will robots take my job essay

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Why Robots Won’t Steal Your Job

• Nahia Orduña

AI will actually help young people find more satisfying entry-level roles.

According to the World Economic Forum Future of Jobs Report 2020, 85 million jobs may be displaced by the shift in labor between humans and machines by 2025, while 97 million new roles may emerge. These are the “jobs of the future,” and they are actually better opportunities for early career professionals. Why?

• The more computers are trained to conduct high-repetitive tasks that are often assigned to entry-level employees, the more roles focused on complex tasks with competitive salaries will arise in their place.
• As new types of roles — roles that no one has done before — are created, young workers are less likely to be forced to compete with their seniors, and more likely to be pioneers
• So, how should you prepare to land one of these roles? First, do a simple Google search. Include the name of your industry plus key phrases like “future of work,” or “job trends in [industry]” to see what positions are up and coming in your area of interest.
• Next, figure out what skills you have to master to be a competitive candidate. You can find these within job descriptions, or by researching people in similar roles on LinkedIn.
• Finally, figure out what unique qualities you will bring to the table. Ask yourself: Which skills have I acquired over the years because of who I am, where I am from, or what I am passionate about? The ability to combine the new skills you have acquired with what makes you unique will help you build a resume that stands out.

Where your work meets your life. See more from Ascend here .

Science-fiction films and novels usually portray robots as one of two things: destroyers of the human race or friendly helpers. The common theme is that these stories happen in an alternate universe or a fantasy version of the future. Not here, and not now — until recently. The big difference is that the robots have come not to destroy our lives, but to disrupt our work.

• NO Nahia Orduña is an engineer holding a MBA and a technical leader at Amazon Web Services . She is the author of Your Digital Reinvention . Learn more about the Future of Work and find free tools to thrive in the digital world at https://nahiaorduna.com.

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Robots and your job: how automation is changing the workplace

A new study shows that robots are changing the workplace in unexpected ways. Image:  REUTERS/Arnd Wiegmann

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Stay up to date:, emerging technologies.

• A new survey-based study has explored how automation is changing the workplace.
• In spite of popular beliefs, robots are not replacing workers, with data showing that increased automation actually leads to more hiring overall.
• However, as a result of technology which reduces human error, managers of high-skilled workers may not be required as much.
• Lynn Wu co-author of The Robot Revolution study encourages leaders to prepare for automation, to maximize the new benefits.

If you’re worried that robots are coming for your job, you can relax — unless you’re a manager.

A new survey-based study explains how automation is reshaping the workplace in unexpected ways. Robots can improve efficiency and quality, reduce costs, and even help create more jobs for their human counterparts. But more robots can also reduce the need for managers.

The study is titled “The Robot Revolution: Managerial and Employment Consequences for Firms.” The co-authors are Lynn Wu , professor of operations, information and decisions at Wharton; Bryan Hong , professor of entrepreneurship and management at the University of Missouri Kansas City’s Bloch School of Management; and Jay Dixon, an economist with Statistics Canada. The researchers said the study, which analyzed five years’ worth of data on businesses in the Canadian economy, is the most comprehensive of its kind on how automation affects employment, labor, strategic priorities, and other aspects of the workplace.

Wu recently spoke with Knowledge@Wharton about the paper and its implications for firms.

More robots, more workers

Contrary to popular belief, robots are not replacing workers. While there is some shedding of employees when firms adopt robots, the data show that increased automation leads to more hiring overall. That’s because robot-adopting firms become so much more productive that they need more people to meet the increased demand in production, Wu explained.

“Any employment loss in our data we found came from the non-adopting firms,” she said. “These firms became less productive, relative to the adopters. They lost their competitive advantage and, as a result, they had to lay off workers.”

Armed with facts about automation, firms need to consider a bigger-picture strategy when bringing in robots, she said.

“The story is really about how do you leverage technology better to become more productive, to become more competitive? And how do you change your managerial firm practices so you can get the most out of your robot technologies?” Wu said.

Have you read?

Will robots be good or bad for our jobs here are lessons from japan, robots will soon be a necessity but they won't take all our jobs, ai and robots could create as many jobs as they displace, robots render some managers obsolete.

Certain kinds of managers become superfluous as businesses increase automation, according to the study. The drop is simply an effect of modern technology, Wu said. As different tasks and processes are automated, human error is drastically reduced. So, too, is the need for close monitoring of that work by managers.

“Technology can generate reports on what the robots did, what material they used, and they can aggregate it at the firm level, division level, to get lots of different operational metrics very easily,” Wu said. “And those are the kinds of things that managers tend to do.”

But it’s a bit more complex than that. The managerial decrease comes from the changing composition of employment. Although robot adoption results in increased employment, the increase is not uniform across skills, Wu said. Low-skilled workers, such as box packers, and high-skilled workers, such as engineers, grow in numbers, but middle-skilled workers become endangered.

“When you see a huge decrease in middle-skilled work and an increase in those extremes — high- and low-skilled labor — it means the type of managers you need to manage this new workforce will be different.”

Someone who supervises low-skilled workers can manage a lot more people when the firm brings in robots because of the standardization and efficiency. But the change is more ambiguous for managers of high-skilled workers. Those employees are typically responsible for innovation, rather than operations, which is harder to measure.

“Highly-skilled professionals are very good at what they do, better than their managers. They don’t need managers to tell them how to do their jobs or make sure they arrive to work on time,” Wu said. “Managing high-skilled workers is much more like coaching or advising. Managers advise them to help them to achieve the best they can at work, and that kind of skill is very different from supervising work.”

The revolution is inevitable

Wu said the robot revolution is “inevitable” given the leaps in artificial intelligence, machine learning, and other technologies rapidly transforming the workplace. She encouraged business leaders to embrace the change and explore strategies to maximize the benefits. For example, the study found that robots were associated with greater use of performance-based pay because automation reduces variance. In other words, it’s easier to meet production quotas when robots are on the job. Robots also reduce workplace injuries, according to the study.

“In the next couple of years, you’re going to see huge industry turbulence, if you haven’t seen it already,” she said. “The firms that figure it out, either by luck or by ingenuity, are going to kill it. And the firms that don’t figure it out are not.”

The Top 10 Emerging Technologies of 2023 report outlined the technologies poised to positively impact society in the next few years, from health technology to AI to sustainable computing.

The World Economic Forum’s Centre for the Fourth Industrial Revolution is driving responsible technology governance, enabling industry transformation, addressing planetary health, and promoting equity and inclusion.

Learn more about our impact:

• Digital inclusion: Our EDISON Alliance is mobilizing leaders from across sectors to accelerate digital inclusion, having positively impacted the lives of 454 million people through the activation of 250 initiatives across 90 countries.
• AI in developing economies: Our Centre for the Fourth Industrial Revolution Rwanda is promoting the adoption of new technologies in the country, enabling over 4,000 daily health consultations using AI.
• Innovative healthcare: Our Medicine from the Sky initiative is using drones to deliver medicine to remote areas in India, completing over 950 successful drone flights.
• AI for agriculture: We are working with the Government of India to scale up agricultural technology in the country, helping more than 7,000 farmers monitor the health of their crops and soil using AI.

Want to know more about our centre’s impact or get involved? Contact us .

Wu also urged business leaders to be mindful of their low-skilled workers. As a company automates and the middle-skill level shrinks, those entry-level workers lose upward mobility.

“In our old paradigm, we don’t expect people to stay on those jobs forever,” she said. “But now you notice that the career ladder is broken. There is no middle skill to go to. There are no supervisory jobs to go to. That means that the contract, where there is an implicit understanding that you will move up eventually from your low-skilled work, needs to be revisited because it’s changing.”

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World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

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Will robots take our jobs?

Three CAS experts share their ideas for what it means to be human in a world of AI

August 28, 2023 | in The Big Question

By Ana Rico (COM’25)

As artificial intelligence (AI) systems become more advanced and powerful — processing vast amounts of data, performing complex tasks, generating new ideas, designs, and, even language, new questions have emerged: What does it mean for privacy? Fairness? Transparency? Accountability? What does it mean for humanity? What does it mean for our jobs? 

When we asked ChatGPT, the artificial intelligence-infused chatbot said: “Being human in the age of AI means navigating a world where technology is increasingly integrated into our lives and has the potential to reshape our society, economy, and even our understanding of what it means to be human.” 

AI systems can complement human abilities; but they cannot replace human creativity, imagination, or emotional intelligence. Being human in the age of AI means grappling with these questions, adapting to new ways of working and living alongside AI, leveraging its strengths while also recognizing its limitations; celebrating and cultivating our ability to dream, create, and imagine new possibilities.

To help us understand all of this, and learn where artificial intelligence falls short, we asked three CAS faculty members in three different fields — Economics, Philosophy, and Psychological and Brain Sciences — are robots taking over our jobs?

Pascual Restrepo, an associate Professor of Economics whose research focuses on the impact of technology on labor markets, employment, wages, inequality, and growth. His most recent publication, “Demographics and Automation,” studies the impact of industrial robots on US labor markets. 

Juliet Floyd, Borden Parker Browne Professor of Philosophy and Director of the Boston University Center for the Humanities. A philosopher on logic, language, mathematics, and science, she has written over 80 articles, one of them on the topic of opacity in AI and the concepts of “rigor” and the “everyday.” ‘

Rachel Denison, an Assistant Professor of Psychological and Brain Sciences who studies visual perception, attention, and decision making. Her research focuses on how the brain integrates visual information in real-time to produce a coherent perceptual experience. 

Pascual Restrepo , associate Professor of Economics

Focusing on the sheer number of jobs or total hours worked is misguided. The real concern is whether technological advancements are paving the way toward a future where large segments of society find their skills and abilities undervalued, leaving them without access to high-pay jobs where they can provide value. In such a scenario, a small group of individuals would have a significant stake in the economy, while the majority would have minimal input and no access to meaningful work.

This scenario is eerily reminiscent of Kurt Vonnegut’s novel Player Piano , where automation and machines have replaced most human labor, leading to a stark division between the few who maintain the machines and the majority who are left without access to meaningful work.

Are we heading to a future with a scarcity of valuable jobs for a significant segment of society? It is hard to tell. Technology will undoubtedly eliminate some roles for humans, but it is also likely to create new ones. The nature of jobs will inevitably change, as it has throughout history. The critical question is whether these new roles will generate enough demand for workers with diverse skills or will they only benefit a select few with highly sought-after skills, much like Vonnegut’s engineers.

During the initial stages of the industrial revolution, the transition wasn’t smooth, and it took some time for technological progress to raise everyone’s wages and create broad-based access to valuable employment opportunities. In the last 40 years, we have seen a similar trend, with technological progress automating or devaluing some jobs and skills more than it has created new employment opportunities, especially for workers without a college degree. This is evidenced by the stagnant wages and decreasing employment opportunities for non-college-educated Americans since 1980. 

