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• Last updated March 22, 2024
• In AI Origins & Evolution

14 Best Presentations On Artificial Intelligence And Machine Learning

• Published on January 3, 2018
• by Jeevan Biswas

For a quick overview of a subject or a breakdown of concepts, SlideShare serves as a go-to platform for many. The recapitulations found in many of the presentations are both concise and informative.

The most popular presentations are the ones that have received the most number of likes and have been viewed more than the other presentations in a particular category.

AIM brings you the 14 most popular presentations on Artificial Intelligence, Machine Learning. Deep Learning and everything else in between.

Best AI PPT and Topics in 2024

1) artificial intelligence and law overview.

• 2)  What is Artificial Intelligence – Artificial Intelligence Tutorial For Beginners

3) Why Social Media Chat Bots Are the Future of Communication

4) ai and the future of work, 5) ai and machine learning demystified, 6) study: the future of vr, ar and self-driving car, 7) artificial intelligence, 8) solve for x with ai: a vc view of the machine learning & ai landscape, 9) deep learning – the past, present and future of artificial intelligence.

• 10) The Future Of Work & The Work Of The Future

11) Asia’s Artificial Intelligence Agenda

12) 10 lessons learned from building machine learning systems, 13) design ethics for artificial intelligence, 14) artificial intelligence.

People who are not aware of what artificial intelligence is will find the topic presented in a very simple manner here.

Along with the explanation of what AI is, the two major approaches towards AI are discussed– logic and rules-based approach, and machine learning approach. Special emphasis on the machine learning approach can be seen in the slides devoted to its detailed examination. The examination goes beyond the rudimentary explanation of what machine learning is and presents examples of proxies that seem like machine learning but are not.

The presentation lists examples of AI in the field of law and identifies some of the limitations of AI technology.

2)  What is Artificial Intelligence – Artificial Intelligence Tutorial For Beginners

For the uninitiated, this presentation offers an ideal rundown of AI. The question of AI being a threat is raised at the very beginning. However, as the presentation progresses, it discusses the basics necessary for understanding AI. The most basic question of what is artificial intelligence is answered.

A brief history of AI and the discussion on recent advances in the field of AI is also found. The various areas where AI currently sees practical application have been listed. Fascinating uses that AI can be put to in the future are also found in the presentation. The two approaches of achieving AI, machine learning and deep learning, is touched upon.

All in all, this presentation serves as a simple introduction to AI.

An exciting application of AI can be found in chatbots. Here, the limitless scope of chatbots is explored. The various milestones reached by leading players  in bot technology such as Facebook, Skype and KIK are enumerated.

The evolution of chatbots and its absorption of more AI in the future is also looked into. E-Commerce is touted as the biggest beneficiary of the advancement in chatbots and that bot technology will owe its rise to services and commerce.

Two tech giants, Facebook and Google, have been pitted against each other based on their ongoing developments in this area and the question of who will emerge as the best is raised.

This presentation talks about the far-fetching applicability of AI and ML,and the perils of that applicability. In order to derive a better understanding of this presentation, it is advisable to first watch the original talk.

During the course of the presentation, many examples of how machines can learn and perform any human task that is repetitive in nature are cited.

Other possibilities suggested include the creation of new unheard jobs for human beings as a result of aggressive use of AI and other allied technologies. Qualities that are characteristic only of human beings, may be the basis on which these jobs will be created is also suggested.

It concludes with a message- Ride the train, don’t jump in front of it.

In this presentation, Carol Smith establishes that AI cannot replace humans. Smith conveys that AI can serve the purpose of enabling human beings in making better decisions.

The slides talk about how the actions of AI are the result of the human inputs going into its programming. An AI’s bias is not its own, but the human bias with which it has been programmed, is emphasised on.

Other issues such as the need for regulations and other considerations within it that require deliberation are also touched upon. The presentation leaves you with a message – Don’t fear AI, Explore it.

Though no descriptive breakdown of topics related to AI is found, the presentation offers interesting numerical insights into many questions. Statistics on three main subjects – artificial intelligence, virtual reality and wearable technology, is provided here.

A variety of questions and the numerical representations of their responses are found under four main categories:

• Will you  purchase a self-driving car when they become available?
• Are you concerned with the rise of Artificial Intelligence?
• Is wearable technology part of your daily life?
• Do you own or intend to purchase a Virtual Reality headset in the next twelve months?

