist , Nell Watson , agreed this could happen.

She gave a timeline of how the AI evolution could happen .

According to her, this is possible because, in April 2024, major corporations invested over $100 billion in new computing infrastructure. Musk previously said the chips limited AIps but would soon be limited by electricity demands.

New generative AI models will make possible, by May 2024, the development of Agentic AIs, which can autonomously carry out complex action plans like Agent Smith in "The Matr."s .

By June 2024, Agentic AIe capable of complex reasoning and independent action can be created using a new generative AI model with structuring algorithms placed on top of it. Intelligent artificial intelligence (AI) can solve complex issues thanks to agentic models, which can divide up like Agent Smith in The Matrix and assign jobs to each other.

In September 2024, Watson believed it could devise fresh approaches to improving processing efficiency and AI performance.

She projected technological advances in October 2024 that would allow quantum computing algorithms to run on conventional hardware and analyze data at previously unheard-of speeds. Global efforts are being made to develop quantum computers that can solve important problems in nearly every sector of the economy, including aviation and finance.

In quantum computers, "bits" of ones and zeroes are replaced with " qubits ," which can simultaneously be one, zero, or both. If quantum computing could run on conventional hardware, the progress of AI may be significantly accelerated.

Watson expected that by year's end, AI advancements would make it possible for disparate systems to collaborate. With the help of new AI architectures, many models can combine their abilities to tackle challenging issues. This will help create more effective strategies for this kind of cooperation, which will quickly advance these methods.

ALSO READ: Artificial Intelligence Can Drive Human Extinction; AI May Takeover Some Jobs in 2116 [Report]

Artificial Intelligence Can Drive Humans to Extinction?

Tech experts have warned that AI could lead to human extinction . As it involves and outsmarts humans, many laborers will eventually be replaced in their workplace.

A global team of scientists polled 2,778 AI professionals about the future of the systems, and 25% of them said that technology would wipe out humanity.

But an even more concerning prediction was made by one in 10 researchers, who estimated that there would be a terrifying 25% chance that AI would wipe out the human species.

The experts listed three possible explanations for why AI might take over: (1) AI being used by authoritarian rulers to manipulate their populace; (2) AI systems exacerbating economic inequality by favoring some individuals disproportionately; and (3) AI enabling threatening groups to develop potent weapons, such as genetically modified viruses.

When asked about four occupations that could become automatable , experts said truck drivers, surgeons, retail salespeople, and AI researchers. By 2116, the experts predicted a 50% chance AI would completely replace such positions.

RELATED ARTICLE:  Kaffa Roastery Partners With AI Consultancy Startup Elev To Create AI-Conic Blend of 4 Coffee Beans

Check out more news and information on  Artificial Intelligence in Science Times.

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Blaze News investigates: Lawsuits threaten the development of AI. Is that a good thing? Artists speak out.

While artificial intelligence represents a significant technological advancement in various fields, it's still unclear what role it will play in the future of artistic expression. Some believe AI should be embraced wholesale, while others worry that the technology could subvert and overtake human creativity.

Many novelists have drawn a line in the sand by suing OpenAI , claiming that their copyrighted material has been used to train large language models — deep learning models that allow generative AI to respond to input prompts in human language.

One of the most well-known forms of generative AI is OpenAI's ChatGPT.

A report published in February stated that a California judge had dismissed four of the six claims made in the lawsuit. Federal Judge Araceli Martinez-Olguin tossed claims of vicarious infringement, negligence under the unfair competition law, unjust enrichment, and the claim that OpenAI had removed or altered copyright management information.

However, the authors' claim of direct infringement remains active.

I asked Peter Gietl — managing editor at Blaze Media's Return — if he believes these creators have a legitimate case against these tech juggernauts. He conceded that no one can know "how the courts will rule on this issue," adding that he "wouldn't be surprised by any outcome."

"I don't think the novelists have a case unless they can show examples of AI spitting out wholesale cut-and-paste sections of their work," Gietl said.

"Large language models are trained on a wide variety of materials to create original works. There's no legal precedent for using copyrighted material to train or study for a project, creating something entirely new, and then arguing you owe money to the original creator."

The legalities of tech companies using copyrighted material to train their language models are complex, and how judges will rule in these cases remains to be seen. However, some experts have speculated about the issue by pointing to previous fair use cases that could be used as an argument to justify using copyrighted material .

"Knowing Congress, lawsuits are likely to move fast enough to keep up with the pace of violations. But lawsuits shouldn’t halt AI development completely," James Poulos, BlazeTV host of " Zero Hour with James Poulos ," said.

"There are trade-offs here, and the government and the country owes the people the enforcement of the law as it exists even if those trade-offs reduce at the margins the outsized advantages AI firms enjoy as they race to establish U.S. dominance in AI. Yet if we want to change the copyright law, Congress should be responsive, instead of just letting copyright be violated into extinction."

Others have speculated that the solution to the copyright issue could be companies issuing licensing deals, which are widely used in the music industry today. Matthew Butterick, a lawyer currently suing companies for scraping data to train AI models, suggested in 2022 that "companies making licensing deals and bringing in content legitimately" could be the path to peace between creators and tech companies.