We can’t definitively say that robots and AI will leave many without access to good, high-paying jobs. But we should not rule out this possibility either. Our best course of action requires acknowledging the potential for significant shifts in the job market and preparing accordingly, lest we find ourselves in a reality akin to Vonnegut’s Player Piano.

Juliet Floyd , Borden Parker Bowne Professor of Philosophy and director of the Boston University Center for the Humanities

Step-by-step, rule-determined tasks can be automated. ChatGPT can generate pretty good, sometimes accurate, web-scraped B-level reporting on facts, more grammatically than some humans, because most of what we say in everyday life is predictable. However, human philosophical and ethical experience — reflection, discussion and personal growth — cannot be automated. As Arendt put it: “vitality and liveliness can be conserved only to the extent that [humans] are willing to take the burden, the toil and trouble of life, upon themselves”. Maybe more of us should and will pursue more forms of work, but not as a job.

In the history of capitalism, jobs have frequently been created from technological shifts, but disruptions made life brutally difficult for those whose expertise is displaced. Today we are all dependent upon AI and are undergoing a major shift in forms of vulnerability. Startups seemed romantic until many young workers didn’t get paid. When flights are canceled, the remarkably dense efficiency of our air transportation systems crashes, saddling us with huge backups and supply chain snafus. Having one’s phone near one is now almost always a must. Inequality is a major problem, as are climate degradation and the danger of AI-designed superbugs and crowd-sourced mass shooting manuals for Incels. Supermarkets, which were called “self-serve” when they appeared, were far more efficient than old-time, everything-behind-the-counter stores until COVID hit, and then some people again began to ask someone else to pack their bags, and at Amazon it was a robot, while the delivery person was a person. 

We will need AI to save us from AI, whether we like it or not, and we will have to discuss and interpret and include ethics in its uses. There will be plenty to do. Human to human culture, including intergenerational differences, is crucial. GrubHub became popular during COVID: remote work made it romantic to order a meal in — and remote work has the potential to disrupt offices. But people seem to be drifting back toward the idea of going out and being served by a real person, just as some are drifting away from dating apps to human matchmakers . 

Will this last? BU Emerging Media Studies Ph.D. Kate Mays , now a postdoc at Syracuse, showed in her dissertation on emotions and robots that inter-culturally humans have certain preferences in the way robots appear: gender-neutral is the general favorite, female-looking next, and male-looking robots are the least liked. But will this be the same in the next generation? Will it be true for sex robots? How many people will prefer sex robots to humans anyway? Note that while in robotic Fictosexuality a human fantasizes a partner who will never let them down, when the software of a holographic companion is discontinued, one may be worse off . 

Rachel Denison , assistant professor of Psychological & Brain Sciences

For robots to take human jobs, they have to be able to do things that humans do. So which human tasks are easier and harder for robots, and why?

Today’s computer-controlled systems can do two kinds of tasks well—which, interestingly, lie on opposite ends of a spectrum. At one end, industrial machines excel at automation, churning out everything from cars to computer chips. Automation tasks involve repetitive, inflexible behavior in highly-controlled physical environments. Factories can be built to precise specifications for robots to operate according to a fixed program. At the other end, generative AI systems excel at producing infinitely flexible abstract content, in a virtual realm free of physical constraints. 

In between these two extremes of current robot prowess is a large space of tasks that require flexible behavior in uncontrolled physical environments. A rundown of major industries—food, housing, healthcare, retail, transportation, tourism—reminds us how much of our lives still takes place in the messy world. A fundamental challenge of behaving effectively under such conditions is dealing with uncertainty. 

Even just figuring out what is happening in the world at any given moment requires resolving innumerable ambiguities in sensory data. Our eyes and ears give us partial information about what’s out there; our brains fill in the rest. Even though perception feels effortless to us, if you’ve ever looked at an ambiguous image like the duck-rabbit or old woman-young woman , you’ll know that our brains are doing a lot of interpretive work under the hood. Robots will have to do the same to understand what is going on in novel, changing environments. Current computer vision systems in self-driving cars still make mistakes humans never would. 

Making a guess about what’s happening is one thing; deciding what to do about what’s happening is quite another. But the challenge of handling uncertainty is at the heart of decision making, too. In the course of our jobs, we often have to make quick decisions using incomplete information. How should I handle this customer who just snapped at me? Should I perform emergency surgery on this patient? We often simply cannot get all the information we wish we had in order to decide the best course of action, and robots won’t be able to either, despite their vast access to stores of human knowledge. In many real-world decision scenarios, the most critical information is specific, contextual, and unavailable. 

Robots will likely get better and better at handling uncertainty in perception, decision making, and action. But at the end of the day — barring a wholesale robot takeover — the jobs robots do will be the jobs we let them do. For this reason humans will have to trust robots to make good decisions in the face of all this uncertainty. One interesting possibility is that robots may be able to tell us about their own levels of confidence in their judgment calls — a process that requires metacognition, or thinking about one’s own thoughts. The better their metacognition, the more we’ll trust them. And the sooner we’ll be able to step in when they’re out of their depths. ____________________________________________________________________________________________________________

Interested in learning more? Join Arts & Sciences for the 2023 Gitner Family Lecture , “What does it mean to be human in the world of AI?” with Arts & Sciences faculty members  Margarita Guillory , associate professor of religion;  Rachell Powell , professor of philosophy;  Rachel Denison , assistant professor of psychology & brain sciences; Pascual Restrepo , associate professor of economics.

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Will Robots Take My Job? The Future Of Automation.

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There are dozens of action and horror films all focused on artificial intelligence, and what happens when robots take over. While this makes for great entertainment, some people take this idea to heart and are terrified of robots taking over their work.

This slight panic by some mirrors what we know from history; when electricity was discovered and mass produced, everyone worried about candlestick makers. When cars became popular, carriage makers were worried they would be out in the cold.

Technology advancements do sometimes mean that certain jobs become less needed over time, but that doesn’t mean entire industries are just out of luck. In fact, research shows that automation doesn’t reduce the number of jobs available, and it can even add more jobs to the workforce.

Many of these jobs are in the information technology industries. If you’re considering going into IT, now is an ideal time to get the education you need to pursue that career. AI and tech advancements are only going to keep moving forward. As new technology is created, more jobs are needed. Having an IT degree will mean you’re ready to be part of these advancements and can feel secure in your future.

Currently many of these new exciting AI advancements haven’t trickled into everyday life. For example, self-driving cars are an exciting and developing technology, but you can’t buy one and likely won’t be able to anytime soon. If being involved in these current developments sounds exciting to you, it could be the perfect time to get an IT degree and move into a field where you’d be on the cusp of all the technology advances ahead.

With new technology, some jobs eventually do become less necessary (there aren’t many carriage makers today). But change is the only constant in the world. And ultimately, technology advancements of the past and present are hugely beneficial for society.

Jobs lost to automation.

It’s true that over time, there will be some jobs that are lost to automation. These job losses will happen slowly so you shouldn’t expect to be out of the workforce tomorrow. And in the past, as future automation slowly takes over tasks, workers are able to transfer their skills easily to other industries or lines of work.

Travel agent.

With online and digital options, the Bureau of Labor Statistics says that the number of travel agents will decline by 11% by 2024. Many people already use online apps and websites to help them plan their entire trips, and as AI continues to get smarter, people will be able to explain exactly what kind of vacation they are looking for, and the machine can factor in all the variables.

Assembly line work.

With increased robotics tools and programs, there are already 5 million fewer manufacturing jobs today than there were in 2019. Experts expect this number will continue to decline as more robotics inventions are put into factories around the world. Humans will still be needed to run and operate these machines, but actual assembly work is likely to decline.

Customer service.

You may already be familiar with the bots that you often deal with as part of customer service interactions. As AI continues to get more advanced, these customer interactions will be more sophisticated and prevalent. A new report says that customer service and customer interaction jobs could decrease by 20% in the next decade.

Medical lab workers.

While future automation will likely never take the place of doctors, there are some medical tasks that could be automated. The Bureau of Labor Statistics says that there is likely to be a 14% decrease in medical lab workers by the year 2024. From running lab tests to helping diagnose patients and do research, automated programs can help increase accuracy and consistency in the medical field.

Postal workers.

Postal workers are likely to be hit the hardest when it comes to automation takeover. The BLS expects there to be a 38% drop in postal workers by 2024. Increased robotics advancements allow for sorting, packaging, and delivery to be automated, and less human interaction is needed.

Why you shouldn't be afraid of robots taking your job.

While there are skills that will be less needed thanks to technology, future automation will create many jobs and won’t touch many industries. If you’re hoping to make sure your job and career is safe from automation, there are some industries you can begin going to school for and be prepared.

Nervous about a potential career change? We have a whole guide on how to navigate this process. WGU makes career changing easy with a complete flexible, online education. You can continue to work at your current place while getting your degree and preparing for a new career. Our competency-based education means that you can move quickly through material once you understand it.

You don’t need to be afraid of robots taking your tasks anytime soon, and especially if you work in industries that are extremely hard to automate.

Jobs safe from automation.

No matter how advanced machines get, we will always need teachers to manage classrooms, provide kindness and empathy for children, and go in-depth when students don’t understand the concepts. There isn’t a machine that can offer students the same attention that people can.

Even at schools like WGU that are online, there are faculty members and Program Mentors to provide the crucial human interaction you need every step of the way. Tools like computers and other technical advancements are a huge help to teachers as they work to provide better learning opportunities for students. But teachers will never be able to be replaced by robots.

If you’re interested in getting into teaching , WGU is a great option. Flexible, completely online, and competency based education means that you can get into a teaching career pain-free.

Automation will continue to bring help and advancement to the medical field, but nurses and doctors will likely never be able to be completely replaced by machines. The way that nurses connect with patients, offer them comfort and support, and make them feel understood is vital to patient satisfaction.

You have the option to utilize WGU to become a nurse and further your career in an industry that will stand the test of time. Our rigorous coursework will ensure that you’re ready to work in the nursing field, prepared for all the things that are likely to come your way.

Hairdressers.

While automation is impacting many industries that are directly related to customer service, hair stylists and makeup artists are not among that group. These kinds of jobs require the human eye to be done right. Software and machines that have been created to try to do this work have largely failed, meaning that hairdressers are likely safe from automation fears.

Social workers and therapists.

Jobs that revolve around helping people and working with their mental health and mind will likely never be replaced by automation. People need that human interaction and understanding to benefit from these services. Social workers and therapists are highly trained to have the empathy and listening abilities that robots will never be able to acquire. Because of this, these jobs will never be a good fit for automation.

While artificial intelligence, machine learning, and new technology may be a little overwhelming, you really don’t need to worry that the robots are going to take over. There are many industries that will benefit, especially IT. The IT college at WGU can help you be prepared for the explosion of jobs and opportunities that will come to IT professionals as automation continues to grow. There will be a high demand for people to program robots, develop new software and security systems, and more. WGU can help you get an IT degree and get in on the action. And if you’re in an industry that could be getting less valuable, or if you’re wanting to get into an industry that will likely never become automated, WGU can help!