From consumer opinions to overall consensus of countries, the numbers show current trends and the possible trends in the future based on increasing development in the mentioned technologies.

There are many who have been introduced to AI only recently due to the buzz surrounding it and may not be aware of the early developments that led to its current status.

This presentation from 2009 offers a simple yet informative introduction to the rudiments of AI. AI’s history and a timeline of all the significant milestones in AI up to 2009 can be found. The presentation also provides an introduction to AI programming languages such as LISP and PROLOG.

For those who would like to have a crash course on the basics of AI in order to catch up with it current trends, this presentation serves the purpose.

While the concepts of  AI or ML are not spoken about, light is shed on other important aspects of it. The presentation discusses about how many known tech giants such as Google are bolstering their AI capabilities through mergers and acquisitions.

The role of venture capital(VC) in the landscape of AI and machine learning,and the involvement of VC in the firms that were acquired are mentioned.

Another point highlighted is how large companies are moving towards ML and re-configuring themselves around ML, and how it is not a US-centric phenomenon. Key points have been expressed in the form of self-explanatory graphical representations. Rounding off the presentation is the possible direction that ML can take and a few pointers on achieving success in ML.

This presentation provides a comprehensive insight into deep learning. Beginning with a brief history of AI and introduction to basics of machine learning such as its classification, the focus shifts towards deep learning entirely.

Various kinds of networks such as recurrent neural nets and generative adversarial networks have been discussed at length. Emphasis has been given to important aspects of these networks and other mechanisms such as natural language processing (NLP).

Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first time learner’s of AI to comprehend.

10) The Future Of Work & The Work Of The Future

The subject of self-learning of robots and machines is explored here. Talking about the fictional Babel fish, it is suggested that the advancements in technology leading to improved learning and translations by machines  made the Babel fish a near-real entity.

New ‘power’ values such as speed, networked governance, collaboration and transparency, among others, have been put forth and juxtaposed against older ones that are not fully technology  driven.

Going against the popular assumption that robots and machines will replace human beings, the presentation proposes that we are on the brink of the largest job creation period in humanity.

This presentation is a briefing paper by the MIT Technological Review and talks about how the global adoption of AI is being sped up by Asian countries. It suggests that Asia will not only benefit greatly from the rise in AI technology, but will also define it.

The data collected for the review has been summarized in the form of simple info-graphics. They are a numerical reflection of the mood surrounding the adoption of AI across different industries and how it could possibly impact human capital.  The review also suggests that while there is awareness about AI in Asia, only a small percentage of companies are investing in it.

Pointers for business leaders in Asia to capitalize on AI is offered in the end along presentation with an info-graphic timeline of the history of AI.

Download review report in pdf

While they are two separate presentations, they talk about the same subject- machine learning. The presentations are a summary of the analysis of machine learning adopted by two platforms, Netflix and Quora.

In case of Netflix, emphasis has been given to the choice of the right metric and the type of data used for testing and training. It also emphasises the need to understand the dependence between the data used and the models employed. The advice to optimize only areas that matter is offered.

The second presentation on Quora, talks about teaching machines only what is necessary. It stresses on the need the to focus on feature engineering and being thoughtful about the ML infrastructure. Another point it highlights is the combination of supervised and unsupervised being the key in ML application.

With 135 slides, this presentation provides an exhaustive insight into the creation of an ethically sound AI. An introduction to the subject of User Experience(UX) design is followed by the rules that have to be considered during the designing process.

The chronological progression of UX, beginning with experience design and ending with intelligence design, and the direction in which this process is headed is also discussed.

Supported by powerful visuals, the presentation touches upon many essential considerations such as nature of intelligence, purpose of existence, awareness of self and the need for which the AI is created.

It raises a pertinent point that while creating AI, human beings are creating something that embodies qualities that they lack.

Made for a school competition in 2009, it provides many examples of cutting-edge applications of AI at the time.

Many of the examples, such as mind controlled prosthetic limbs, Ultra Hal Assistant and Dexter- the robot provide a trip down the AI memory lane where the applications of AI seemed like a page out of a sci-fi novel. It presents a list of areas where AI can assist human beings.