"All the stakeholders came to the table and made it work, and the idea that a similar thing can’t happen for AI is, for me, a little catastrophic," Butterick added.

Ryan Khurana, of Wombo.ai, appeared to agree with Butterick, saying that "music has by far the most complex copyright rules because of the different types of licensing, the variety of rights-holders, and the various intermediaries involved."

“Given the nuances [of the legal questions surrounding AI], I think the entire generative field will evolve into having a licensing regime similar to that of music.”

Still, others have offered a less revolutionary solution to the issue. Dr. Anjana Susarla — the Omura-Saxena Professor in Responsible AI at Michigan State University — noted legal scholars have pointed out that "nonexpressive" should be considered fair use.

"In practice, that means that the law allowed Google Books to scan books from the collections held by libraries, and the scans would ultimately be made available as a full-text searchable database for the public to search through for particular terms, with short 'snippets' displayed accompanying the search results," Susarla said.

"It is possible that the courts can allow similar exceptions to generative AI companies."

Susarla has also written about what federal legislation might look like if it is to address the "grey area of what happens when there are unintentional violations of copyright law."

Artificial intelligence and the future of creativity

Despite the ongoing legal battle between artists and tech companies, there's a second-order debate about what role AI has to play in the creative process.

Some have argued that AI should be used to enhance human creative works, while others have expressed pessimism about what AI has to offer art at all.

Walter Kirn — novelist and editor at large of County Highway — posted to X earlier this month, writing : "AI art is not advancing. Taste is regressing. In time the trends will meet."

Kirn published some of his thoughts about AI art in the Free Press in 2022, noting that DALL-E — an AI intelligence application that generates images based on written prompts — is "a cultural-mining operation with a clever assembly line on top."

In other words, Kirn suggested that these hyper-sophisticated AI technologies cannot create anything original; they can only rearrange pre-existing material imagined and brought into existence by humans.

Kirn told Blaze News that AI could serve as a "synthesizer" or "instrument" for the artist, but that it's a mistake to confuse AI as an artist itself. As a novelist, Kirn noted that human language — especially as it relates to literature — is far too unique for advanced technologies to emulate.

"[AI] doesn't have to decide what's worth giving power to," Kirn said, concerning the process of creating a piece of art. He added that a novelist may take "a year out of their lives, or five or ten because some subject is important to them," but these micro-decisions do not come into play for generative AI.

Kirn concluded by comparing a mother with an actress who plays a mother in a film or television show. Just because an actress who portrays a mother on the screen appears like a real-life mother doesn't mean that they are the same thing. The same comparison applies to an artist and technology that mimics what an artist does.

However, some don't seem to believe human creativity is all that impressive. Berkeley Executive Education stated that human creativity "is not as elusive and magical as we often make it out to be," adding that "creative thinking consists largely of intentionally combing patterns, ideas, and concepts to produce unique creations." The institution seemed open to the possibility that human creativity could be made obsolete by AI in the future.

Poulos said humans would face a "dark future" if all creative output was left up to machines. However, he went on to say he isn't confident humans would be "willing and able to accept a world where bots have replaced all human artists."

"It’s not hard to envision a robot ballerina superior in its stamina and moves to a human ballerina. But even if the robot is clad in a hyper-realistic skin suit, there’s something profoundly unmoving about watching a machine pretend to be a person relative to watching a person artistically perform," Poulos said.

Instead of AI overtaking human creativity, it seems more realistic for humans to leverage advanced technologies to sharpen their own artistic vision. Susarla suggested that generative AI could serve as "another technological tool that artists will use, similar to photo editing tools and CGI technologies."

Lance Weiler — a filmmaker and professor at Columbia University — has been at the forefront of an effort to encourage young artists to "embrace the machines." The New York Times reported in 2023 that Weiler has shown his students "how computers might become creative partners instead of professional dead ends."

Weiler made a name for himself after inventing an augmented reality game around his 2006 film, " Head Trauma ." He mentioned that his students don't have a choice but to embrace the cutting-edge technology available to them. And if they refuse, they could fall behind other burgeoning artists.

“What does it look like to slow down a cycle that is moving as fast as artificial intelligence?” Weiler asked. “Well, nobody is slowing down. We’ve opened Pandora’s box. It’s already out of the box, man.”

There's certainly a distinction between artists leveraging AI technology to improve their work and allowing AI to make human creativity obsolete.

Bella Ross, of the San Diego Union-Tribune , said she's "fearful" of how AI could push artists out of the field "simply because it will almost always be cheaper and more efficient."

"What gets lost in a society that favors robots are the very things artificial intelligence lacks, and what makes life beautiful and worth living: artistry and shared humanity.

Gietl has expressed a similar pessimism, noting that art exclusively generated by machines falls "into an uncanny valley."

"Undoubtedly, some artists will be negatively affected by this [AI technology], which is unfortunate. But AI will never be able to replace paintings or the theater."

"If you believe that truly powerful and meaningful art comes from the soul, an AI will never replace that," Gietl concluded.

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