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Will robots take your job before you even graduate?

With each passing year, parents are getting more worried about how their children will fare once it’s time to take that step from school to the workforce.

They have good reason to fret. Some 17 million Americans under age 30— about one third of the under-30 population—are saddled with student debt. Many are worried about their career prospects despite having invested—heavily, in some cases—in education.

The cost of college is being hotly debated. But it’s only one aspect of an even bigger issue: The automation of many entry-level roles will make it even harder for young people to gain traction in the working world.

The road from education to employment is full of more disconnects than ever. Research from the McKinsey Global Institute finds that workers from ages 18 to 34 hold almost 40%—or 14.7 million—of the US jobs that could disappear due to automation in the next decade. This creates a challenge for young people, both for those trying to make a living in the service sector and for college graduates aiming to get onto the professional track.

Two-thirds of the job losses for young people could occur in food, hospitality, or retail. These industries provide a crucial opportunity for more than 30 million Americans overall to bring home a paycheck—and workers under 34 years old make up half or more of the nation’s wait staff, hotel receptionists, and fast food workers. These types of roles build valuable soft skills like communication, punctuality, and customer service, and they also provide that all-important first line on a resume that can propel people onward and upward. The gig economy has created some alternative options such as driving and delivery, but those types of on-demand services are scarce outside of urban areas.

One-third of the automation-related job losses for young people could occur in white-collar jobs, including entry-level roles in accounting, finance, human resources, and administration. In the legal profession, for example, AI can handle document review and case law search—not a favorite task for junior attorneys, perhaps, but one that provides valuable immersion and learning. Actuaries have traditionally spent their early years crunching numbers to assess risk. Now AI is outperforming humans at these tasks.

This means aspiring young professionals will need to enter the labor force in higher-level roles. But employers have been saying for years that too many new hires, even those with college degrees, are not work-ready.

The jobs of the future will demand even more in the way of digital skills, people skills, creativity, communication, and critical thinking.

Companies can help to address this issue by offering more paid internships and apprenticeships to prepare students to hit the ground running after graduation. The apprenticeship model, traditionally associated with skilled trades, is now being adopted by companies such as IBM, Bank of America, and investment and insurance firm The Hartford.

As technology changes, we need to change apace. The US education system has not evolved as quickly as the new world of work. It is not equipping students enough of the technical skills nor the soft skills they will need in the workforce. And there are few road maps available for the majority of young people who are not headed to college.

Back to high school

A systematic solution could be to expand student access to a wider range of post-secondary education and training programs, or blended schools that combine high school diplomas with associates degrees.

When technology took a leap forward in the early 1900s, shifting the economy from agriculture to manufacturing, the United States responded by making high school universal and compulsory.

The “high school movement” eventually made Americans the best-educated workforce in the world and set the stage for the GI Bill to boost college attendance after World War II. The wave of technological progress we’re facing today calls for a similar raising of the bar for how the young generation attains education.

In nearly every field, workers will increasingly need access to some type of postsecondary training. In addition to expanding access to four-year universities, we need a wider variety of options, including community college, apprenticeships, online courses, vocational schools, and credential programs.

Some initiatives promise progress in this direction. In 2014, Tennessee became the first state to cover the cost of community college or technical training for residents—and since then, more than a dozen states and some cities, like Chicago, have followed suit. Some of these programs, such as IBM’s P-Tech schools, the Dallas County Promise, and the Detroit Promise Path, provide business mentors to help young people through the job application process and academic life.

This can be critical support for participants who are the first in their families to go beyond high school. Early evidence suggests these programs have increased the share of young people attending and completing community college.

Employers have the best view on emerging jobs and the new sets of skills required. Some are working closely with community colleges, online educators, and universities to design relevant curricula to create a more robust talent pipeline. Advanced manufacturing companies in particular have made an effort to get out in front with community college partnerships to develop the specialized skills they need to fill the thousands of open positions in the US manufacturing market.

Northrop Grumman has worked with the University of Maryland to create a certificate in cybersecurity , a growing field with too few graduates. Others are participating in efforts to standardize credentials. Google has worked with Coursera, an online education provider, to create a five-course certificate to prepare workers for IT support positions. That certificate is now recognized by dozens of major employers across the US.

These are all positive steps. But now these efforts need to be scaled up. The United States needs to focus on upgrading its workforce skills—and we definitely can’t afford to let the disappearance of entry-level jobs leave millions of young people adrift.

This article appeared first in Quartz

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Employment Research

Will Robots Take Our Jobs?

Artificial Intelligence, robots, and automation are often discussed in the media as ways to reduce the labor force—as "job eliminators." In the Page One Economics essay Will Robots Take Our Jobs? , author Scott Wolla explores the history of technological advancements in automation, from the Industrial Revolution to the modern era, and whether or not a "Robot Apocalypse" is really in the cards.

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Rise of ai: are robots taking our jobs | lynn wu, may 16, 2023 • 21 min listen.

Professor Lynn Wu discusses who should be worried about robots in the workforce.

Listen to the podcast.

The robots are coming, whether employees are ready or not. Wharton’s Lynn Wu explains why the next workplace revolution requires firms to rethink everything, especially the traditional career ladder.

Are Robots Taking Over the World — and Our Jobs?

Dan Loney: What sparked your interest in studying how robots are starting to change employment?

Lynn Wu: Honestly, this one has the easiest motivation. At the time, there were so many articles in the press and academia about how robots are going to take over all our jobs and the impending robocalpyse. There were already policy pieces on robot taxes. Bill Gates promoted it. Bill DiBlasio made it a central piece of the presidential campaign back in 2020. And Bernie Sanders had also proposed some kind of a robot tax.

I think it’s really important that we understand what’s going on and have some real, concrete evidence at the firm level to see whether firms actually do lay off people en masse after robot adoption. There were only industry and country-level evidence at the time, and it is really important to study at the firm level because countries and industries do not adopt robots. Whatever the positive/negative effects that you find depends on whether firms that adopt actually laid off people, or is it coming from firms that do not adopt? These facts are very difficult to observe when we are looking at a macro level, at the industry and country level.

Loney: Why do you think these narratives pop up? They have really taken hold with some people over the last few years.

Wu: I think it’s not just the last few years. I’ve seen this trend going on every time we see a potentially transforming technology that could affect work. We see that back in the day of the Industrial Revolution with the Luddite movement. Those people literally burned the looms that automated the process of making garments. It turns out that having these looms, which effectively accelerate the process of making garments, did not make these people lose their jobs. We see an increase in employment for people who can effectively use new automated, mechanical tools like looms. You see the same thing with Excel. It was going to replace accountants. It never happened.

Every time we see a technology that could potentially change the way we work, change our lives, there’s a human visceral reaction to it. We tend to overestimate what the technology can do and think, “Oh my gosh. I’m going to lose my job now.” It’s really important to take it back and think about, “What exactly is that technology doing?” before we make any strong decisions, especially the policymakers and at the policy angle. What are we going to do about this? What are workers going to do about it? What are firms going to do about it?

Who Will Be Impacted by Robot Workers?

Loney: Tell us a little bit about the research that you’re doing in this area to try to get a better grasp on what’s been taking place here.

Wu: Our work is first to study robot adoption on employment and its effect at a firm level. I want to emphasize at the firm level, because only at a firm you can see what happens when firms adopt robots. Do they actually lay off people, or do they hire more people? And what happens to the firm that did not adopt? These kinds of effects can only be observed at the more micro level.

We used the data from our sister school in Canada, which has comprehensive data on robot import and export, which has a very good measure of robot adoption [at firms]. We also have very comprehensive data about their financial performance from their tax filings and surveys that the Canadian government mandated on various firm practices.

What we found is exactly the opposite of what people were expecting. Robots did not replace human workers. In fact, the robot adopters, or the firms that adopted robots, hired more people than it did before. So, how do we reconcile the evidence that we see sometimes at an industry level and the country level that there is a negative effect of robots on employment? It turns out it’s not the robot-adopting firms that are hurting employment. It is the firms that did not adopt robots that are losing the competition. They’re not as competitive as before, and they had to lay off people because they’re losing the market share.

It’s a very different story than the popular press thinking that we’ve got to tax robots to preserve human work. Taxing the firm that got the robots turned out to be the exactly wrong thing to do in this case. That’s one major finding. We’re basically saying that we have to look at these phenomena in greater detail to understand what’s going on here. Without this kind of firm-level measurement and technology measurement, we wouldn’t be able to know this important distinction.

We also have found other effects on employment. It’s not the number that matters. We always think that robots are taking over our jobs, and that’s not the case. We see skill effects. Specifically, robot-adopting firms hired more high-skill workers, many more low-skill workers, at the expense of middle-skilled workers. I define high-skill workers as those with college education. Low-skill workers are the people who barely finished high school. And middle-skill workers are people with high school degrees or associate degrees, who had some kind of more advanced work-related trainings. It’s these middle-skill workers who are being decimated by robots, and that is a big problem.

We also show that managerial, supervisory work has also been decimated by robots. If you look at the average number, it looks great. Employment has gone up. But hollowing out the middle-skill work, hollowing out the supervisory work is a big problem because now the career ladder is broken. How do we incentivize, how do we train, where did the middle-skill work go? You can’t expect all people to get college degrees and become programmers or robot technicians or producers.

Loney: Does the adoption of robots change the dynamics of the work being done by those companies or their success?

Wu: Absolutely. Just adopting the robot itself is not going to be enough. You have to be able to learn how to manage robots in a way that accelerates performance, increases your worker productivity. Let me give you a real-life example from a repair facility at a U.S. electronics firm. They actually experienced a dramatic improvement in their ability to observe productivity after robots were implemented. At this repair facility, they fix electronics. And because robots don’t get physically tired when performing this kind of repetitive task, they can do this job more consistently than humans. As a result, the variance in production has gone down.

This allowed managers to clearly observe individual employees’ behaviors. They were able to see that many human employees were following irregular patterns of being very productive in the morning, compared to the afternoon. But then they do more repairs at later hours, as they were cramming their work at the end of the day.

Interestingly, after robots are implemented, they are able to track the individual employee’s productivity more easily for two reasons. First, the type of errors robots make are very different from that of humans. Because of the differentiating errors, it makes it easier for us to figure out which one is which. Robots are more likely to make consistent errors compared to humans, again making human errors easier to identify.

Robots also provide precise data about their own performance, which made it easier to isolate both the positive and negative side of performance changes caused by human behaviors. This data-generating capability allows managers to monitor their productivity much better than before and detect weaknesses in the production processes.

So, it’s not just adopting the robot itself. It’s all the other things they’ve done to detect and figure out the production process. In this case, the manager wasn’t even aware of this cramming behavior described earlier until after they adopted robots to observe these processes. And as a result, they changed a lot of their work processes along the way to further reduce the errors once humans and robots were working together. Overall error rates in the facility have dramatically improved. This is an example of how robots can be used to improve productivity and how to manage the workforce appropriately to capture, to further increase the effect of the robots.

The Effects of Robots and Generative AI on the Workforce

Loney: How are careers going to be impacted by the further adoption of robots? I’ll play that off of the comment you made earlier about the impact being significant on middle managers. That’s an important stepping stone in a person’s professional career. If we have fewer of those, the structure of leadership changes.

Wu: That’s a really important point, and it’s a really hard problem to solve. In my research I mentioned earlier, because you have many more lower-skill workers, many more higher-skill workers at the expense of middle-skill work, the type of manager you need is going to be very different. These managers need to understand how a robot works to be able to test these hypotheses. Just like the example I gave about repair facilities. They need to fundamentally change the way they work, fundamentally change the way they monitor and reward and hire employees.

There are two effects. No. 1, we simply need fewer managers and supervisors than before. Because you can manage many standardized workers and lower-skilled workers at the same time, as opposed to higher-skill or middle-skill workers. Furthermore, the type of management skills you need is going to be different. So, it’s a big problem. Now, we have no middle-skill work, or less of them, and much fewer supervisory work. Where do people go? The entry-level work is supposed to be a stepping stone to move up in the career hierarchy, and now you can’t move up anymore. You’ve got middle-skill, you’re gone. You go to the supervisors, and you are gone. Then it’s very hard to move up to high-skill work, right? That requires extensive training. This is a very big challenge for managers, where you have to think about how to build a new career ladder now. The existing one may not work.

That’s why you see lots of unionization going on in the workforce, from Amazon warehouses to Starbucks, everywhere. It’s because you can’t use a career ladder as a motivating force for people to work at an entry-level job at lower pay in exchange for future career advancements. How do you build that back? If firms do not build it back, then we’re going to see unions becoming more of a mainstay in our society again.

Loney: If we’re expecting that we’re going to see more companies adding robotics into their operational structure, does that answer the question about whether or not companies can even avoid having robots in the first place?

Wu: The moment one firm adopts, they become more effective and more competitive. That means everyone else, in order to stay competitive in the marketplace, has to adopt these new technologies. Even the biggest, very profitable, very innovative firms have to catch up. We see in Google’s case, when Microsoft released ChatGPT, Google is scrambling to do the same thing, incorporating every aspect of that technology in their products. That is something that firms just cannot avoid. The Luddites burning the loom is not going to work in this case. Probably never would work.

Loney: How will the advancement of ChatGPT play a role in the corporate structure as we move forward?

Wu: I think the robot thing is the tip of the iceberg. ChatGPT, the large language model, is going to accelerate that process tremendously. Because if you think about what ChatGPT and these large language models are targeting, it’s exactly that middle-skill work. And because these technologies are really good, when you are an expert in that field already, it accelerates your work. But who was doing that work for you before, if you were a senior person? It’s people below you. Now, you can use the ChatGPT to do a lot of it for you. So, it’s precisely that middle-skill work that is being targeted. And that’s exactly the same effect of the robots. There was a recent paper by OpenAI and also our colleagues at Wharton that showed that the skill set that’s being targeted by ChatGPT is middle-skill programming jobs and writers.

Loney: Does the longer-term outlook for middle-skill jobs look very bleak at this point?

Wu: I think existing middle-skill work is in trouble. But new middle-skill work will be created. For example, there’s prompt engineering, something you’ve never heard of until maybe a few months ago. These engineers are literally trying to make ChatGPT do what it’s supposed to do. We’ll need robot technicians to fix the robots, process engineering to observe processes, and see where robots can be used in the production processes. All these things are probably going to be new tasks. Over time, these new tasks will evolve into new career opportunities, just like 20 years ago when there was no social media manager, right? That’s a new job that was created as a result of the technologies.

But the important problem is not necessarily the new jobs that will be created. I guarantee you that new jobs and new tasks will be created. It’s the speed at which we can retrain the existing workforce to leverage that. The last time we had this kind of dramatic technology change was probably the Industrial Revolution, the steam engine being replaced by electricity. That took 30, 40 years to complete. And that means existing managers retire, the existing workforce retires. This time, we are not going to have a 30, 40-year horizon. We’re going to have a five, 10-year horizon. How you retrain that existing workforce is going to be a huge challenge for everyone.

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Will robots take your job? Humans ignore the coming AI revolution at their peril.

Robots have transformed industrial manufacturing , and now they are being rolled out for food production and restaurant kitchens . Already, artificial intelligence (AI) machines can do many tasks where learning and judgment is required, including self-driving cars , insurance assessment , stock trading , accounting , HR and many tasks in healthcare . So are we approaching a jobless future, or will new jobs replace the ones that are lost?

According to the optimistic view , our current phase of increasing automation will create new kinds of employment for those who have been made redundant. There is some historical precedent for this: Over a hundred years ago, people feared that the automobile revolution would be bad for workers. But while jobs related to horse-drawn carriages disappeared, the invention of the car lead to a need for automobile mechanics; the internal combustion engine soon found applications in mining, airplanes and other new fields.

The difference, however, is that today’s AI technology aims to replace the human mind, not simply make industry more efficient. This will have unprecedented consequences not predicted by the advent of the car, or the automated knitting machine.

The effects of AI technology on society cannot be measured purely based on productivity.

The effects of AI technology on society cannot be measured purely based on productivity. Modern civilization needs employment — not simply for our livelihoods, but for our emotional wellbeing. If AI increases to the point that a significant portion of workers are suddenly unemployed, this research suggests this could have a profound impact on our social well-being — even with the guaranteed minimum income that is being proposed by leading economists as a way to soften the effects of an increasingly jobless society.

So let’s see where we stand. Automation technologies are already impacting many different aspects of the restaurant industry , and it is anticipated that they will put pressures on job availabilities for the food system workers . Self-driving cars will perhaps have an even greater impact on general employment, although they have a greater challenge in winning public trust . Still, many companies have already received permits to test self-driving car technology . General Motors has announced that it is ready to mass produce self-driving cars.

So delivery and truck drivers, professors, brokers in the investment business , and accountants will likely become redundant, but so will lawyers, if a new start-up has its way . Meanwhile, information technology is already having a great impact on the education industry. Due to the challenges from online courses, and the high costs of running centralized campuses with expensive infrastructure, Harvard Business School professor Clayton Christensen has suggested that half the colleges and universities in the U.S. will close in the next couple decades . (And it’s not just in the U.S. either: The Indian Council for Technical Education (ICTE), which regulates engineering colleges in one of the world’s fastest growing economies, recently announced that 800 colleges will be shut down .)

A November 2017 report from global management consulting firm McKinsey on the effects of automation on jobs, skills and wages for the period ending in 2030 estimates that fully 50% of current work activities are automatable by technologies that have already been tested and found effective. The report predicts that in 60 percent of occupations, at least one-third of activities could be automated. The report expects 400 million to 800 million people could be displaced by automation in the next 12 years, creating a challenge potentially greater than past historic shifts, at least in the modern era.

One way of meeting the challenge of automation is by retraining the workforce. But this retraining will not simply be the replacing of one set of skills for another . It used to be that users of a technology needed to know how it worked; now many consumer machines are too complex to be repaired.

Indeed, very few people need to know how the computer systems in a robot work; they just need to be able to interpret sensor readings and error messages. Even a car mechanic uses a computer to identify what system is not working properly and needs replacement.

In other words, the number of jobs involving routine skills — both physical and cognitive — is shrinking . Increasing automation at factories is rapidly replacing workers at factories, even in low-wage countries like China . With robots and AI machines doing most of the work, the demand for specialized training related to the tasks where humans have been made redundant will go down. We will still need engineers, but not as many as in the past.

Tech advances can be spurned by a society at its peril — rival nations with less to lose will press ahead.

The remaining jobs will likely involve fewer routine tasks . We would need more generalized education so that it is possible for workers to be trained in short order for different tasks in in a highly automated labor market . Given that colleges and universities have institutional inertia, this challenge is not being addressed with any priority.

We live in an age of unprecedented worldwide migration, where most migrants are finding employment in unskilled jobs . Since these jobs will likely become most at risk as the use of automation advances , societies must also prepare for the challenges of retraining and educating this unique segment of the workforce.

Some scientists and tech titans are calling for the regulation of artificial intelligence machines . But the evolution of technology has its own momentum and technological advances can be spurned by a society only at its peril — rival nations with less to lose will press ahead. As a result, machines will continue to replace humans at jobs. The challenge is to be cognizant of the costs and risks, so that one can develop strategies to meet the future with resilience.

Subhash Kak is Regents Professor of electrical and computer engineering at Oklahoma State University, Stillwater. He Tweets at @subhashkak1.

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The future of robots in the workplace: The impact on workers

For this 2015 working paper for the National Bureau of Economic Research, researchers tested economic models to predict how much smart machines may eventually replace human labor.

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by Rachael Stephens, The Journalist's Resource August 11, 2015

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Not so long ago the idea of robots patrolling neighborhoods or caring for children was the domain of science fiction. While robots have yet to replace police and daycare workers, technology has become so advanced that automated systems are taking on greater roles in society and the workplace.

Academic research has explored the diverse impacts of technology on employment — what happens when jobs shift elsewhere or when they’re atomized through Internet-enabled technologies. A 2015 study from Uppsala University and the London School of Economics looked the economic impact of industrial robot use in 17 countries from 1993 to 2007 and found that robots contributed to the economy, partly by helping humans do their work better.

A 2015 study for the National Bureau of Economic Research, “Robots Are Us: Some Economics of Human Replacement,” uses an economic model to explore the potential impact of increased workplace automation. The authors — Seth Benzell, Laurence Kotlikoff and Guillermo LaGarda of Boston University and Jeffrey Sachs of Columbia University — develop a model that calculated the initial and final states of an economy with two inputs to production (capital and code) and two types of workers (low-tech and high-tech). They then tested the impact that variations on workplace conditions and industrial policies will have on the economy.

Key findings of the study include:

• Increased workplace automation could produce both “economic misery” and prosperity. Specifically, three consequences were found to be highly probable: “A long-run decline in labor share of income (which appears underway in OECD members), tech-booms followed by tech-busts, and a growing dependency of current output on past software investment.”
• As technology improves and its use in the workplace expands, the demand for high-tech workers falls. At the end of the simulation, nearly 68% of high-tech workers end up in the service sector, earning approximately 14% less than they did previously.
• As high-tech workers return to the service sector, the wages of low-tech workers rise 41%, then fall to 17% above the initial steady state wage — higher than the initial state, but lower than during the “boom.” In effect, the drop in high-tech worker compensation generates a boom-bust in low-tech worker compensation.
• In the long run, national income increases in the short term, but then falls by 17%.
• Adding a “positive tech shock” — a technical innovation that increases reduces costs or increases productivity — to the model causes a 13% short-term increase in national income, but national income then falls again by 28%, ending up lower than in the initial steady state.
• During a positive tech shock, labor’s share of national income also rises in the short-term but then falls, from 75 to 57%.
• The positive tech shock also causes consumption of goods to decrease by 28%, and the price of services to decrease by 43% as compared to before the technological breakthrough.
• Some public policy options were found to reduce the negative long-term impacts on workers and the economy. For example, a high national saving rate mitigates the impacts of a positive tech shock, resulting in workers earning very near their initial steady state wages (rather than far less), but able to consume 20% more with those wages than they were before the shock.
• Some policies to mitigate the negative effects were found to be likely to backfire, including requiring that all code be open source or restricting the labor supply — these solutions were found to further hurt wages, savings and capital stock.

The authors conclude: “Our simple model illustrates the range of things that smart machines can do for us and to us. Its central message is disturbing. Absent appropriate fiscal policy that redistributes from winners to losers, smart machines can mean long-term misery for all.”

Keywords: technology, artificial intelligence, AI, robotics

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Rachael Stephens

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• Future of Work

Robots were supposed to take our jobs. Instead, they’re making them worse.

The robot apocalypse is already here, it just looks different than you thought.

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The robot revolution is always allegedly just around the corner. In the utopian vision, technology emancipates human labor from repetitive, mundane tasks, freeing us to be more productive and take on more fulfilling work. In the dystopian vision, robots come for everyone’s jobs, put millions and millions of people out of work, and throw the economy into chaos.

Such a warning was at the crux of Andrew Yang’s ill-fated presidential campaign, helping propel his case for universal basic income that he argued would become necessary when automation left so many workers out. It’s the argument many corporate executives make whenever there’s a suggestion they might have to raise wages: $15 an hour will just mean machines taking your order at McDonald’s instead of people, they say. It’s an effective scare tactic for some workers.

But we often spend so much time talking about the potential for robots to take our jobs that we fail to look at how they are already changing them — sometimes for the better, but sometimes not. New technologies can give corporations tools for monitoring, managing, and motivating their workforces, sometimes in ways that are harmful. The technology itself might not be innately nefarious, but it makes it easier for companies to maintain tight control on workers and squeeze and exploit them to maximize profits.

“The basic incentives of the system have always been there: employers wanting to maximize the value they get out of their workers while minimizing the cost of labor, the incentive to want to control and monitor and surveil their workers,” said Brian Chen, staff attorney at the National Employment Law Project (NELP). “And if technology allows them to do that more cheaply or more efficiently, well then of course they’re going to use technology to do that.”

Tracking software for remote workers, which saw a bump in sales at the start of the pandemic , can follow every second of a person’s workday in front of the computer. Delivery companies can use motion sensors to track their drivers’ every move , measure extra seconds, and ding drivers for falling short .

Automation hasn’t replaced all the workers in warehouses, but it has made work more intense, even dangerous , and changed how tightly workers are managed. Gig workers can find themselves at the whims of an app’s black-box algorithm that lets workers flood the app to compete with each other at a frantic pace for pay so low that how lucrative any given trip or job is can depend on the tip, leaving workers reliant on the generosity of an anonymous stranger. Worse, gig work means they’re doing their jobs without many typical labor protections.

In these circumstances, the robots aren’t taking jobs, they’re making jobs worse. Companies are automating away autonomy and putting profit-maximizing strategies on digital overdrive, turning work into a space with fewer carrots and more sticks.

A robot boss can do a whole lot more watching

In recent years, Amazon has become the corporate poster child for automation in the name of efficiency — often at the expense of workers. There have been countless reports of unsustainable conditions and expectations at Amazon’s fulfillment centers. Its drivers reportedly have to consent to being watched by artificial intelligence, and warehouse workers who don’t move fast enough can be fired .

Demands are so high that there have been reports of people urinating in bottles to avoid taking a break. The robots aren’t just watching, they’re also picking up some of the work. Sometimes, it’s for the better, but in other cases, they may actually be making work more dangerous as more automation leads to more pressure on workers. One report found that worker injuries were more prevalent in Amazon warehouses with robots than warehouses without them.

Amazon is hardly the only company that uses automation to keep tabs on workers and push them to do more. In 2020, Josh Dzieza at the Verge outlined the various ways artificial intelligence, software, and machines are managing workers at places such as call centers, warehouses, and software development shops. He described one remote engineer in Bangladesh who was monitored by a program that took three pictures of him every 10 minutes to make sure he was at his computer, and a call center worker who learned to say “sorry” a lot to customers in order to meet an artificial intelligence-based empathy monitor. A web of technologies has enabled the management of every minute of the working day.

“It would have been prohibitively expensive to employ enough managers to time each worker’s every move to a fraction of a second or ride along in every truck, but now it takes maybe one,” Dzieza wrote. “This is why the companies that most aggressively pursue these tactics all take on a similar form: a large pool of poorly paid, easily replaced, often part-time or contract workers at the bottom; a small group of highly paid workers who design the software that manages them at the top.”

A 2018 Gartner survey found that half of large companies were already using some type of nontraditional techniques to keep an eye on their workers, including analyzing their communications, gathering biometric data, and examining how workers are using their workspace. They anticipated that by 2020, 80 percent of large companies would be using such methods. Amid the pandemic, the trend picked up pace as businesses sought more ways to keep tabs on the new waves of workers working from home.

This has all sorts of implications for workers, who lose privacy and autonomy when they’re constantly being watched and directed by technology. Daron Acemoglu, an economist at MIT, warned that they’re also losing money. “Some of these new digital technologies are not simply replacing workers or creating new tasks or changing other aspects of productivity, but they’re actually monitoring people much more effectively, and that means rents are being shared very differently because of digital technologies,” he said.

He offered up a hypothetical example of a delivery driver who is asked to deliver a certain number of packages in a day. Decades ago, the company might pay the driver more to incentivize them to work a little faster or harder or put in some extra time. But now, they’re constantly being monitored so that the company knows exactly what they’re doing and is looking for ways to save time. Instead of getting a bonus for hitting certain metrics, they’re dinged for spending a few seconds too long here or there.

The problem isn’t technology itself, it’s the managers and corporate structures behind it that look at workers as a cost to be cut instead of as a resource.

“A lot of this boom of Silicon Valley entrepreneurship where venture capital made it very easy for companies to create firms didn’t exactly prioritize the well-being of workers as one of their main considerations,” said Amy Bix, a historian at Iowa State University who focuses on technology. “A lot of what goes on in the structure of these corporations and the development of technology is invisible to most ordinary people, and it’s easy to take advantage of that.”

The future of Uber isn’t driverless cars, it’s drivers

Uber’s destiny was supposed to be driverless.

In 2016, former CEO Travis Kalanick told Bloomberg making an autonomous vehicle was “basically existential” for the company. After a deadly accident with an autonomous Uber vehicle in 2018, current chief executive Dara Khosrowshahi reiterated that the company remained “ absolutely committed ” to the self-driving cause. But in December 2020 and after investing $1 billion, Uber sold off its self-driving unit . A little over four months later, its main competitor, Lyft, followed suit . Uber says it’s still not giving up on autonomous technology , but the writing on the wall is clear that driverless cars aren’t core to Uber’s business model, at least in the near future.

“Five or 10 years from now, drivers are still going to be a big piece of the mix on a percentage basis [of Uber’s business], and on an absolute basis, they may be an even bigger piece than they are today even with autonomous in the mix because the business should get bigger as both segments get bigger,” said Chris Frank, director of corporate ratings at S&P Global. “In addition, drivers will need to handle more complex conditions like poorly marked roads or inclement weather.”

In other words, they’re going to need workers to make money — workers they would very much like not to classify as such.

Gig economy companies such as Uber, Lyft, and DoorDash are fighting tooth and nail to make sure the people they enlist to make deliveries or drive people around are not considered their employees. In California last year, such companies dumped $200 million into lobbying to pass Proposition 22 , which lets app-based transportation and delivery companies classify their workers as independent contractors and therefore avoid paying for benefits such as sick leave, employer-provided health care, and unemployment. After it passed, a spokesman for the campaign for the ballot measure said it “represents the future of work in an increasingly technologically-driven economy.”

It’s a future of work that might not be pleasant for gig workers. In California, some workers say they’re not getting the benefits companies promised after Prop 22’s passage, such as health care stipends. Companies said that workers would make at least 120 percent of California’s minimum wage, but that’s contemplating the time they spend driving only. Before the ballot initiative was passed, research from the UC Berkeley Labor Center estimated that it would guarantee a minimum wage of just $5.64 per hour.

Companies say they’ve been clear with drivers about how to qualify for the health care stipend, which is available to drivers with more than 15 engaged hours a week (in other words, if you don’t have a job and are waiting around, it doesn’t count). In a statement to Vox, Geoff Vetter, a spokesperson for the Protect App-Based Drivers + Services Coalition, the lobbying group that championed Prop 22, said that 80 percent of drivers work fewer than 20 hours per week and most work less than 10 hours per week, and that many have health insurance through other jobs.

Gig companies have sometimes been cagey about how much their workers make, and they’re often changing their formulas. In 2017, Uber agreed to pay the Federal Trade Commission $20 million over charges that it misled prospective drivers about how much they could make with the app. The FTC found that Uber claimed some of its drivers made $90,000 in New York and $74,000 in San Francisco, when in reality their median incomes were actually $61,000 and $53,000, respectively. DoorDash caused controversy over a decision to pocket tips and use them to pay delivery workers, which it has since reversed.

Even though Uber is charging customers more for rides in the wake of the pandemic, that’s not directly being passed onto their drivers. According to the Washington Post , Uber changed the way it paid drivers in California soon after Prop 22 passed so that they were no longer paid a proportion of the cost of the ride but instead by time and distance, with different bonuses and incentives based on market and surge pricing. (This is how Uber does it in most states, but it had changed things up during the push to get Prop 22 passed.) Uber’s CEO pushed back on the Post story in a series of tweets , arguing that decoupling driver pay from customer fares had not hurt California drivers and that some are now getting a higher cut from their rides.

In light of a driver shortage, Uber recently announced what it’s billing as a $250 million “driver stimulus” that promises higher earnings to try to get drivers back onto the road. The company acknowledges this initiative is likely temporary once the supply-demand imbalance works itself out. Still, it’s hard not to notice how quickly Uber and Lyft have been able to corner most of the ride-hailing app market and exert control over their drivers and customers.

“When a new thing like this comes on, there’s huge new consumer benefits, and then over time they are the market, they have less competition except one another, probably they’re a cartel at this point. And then they start doing stuff that’s much nastier,” said David Autor, an economist at MIT.

One of the gig economy’s main selling points to workers is that it offers flexibility and the ability to work when they want. It’s certainly true that an Uber or Lyft driver has much more autonomy on the job than, say, an Amazon warehouse worker. “People drive with Lyft because they prefer the freedom and flexibility to work when, where, and for however long they want,” a Lyft spokesperson said in a statement to Vox. “They can choose to accept a ride or not, enjoy unlimited upward earning potential, and can decide to take time off from driving whenever they want, for however long they want, without needing to ask a ‘boss’ — all things they can’t do at most traditional jobs.” The spokesperson also noted that most of its drivers work outside of Lyft.

But flexibility doesn’t mean gig companies have no control over their drivers and delivery people. They use all sorts of tricks and incentives to try to push workers in certain directions and manage them, essentially, by algorithm. Uber drivers report being bothered by the constant surveillance, the lack of transparency from the company, and the dehumanization of working with the app. The algorithm doesn’t want to know how your day is, it just wants you to work as efficiently as possible to maximize its profits.

Carlos Ramos, a former Lyft driver in San Diego, described the feeling of being manipulated by the app. He noticed the company must have needed morning drivers because of the incentives structures, but he also often wondered if he was being “punished” if he didn’t do something right.

“Sometimes, if you cancel a bunch of rides in a row or if you don’t take certain rides to certain things, you won’t get any rides. They’ve shadow turned you off,” he said. The secret deprioritization of a worker is something many Lyft and Uber drivers speculate happens. “You also have no way of knowing what’s going on behind there. They have this proprietary knowledge, they have this black box of trade secrets, and those are your secrets you’re telling them,” said Ramos, now an organizer with Gig Workers Rising.

Companies deny that they secretly shut off drivers. “It is in Lyft’s best interests for drivers to have as positive an experience as possible, so we communicate often and work directly with drivers to help them improve their earnings,” a Lyft spokesperson said. “We never ‘shadow ban’ drivers, and actively coach them when they are in danger of being deactivated.”

The future of innovation isn’t inevitable

We often talk about technology and innovation with a language of inevitability. It’s as though whenever wages go up, companies will of course replace workers with robots. Now that the country is turned on to online delivery , it can be made to seem like the grocery industry is on an unavoidable path to gig work. After all, that’s what happened with Albertsons . But that’s not really the case — there’s plenty of human agency in the technological innovation story.

“Technology of course doesn’t have to exploit workers, it doesn’t have to mean robots are coming for all of our jobs,” Chen said. “These are not inevitable outcomes, they are human decisions, and they are almost always made by people who are driven by a profit motive that tends to exploit the poor and working class historically.”

Chase Copridge, a longtime California worker who’s done the gamut of gig jobs — Instacart, DoorDash, Amazon Flex, Uber, and Lyft — is one of the people stuck in that position, the victim of corporate tendencies on technological overdrive. He described seeing delivery offers that pay as little as $2. He turns those jobs down, knowing that it’s not economically worth it for him. But there might be someone else out there who picks it up. “We’re people who desperately need to make ends meet, who are willing to take the bare minimum that these companies are giving out to us,” he said. “People need to understand that these companies thrive off of exploitation.”

Not all decisions around automation are ones that increase productivity or improve really anything except corporate profits. Self-checkout stations may reduce the need for cashiers, but are they really making the shopping experience faster or better ? Next time you go to the grocery store and inevitably screw up scanning one of your own items and waiting several minutes for a worker to appear, you tell me.

Despite technological advancements, productivity growth has been on the decline in recent years . “This is the paradox of the last several decades, and especially since 2000, that we had enormous technological changes as we perceive it but measured productivity growth is quite weak,” Autor said. “One reason may be that we’re automating a lot of trivial stuff rather than important stuff. If you compare antibiotics and indoor plumbing and electrification and air travel and telecommunications to DoorDash and smartphones or self-checkout, it may just not be as consequential.”

Acemoglu said that when firms focus so much on automation and monitoring technologies, they might not explore other areas that could be more productive, such as creating new tasks or building out new industries. “Those are the things that I worry have fallen by the wayside in the last several years,” he said. “If your employer is really set on monitoring you really tightly, that biases things against new tasks because those are things that are not easier to monitor.”

It matters what you automate, and not all automation is equally beneficial, not only to workers but also to customers, companies, and the broader economy.

Grappling with how to handle technological advancements and the ways they change people’s lives, including at work, is no easy task. While the robot revolution isn’t taking everyone’s jobs, automation is taking some of them , especially in areas such as manufacturing. And it’s just making work different: A machine may not eliminate a position entirely, but it may turn a more middle-skill job into a low-skill job, bringing lower pay with it. Package delivery jobs used to come with a union, benefits, and stable pay; with the rise of the gig economy, that’s declining. If and when self-driving trucks arrive, there will still be some low-quality jobs needed to complete tasks the robots can’t.

“The issue that we’ve faced in the US economy is that we’ve lost a lot of middle-skill jobs so people are being pushed down into lower categories,” Autor said. “Automation historically has tended to take the most dirty and dangerous and demeaning jobs and hand them over to machines, and that’s been great. What’s happened in the last bunch of decades is that automation has affected the middle-skill jobs and left the hard, interesting, creative jobs and the hands-on jobs that require a lot of dexterity and flexibility but don’t require a lot of formal skills.”

But again, none of this is inevitable. Companies are able to leverage technology to get the most out of workers because workers often don’t have power to push back, enforce limits, or ask for more. Unionization has seen steep declines in recent decades. America’s labor laws and regulations are designed around full-time work, meaning gig companies don’t have to offer health insurance or help fund unemployment. But the laws could — and many would argue should — be modernized.

“The key thing is it’s not just technology, it’s a question of labor power, both collectively and individually,” Bix said. “There are a lot of possible outcomes, and in the end, technology is a human creation. It’s a product of social priorities and what gets developed and adopted.”

Maybe the robot apocalypse isn’t here yet. Or it is, and many of us aren’t quite recognizing it, in part because we got some of the story wrong. The problem isn’t really the robot, it’s what your boss wants the robot to do.

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University of Notre Dame

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Will a robot take my job? Notre Dame researcher says this view is overly pessimistic

Published: March 29, 2023

Author: Tracy DeStazio

Yong Suk Lee

Keough School of Global Affairs

With the impact of industrial robots on the U.S. labor markets in the past two decades, and an ever-increasing presence of machine-driven technology (such as artificial intelligence and ChatGPT), many employees have feared that one day robots will take their jobs. 

Not necessarily so, according to research recently published by Yong Suk Lee , an assistant professor in the University of Notre Dame’s Keough School of Global Affairs. He and his co-author, Auburn University’s John Chung, found that industrial robots, particularly those used within the automotive industry, complemented human workers rather than replaced them — some even working collaboratively, side-by-side. Not only that, but the advanced digitization and automation of that industry likely increased labor productivity and created new tasks, requiring the hiring of more employees. In some cases, robot technology may have supplemented the workforce by filling in gaps that were left vacant when employees quit or moved on to other positions.

The study’s authors examined the influence of robots on the U.S. labor market between 2005 and 2016, analyzing the data in five-year intervals. For the first five years, robots did have a negative impact on the number of human employees and their local wages, but that impact rebounded and turned positive in more recent years, beginning around 2010.

Comparing data from the U.S. Bureau of Labor Statistics, the Organization for Economic Cooperation and Development and the International Federation of Robotics, the researchers were able to track that reversal and determine its source. Productivity could have increased due to three factors, they wrote: the automation of tasks and a reduction in production costs, the improvements of robot technology performing the same tasks, and the creation of new tasks spurred by those automation technologies and abilities. 

Productivity gains from task automation occur when robots are able to perform certain tasks better or faster than humans, the researchers wrote, providing a cost savings. Second, newer models of robots that work faster and more accurately than older models can also increase productivity, without displacing workers. Many of these new automation tasks require human workers to operate and manage them, however, especially as they become more complex, which increases the demand for laborers.   

There has also been a recent shift in how robots are being used and what they are doing, Lee said. “When robots were initially introduced, the intent was to cut costs and replace human workers. But now companies are using ‘collaborative robots’ or ‘cobots,’ which are designed to work together with humans.”

Lee explained that in the automobile industry, for example, industrial robots were set up in a production line and human workers had to be kept separate from the machines due to the danger of proximity with large, moving parts. “But now the industry trend is to create a smaller robot that’s more agile and soft,” Lee said, “so that if it bumps into its collaborative human partner at all, it will just stop. It interacts more, making it a much safer environment. 

“When robots were initially introduced, the intent was to cut costs and replace human workers. But now companies are using ‘collaborative robots’ or ‘cobots,’ which are designed to work together with humans.”

“This new collaborative environment implies that the goal of robots is not necessarily to replace human beings, but to actually augment them.”

The implications for labor workers will be different now that the robots can potentially make them more productive, rather than laying them off, Lee said. “New and advanced robot technology is more sophisticated in that they can be programmed to do multiple tasks. If you think of artificial intelligence or specialized software being incorporated into the robot technology, then the robots can ‘learn’ and adjust to the environment.”

When companies learn to harness robotic technology, they can efficiently produce their goods and exceed production targets, and eventually take on more work or begin new projects, Lee explained. “As a company adopts new technologies, sometimes new tasks are created that we didn’t even know existed before but that are now being initiated.” 

But along with that new technology and those new tasks, Lee said, human experts still need to be hired to design, develop and manage those capabilities. “Our findings pointed to the automotive sector in the U.S., which is the largest adopter of robotics, and we see this transitioning of what an automobile is, what the industry is (i.e., electric vehicles). I think that will create a different type of demand for tasks, skills and workers. Robots can not only help existing workers, but can help recruit new, specialized workers in that domain as the technology evolves.”

The other side to that coin is that there’s a constant shortage of manufacturing workers, Lee added. “The demand for robots is changing as we need to augment labor to fill in those gaps where there is a shortage of employees.”

The researchers also found evidence of spillover effects on other supporting industries within and outside of the specific manufacturing sector. Relying on commuting zones as their parameters of influence, they saw a boost in the service sectors within that local economy. “We found growth in the professional services like accountants, lawyers, etc., for example, but also in retail, food and other services,” Lee said. 

“Humans are the ones creating these new technologies and adopting them — and their intentions actually matter. I think technology will become a larger factor in either the inequality or well-being of human laborers in the future.”

Regarding the quickly evolving artificial intelligence and ChatGPT technologies, Lee suggested we learn to harness these revolutionary capabilities rather than fear them. “They could create new opportunities that we haven’t yet seen or thought of,” Lee theorized. “And then there may be fresh demands for completely new jobs and new employees.” 

The researchers concluded that the impact of robot technology on jobs will continue to evolve, and that further research will be able to shed light on how and where those impacts will occur, as well as on how robots and human labor may interact. 

“Humans are the ones creating these new technologies and adopting them — and their intentions actually matter,” Lee said. “I think technology will become a larger factor in either the inequality or well-being of human laborers in the future.”

Contact:  Tracy DeStazio, assistant director of media relations, 574-631-9958 or  [email protected]

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Kevin Kelly

Better Than Human: Why Robots Will — And Must — Take Our Jobs

Imagine that 7 out of 10 working Americans got fired tomorrow. What would they all do?

It's hard to believe you'd have an economy at all if you gave pink slips to more than half the labor force. But that—in slow motion—is what the industrial revolution did to the workforce of the early 19th century. Two hundred years ago, 70 percent of American workers lived on the farm. Today automation has eliminated all but 1 percent of their jobs, replacing them (and their work animals) with machines. But the displaced workers did not sit idle. Instead, automation created hundreds of millions of jobs in entirely new fields. Those who once farmed were now manning the legions of factories that churned out farm equipment, cars, and other industrial products. Since then, wave upon wave of new occupations have arrived—appliance repairman, offset printer, food chemist, photographer, web designer—each building on previous automation. Today, the vast majority of us are doing jobs that no farmer from the 1800s could have imagined.

It may be hard to believe, but before the end of this century, 70 percent of today's occupations will likewise be replaced by automation. Yes, dear reader, even you will have your job taken away by machines. In other words, robot replacement is just a matter of time. This upheaval is being led by a second wave of automation, one that is centered on artificial cognition, cheap sensors, machine learning, and distributed smarts. This deep automation will touch all jobs, from manual labor to knowledge work.

First, machines will consolidate their gains in already-automated industries. After robots finish replacing assembly line workers, they will replace the workers in warehouses. Speedy bots able to lift 150 pounds all day long will retrieve boxes, sort them, and load them onto trucks. Fruit and vegetable picking will continue to be robotized until no humans pick outside of specialty farms. Pharmacies will feature a single pill-dispensing robot in the back while the pharmacists focus on patient consulting. Next, the more dexterous chores of cleaning in offices and schools will be taken over by late-night robots, starting with easy-to-do floors and windows and eventually getting to toilets. The highway legs of long-haul trucking routes will be driven by robots embedded in truck cabs.

All the while, robots will continue their migration into white-collar work. We already have artificial intelligence in many of our machines; we just don't call it that. Witness one piece of software by Narrative Science (profiled in issue 20.05) that can write newspaper stories about sports games directly from the games' stats or generate a synopsis of a company's stock performance each day from bits of text around the web. Any job dealing with reams of paperwork will be taken over by bots, including much of medicine. Even those areas of medicine not defined by paperwork, such as surgery, are becoming increasingly robotic. The rote tasks of any information-intensive job can be automated. It doesn't matter if you are a doctor, lawyer, architect, reporter, or even programmer: The robot takeover will be epic.

And it has already begun.

Medea Giordano

Louryn Strampe

Here's why we're at the inflection point: Machines are acquiring smarts.

We have preconceptions about how an intelligent robot should look and act, and these can blind us to what is already happening around us. To demand that artificial intelligence be humanlike is the same flawed logic as demanding that artificial flying be birdlike, with flapping wings. Robots will think different. To see how far artificial intelligence has penetrated our lives, we need to shed the idea that they will be humanlike.

Consider Baxter, a revolutionary new workbot from Rethink Robotics. Designed by Rodney Brooks, the former MIT professor who invented the best-selling Roomba vacuum cleaner and its descendants, Baxter is an early example of a new class of industrial robots created to work alongside humans. Baxter does not look impressive. It's got big strong arms and a flatscreen display like many industrial bots. And Baxter's hands perform repetitive manual tasks, just as factory robots do. But it's different in three significant ways.

First, it can look around and indicate where it is looking by shifting the cartoon eyes on its head. It can perceive humans working near it and avoid injuring them. And workers can see whether it sees them. Previous industrial robots couldn't do this, which means that working robots have to be physically segregated from humans. The typical factory robot is imprisoned within a chain-link fence or caged in a glass case. They are simply too dangerous to be around, because they are oblivious to others. This isolation prevents such robots from working in a small shop, where isolation is not practical. Optimally, workers should be able to get materials to and from the robot or to tweak its controls by hand throughout the workday; isolation makes that difficult. Baxter, however, is aware. Using force-feedback technology to feel if it is colliding with a person or another bot, it is courteous. You can plug it into a wall socket in your garage and easily work right next to it.

Second, anyone can train Baxter. It is not as fast, strong, or precise as other industrial robots, but it is smarter. To train the bot you simply grab its arms and guide them in the correct motions and sequence. It's a kind of "watch me do this" routine. Baxter learns the procedure and then repeats it. Any worker is capable of this show-and-tell; you don't even have to be literate. Previous workbots required highly educated engineers and crack programmers to write thousands of lines of code (and then debug them) in order to instruct the robot in the simplest change of task. The code has to be loaded in batch mode, i.e., in large, infrequent batches, because the robot cannot be reprogrammed while it is being used. Turns out the real cost of the typical industrial robot is not its hardware but its operation. Industrial robots cost $100,000-plus to purchase but can require four times that amount over a lifespan to program, train, and maintain. The costs pile up until the average lifetime bill for an industrial robot is half a million dollars or more.

The third difference, then, is that Baxter is cheap. Priced at $22,000, it's in a different league compared with the $500,000 total bill of its predecessors. It is as if those established robots, with their batch-mode programming, are the mainframe computers of the robot world, and Baxter is the first PC robot. It is likely to be dismissed as a hobbyist toy, missing key features like sub-millimeter precision, and not serious enough. But as with the PC, and unlike the mainframe, the user can interact with it directly, immediately, without waiting for experts to mediate—and use it for nonserious, even frivolous things. It's cheap enough that small-time manufacturers can afford one to package up their wares or custom paint their product or run their 3-D printing machine. Or you could staff up a factory that makes iPhones.

Photo: Peter Yang

Baxter was invented in a century-old brick building near the Charles River in Boston. In 1895 the building was a manufacturing marvel in the very center of the new manufacturing world. It even generated its own electricity. For a hundred years the factories inside its walls changed the world around us. Now the capabilities of Baxter and the approaching cascade of superior robot workers spur Brooks to speculate on how these robots will shift manufacturing in a disruption greater than the last revolution. Looking out his office window at the former industrial neighborhood, he says, "Right now we think of manufacturing as happening in China. But as manufacturing costs sink because of robots, the costs of transportation become a far greater factor than the cost of production. Nearby will be cheap. So we'll get this network of locally franchised factories, where most things will be made within 5 miles of where they are needed."

That may be true of making stuff, but a lot of jobs left in the world for humans are service jobs. I ask Brooks to walk with me through a local McDonald's and point out the jobs that his kind of robots can replace. He demurs and suggests it might be 30 years before robots will cook for us. "In a fast food place you're not doing the same task very long. You're always changing things on the fly, so you need special solutions. We are not trying to sell a specific solution. We are building a general-purpose machine that other workers can set up themselves and work alongside." And once we can cowork with robots right next to us, it's inevitable that our tasks will bleed together, and soon our old work will become theirs—and our new work will become something we can hardly imagine.

To understand how robot replacement will happen, it's useful to break down our relationship with robots into four categories, as summed up in this chart:

The rows indicate whether robots will take over existing jobs or make new ones, and the columns indicate whether these jobs seem (at first) like jobs for humans or for machines.

Let's begin with quadrant A: jobs humans can do but robots can do even better. Humans can weave cotton cloth with great effort, but automated looms make perfect cloth, by the mile, for a few cents. The only reason to buy handmade cloth today is because you want the imperfections humans introduce. We no longer value irregularities while traveling 70 miles per hour, though—so the fewer humans who touch our car as it is being made, the better.

And yet for more complicated chores, we still tend to believe computers and robots can't be trusted. That's why we've been slow to acknowledge how they've mastered some conceptual routines, in some cases even surpassing their mastery of physical routines. A computerized brain known as the autopilot can fly a 787 jet unaided, but irrationally we place human pilots in the cockpit to babysit the autopilot "just in case." In the 1990s, computerized mortgage appraisals replaced human appraisers wholesale. Much tax preparation has gone to computers, as well as routine x-ray analysis and pretrial evidence-gathering—all once done by highly paid smart people. We've accepted utter reliability in robot manufacturing; soon we'll accept it in robotic intelligence and service.

Next is quadrant B: jobs that humans can't do but robots can. A trivial example: Humans have trouble making a single brass screw unassisted, but automation can produce a thousand exact ones per hour. Without automation, we could not make a single computer chip—a job that requires degrees of precision, control, and unwavering attention that our animal bodies don't possess. Likewise no human, indeed no group of humans, no matter their education, can quickly search through all the web pages in the world to uncover the one page revealing the price of eggs in Katmandu yesterday. Every time you click on the search button you are employing a robot to do something we as a species are unable to do alone.

While the displacement of formerly human jobs gets all the headlines, the greatest benefits bestowed by robots and automation come from their occupation of jobs we are unable to do. We don't have the attention span to inspect every square millimeter of every CAT scan looking for cancer cells. We don't have the millisecond reflexes needed to inflate molten glass into the shape of a bottle. We don't have an infallible memory to keep track of every pitch in Major League Baseball and calculate the probability of the next pitch in real time.

We aren't giving "good jobs" to robots. Most of the time we are giving them jobs we could never do. Without them, these jobs would remain undone.

Now let's consider quadrant C, the new jobs created by automation—including the jobs that we did not know we wanted done. This is the greatest genius of the robot takeover: With the assistance of robots and computerized intelligence, we already can do things we never imagined doing 150 years ago. We can remove a tumor in our gut through our navel, make a talking-picture video of our wedding, drive a cart on Mars, print a pattern on fabric that a friend mailed to us through the air. We are doing, and are sometimes paid for doing, a million new activities that would have dazzled and shocked the farmers of 1850. These new accomplishments are not merely chores that were difficult before. Rather they are dreams that are created chiefly by the capabilities of the machines that can do them. They are jobs the machines make up.

Before we invented automobiles, air-conditioning, flatscreen video displays, and animated cartoons, no one living in ancient Rome wished they could watch cartoons while riding to Athens in climate-controlled comfort. Two hundred years ago not a single citizen of Shanghai would have told you that they would buy a tiny slab that allowed them to talk to faraway friends before they would buy indoor plumbing. Crafty AIs embedded in first-person-shooter games have given millions of teenage boys the urge, the need, to become professional game designers—a dream that no boy in Victorian times ever had. In a very real way our inventions assign us our jobs. Each successful bit of automation generates new occupations—occupations we would not have fantasized about without the prompting of the automation.

To reiterate, the bulk of new tasks created by automation are tasks only other automation can handle. Now that we have search engines like Google, we set the servant upon a thousand new errands. Google, can you tell me where my phone is? Google, can you match the people suffering depression with the doctors selling pills? Google, can you predict when the next viral epidemic will erupt? Technology is indiscriminate this way, piling up possibilities and options for both humans and machines.

It is a safe bet that the highest-earning professions in the year 2050 will depend on automations and machines that have not been invented yet. That is, we can't see these jobs from here, because we can't yet see the machines and technologies that will make them possible. Robots create jobs that we did not even know we wanted done.

Finally, that leaves us with quadrant D, the jobs that only humans can do—at first. The one thing humans can do that robots can't (at least for a long while) is to decide what it is that humans want to do. This is not a trivial trick; our desires are inspired by our previous inventions, making this a circular question.

When robots and automation do our most basic work, making it relatively easy for us to be fed, clothed, and sheltered, then we are free to ask, "What are humans for?" Industrialization did more than just extend the average human lifespan. It led a greater percentage of the population to decide that humans were meant to be ballerinas, full-time musicians, mathematicians, athletes, fashion designers, yoga masters, fan-fiction authors, and folks with one-of-a kind titles on their business cards. With the help of our machines, we could take up these roles; but of course, over time, the machines will do these as well. We'll then be empowered to dream up yet more answers to the question "What should we do?" It will be many generations before a robot can answer that.

This postindustrial economy will keep expanding, even though most of the work is done by bots, because part of your task tomorrow will be to find, make, and complete new things to do, new things that will later become repetitive jobs for the robots. In the coming years robot-driven cars and trucks will become ubiquitous; this automation will spawn the new human occupation of trip optimizer, a person who tweaks the traffic system for optimal energy and time usage. Routine robo-surgery will necessitate the new skills of keeping machines sterile. When automatic self-tracking of all your activities becomes the normal thing to do, a new breed of professional analysts will arise to help you make sense of the data. And of course we will need a whole army of robot nannies, dedicated to keeping your personal bots up and running. Each of these new vocations will in turn be taken over by robots later.

The real revolution erupts when everyone has personal workbots, the descendants of Baxter, at their beck and call. Imagine you run a small organic farm. Your fleet of worker bots do all the weeding, pest control, and harvesting of produce, as directed by an overseer bot, embodied by a mesh of probes in the soil. One day your task might be to research which variety of heirloom tomato to plant; the next day it might be to update your custom labels. The bots perform everything else that can be measured.

Right now it seems unthinkable: We can't imagine a bot that can assemble a stack of ingredients into a gift or manufacture spare parts for our lawn mower or fabricate materials for our new kitchen. We can't imagine our nephews and nieces running a dozen workbots in their garage, churning out inverters for their friend's electric-vehicle startup. We can't imagine our children becoming appliance designers, making custom batches of liquid-nitrogen dessert machines to sell to the millionaires in China. But that's what personal robot automation will enable.

Everyone will have access to a personal robot, but simply owning one will not guarantee success. Rather, success will go to those who innovate in the organization, optimization, and customization of the process of getting work done with bots and machines. Geographical clusters of production will matter, not for any differential in labor costs but because of the differential in human expertise. It's human-robot symbiosis. Our human assignment will be to keep making jobs for robots—and that is a task that will never be finished. So we will always have at least that one "job."

In the coming years our relationships with robots will become ever more complex. But already a recurring pattern is emerging. No matter what your current job or your salary, you will progress through these Seven Stages of Robot Replacement, again and again:

1. A robot/computer cannot possibly do the tasks I do.

2. OK, it can do a lot of them, but it can't do everything I do .

3. OK, it can do everything I do, except it needs me when it breaks down, which is often.

4. OK, it operates flawlessly on routine stuff, but I need to train it for new tasks.

5. OK, it can have my old boring job, because it's obvious that was not a job that humans were meant to do.

6. Wow, now that robots are doing my old job, my new job is much more fun and pays more!

7. I am so glad a robot/computer cannot possibly do what I do now.

This is not a race against the machines. If we race against them, we lose. This is a race with the machines. You'll be paid in the future based on how well you work with robots. Ninety percent of your coworkers will be unseen machines. Most of what you do will not be possible without them. And there will be a blurry line between what you do and what they do. You might no longer think of it as a job, at least at first, because anything that seems like drudgery will be done by robots.

We need to let robots take over. They will do jobs we have been doing, and do them much better than we can. They will do jobs we can't do at all. They will do jobs we never imagined even needed to be done. And they will help us discover new jobs for ourselves, new tasks that expand who we are. They will let us focus on becoming more human than we were.

Let the robots take the jobs, and let them help us dream up new work that matters.

Kevin Kelly ( kk.org ) is senior maverick of Wired and the author, most recently, of What Technology Wants.

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Artificial intelligence and automation: Could a robot do your job?

New data from research house AlphaBeta provides the answer. Search to find your job — if you're game.

This article contains content that is not available.

A new analysis ranks how much of every occupation in Australia is at risk of automation, as artificial intelligence looks set to reshape our working lives.

The research, conducted by economic modelling firm AlphaBeta and funded by Google, finds the top five easiest to automate job categories are:

• 1. Construction and mining labourers, with 86 per cent of their job susceptible to automation.
• 2. Glaziers, plasterers and tilers (85 per cent)
• 3. Floor Finishers and Painting Trades Workers (84 per cent)
• 4. Food Preparation Assistants (84 per cent)
• 5. Food Preparation Assistants (84 per cent)

At the other end of the scale, the study ranks these jobs as the least able to be automated using AI:

• 1. Contract, program and project administrators, with just 7 per cent of their work time susceptible to automation.
• 2. Insurance agents and sales representatives (also 7 per cent)
• 3. Real estate sales agents (9 per cent)
• 4. Engineering professionals (10 per cent)
• 5. ICT managers and miscellaneous specialist managers (both 12 per cent)

What does this mean for my job?

Economist Andrew Charlton, who led the AlphaBeta team that conducted the analysis , says that over the next 30 years, automation will affect every job in Australia — but not always in the ways you might expect.

It's not all about machines destroying jobs.

"It's not so much about what jobs will we do, but how will we do our jobs," he explains. "Everyone will do their job differently, working with machines over the next 20 years."

"For example, a retail worker will spend nine hours less on physical and routine tasks like stocking shelves and processing goods at the checkout, and nine hours more on tasks like helping customers to find what they want and providing them with advice."

Still, there's no doubt AI will put some jobs at risk, and Charlton says the most critical thing is how Australian governments and businesses respond to the need to reshape large sections of the workforce.

How did you get this data?

AlphaBeta did an analysis to figure out how difficult it would be to automate each type of job in Australia, in a research project that was funded by Google.

It's a huge task, and not simple. The project was led by economist Andrew Charlton, a former adviser to Kevin Rudd.

"We broke the Australian economy down into 20 billion hours of work," he explains, "and we asked what does every Australian do with their day, and how does what they do in their job change over the next 15 years."

In more detail, here's the process Charlton and his team stepped through:

• 1. The starting point was an existing US government database called O*NET, which provides a breakdown of the types of tasks every occupation performs. For example, a factory worker might 'operate equipment' and 'monitor facilities', while a sales assistant would 'assist customers' and 'assess products'. The database contains more than 2,000 such work-related activities.
• 2. Each of those work tasks was assessed and placed into one of six groups depending on the type of work it represented. For instance, tasks requiring interaction with other people were assigned to a group named 'interpersonal' and tasks such as reviewing documents or monitoring facilities were assigned to a group named 'information analysis'.
• 3. Each of those groups of work tasks was rated as 'difficult to automate' or 'automatable'.
• 4. All of that information was pulled together, so the researchers could see how much of any individual job was 'difficult to automate' and how much was 'automatable'.
• X (formerly Twitter)
• Business, Economics and Finance

Robots Taking over Jobs

This essay will explore the impact of robotics and automation on employment. It will discuss which sectors are most affected, the potential for job displacement, and the new types of jobs created by technological advancements. The piece will analyze the broader implications of robots taking over jobs for the economy and workforce. Moreover, at PapersOwl, there are additional free essay samples connected to Artificial Intelligence.

How it works

Did you know that about thirty percent of the Earth’s population is unemployed? This sounds crazy to believe but unfortunately, it’s true. The main reason such a catastrophe is occurring is that we’re moving fast into the future, now than ever before. Almost every day, the world changes and humans come up with ways to improve it even more. Some of those improvements occur at the cost of innocent lives. For example, robots stealing our jobs is one of them.

Robots should not be able to steal the jobs of innocent civilians.

The population of Earth is growing with each passing day, and it needs resources and the common currency to survive. In 2016, the Earth’s population was more than 7.4 billion people. In 2017, that number bumped up to more than 7.55 billion people. Today, that number is a little more than 7.6 billion people. As we can see from this data, the Earth’s population is on the rise, and it will only grow unless something abnormal was to happen. Those people need basic survival resources. Those resources can be bought with a common currency. If all jobs were to be taken by robots, it would be unlikely that government officials would pay a common currency to the people. Also, the people who would have deserved more money get paid an equal amount that everybody else gets paid since they have been laid off their work.

Planet Earth is moving fast in developing new technologies like artificial intelligence, and just more robots in general. These new technologies are growing more powerful and are being used with each passing day. They are also being developed to better appeal to a customer.

“It seems that no profession is safe.”, says an article called Robots and Content: Calculators or Creators, by Affelt Amy (“Affelt”). If robots take our jobs in every profession, then even with a fixed income, it will be harder for the average human to survive. We need to stop the usage of AI and robots concerning our jobs. One might object that robots will only take over the dirty jobs that nobody wants to do, and not any of the better jobs that people are already professional in. While this might be true, it won’t be true for too long into the future because as usage of robotics and AI grows with each passing day, it will be too hard to predict which profession will be taken over next.

Without our jobs, it will be hard to maintain everyday life. Sure, we will have a lot of free time, but with every advantage comes a sacrifice. Being jobless will lead to saving more on everything. It will also lead to a lack of a luxurious life and a change in the daily schedule of most people. Pretty soon, more of the low-income families will start appearing. More and more people will start dying off due to lack of basic survival necessities. Even high-income families would become low-income due to lack of jobs. After this, robots will take over the world. According to an article by Forbes, After Robots take over our jobs, then what?, by Michael Bernick, companies like Xerox and Howard Street were hiring repairmen to repair the old machines, but pretty soon, they went out of business as they couldn’t keep up with the human pace of getting new technologies in printing (“Bernick”).

This relates to a short story called Terrible Things. In this article, The Terrible Things took each species one by one to avoid conflict with the other species. The other species doubted that their time would come, because of their appearance, until they were abducted as well. Now,

let’s think of the terrible things like robots and the animals as professions. Each profession doubts that robots would take over them until the truth lies right in front of them. Pretty soon, all the professions will be gone, and robots will have control to everything.

If robots do steal the jobs of innocent civilians, it could lead to a massive catastrophe. Once again, our survival depends on our jobs. The population of Earth is growing so fast that we can’t risk the survival of everybody now and of all the future generations over machines. If you care about your state of well being, and if you want to continue to live the life that you are living right now, then you should definitely care about your future!

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Risk sentiment chart

The Monthly Automation Risk Level Chart visualizes evolving views on job automation risks. Points on the chart represent the monthly aggregated risk level, sourced from user votes and scaled from 0% to 100%, with 100% indicating maximum perceived risk.

The risk level for every job is calculated as an unweighted average, meaning that the votes from all occupations carry equal weight, regardless of the size of the profession.

This chart essentially reflects the collective sentiment of the users frequenting our website.

Discover more charts like this one , including a variant weighted by employment numbers.

Explore the charts to observe shifts in job security in the AI and robotics era. Remember, your vote influences the perceived risk for your occupation. Don't miss out on having your say!

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