It concludes with  a series of questions, some of which, are still being debated. Such as machines replacing human beings’ and human unemployment due to the use of machines.

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The present and future of AI

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Q: Any predictions for the next report?

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

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Blockchain booms, risks loom: the ai rescue mission in smart contract auditing, developing incident response plans for insider threats, weis wave: revolutionizing market analysis, popular presentations on artificial intelligence.

Artificial intelligence is an increasingly important technology that enables computers to simulate human intelligence-based tasks. With a robust foundation of software and hardware, AI can accomplish numerous human tasks with much more efficiency. It works by building and training algorithms using programming languages like Python, R, and more. Once you have an algorithm, the next step is to ingest training data in the model, analyze it, and find patterns/abnormalities to forecast future states. There are many learning materials on artificial intelligence and related technologies. However, not all of those materials credibly explain AI concepts and applications.

Additionally, going through an entire book is time-consuming. Learning from a PPT on artificial intelligence is much easier than reading an entire book or research paper. This blog highlights some popular presentations on artificial intelligence and machine learning. 

Some popular presentations on artificial intelligence

• Introduction to Artificial Intelligence

Going through this AI PowerPoint presentation will be an excellent place to start learning about artificial intelligence. It is a brief presentation introducing you to artificial intelligence and its subsets like machine learning and deep learning without diving into more essential details. It describes what AI, machine learning, and deep learning are. Proceeding with AI, the presentation specifies types of artificial intelligence and its use cases. You will see that AI has applicability in various applications like supply chain management, human resource, knowledge management, customer insights, predictive analytics, and many more. Some of these use cases have been explored and explained via flowcharts to make them more accessible for the reader to understand. Finally, the AI PPT explains the rising trends observed in 2020.

You can download the PPT here.

• Introduction to Machine Learning and AI 

Introduction to ML/AI is yet another artificial intelligence PPT that will introduce you to the subject. The presentation will explain machine learning and discuss several commercial applications. The PowerPoint presentation will also differentiate between machine learning and artificial intelligence. You will be acquainted with supervised machine learning methods using regression and classification techniques and unsupervised learning via clustering, association, and data reduction. The AI PPT will also explain the problems faced while working with the algorithms and the consequent failures. You will have a broad overview of how to begin working with AI/ML, the entire procedure, and the result.

• Artificial Intelligence Introduction 

This artificial intelligence presentation is yet another PPT that briefs you about what AI is. It begins by explaining the term “intelligence” and providing several alternative definitions leading to a holistic one. The description is done in tandem with the need for incorporating such technologies. The AI presentation discusses advancements in AI technology, starting with the Turing Test developed by Alan Turing to test for intelligence in the 1950s. Using the test results, one can build a representative model with real-world knowledge and reasoning. There is a detailed procedure for understanding and using the test to solve problems. 

You can download PPT on artificial intelligence if you wish to download it here .

• Applications of Artificial Intelligence in the Real World

AI is becoming highly applicable in many real-world applications, and this PowerPoint presentation discusses common areas where AI is applied. This presentation talks about AI developments in creating fundamental technologies that can be used in daily life. It begins with recent developments in artificial intelligence and explores some use cases in everyday life. It talks about AI in self-driving cars, chatbots, social media platforms, healthcare, etc.

You can access and download the PPT here .

• Sub-ML Framing: Economics of Data Science use cases 

In this AI applications PPT, you will learn about experimenting with use cases via artificial intelligence. Before jumping directly into creating fully functional use cases, you can always start by developing basic versions and adding incremental updates. This approach is referred to as the sub-ML approach. The presentation discusses the feature store requirements to implement several use cases in machine learning. You can easily understand the framework by only going through the architectures given in this paper presentation on machine learning without delving into more details. 

You can refer to the PPT here.

Read More: Top Artificial Intelligence Books

• How AI and Robotics are transforming healthcare

This PowerPoint presentation on artificial intelligence will focus on its usefulness in healthcare. AI in healthcare is a trending artificial intelligence topic for presentation due to its increasing popularity and usefulness. New technologies and algorithms have enabled doctors and healthcare professionals to diagnose abnormalities and predict prognosis. The presentation will highlight the different sub-fields where AI-based tools support decision-making and provide more comprehensive access to information regarding health. 

• Artificial intelligence in Finance 

AI in Finance is another application of artificial intelligence PPT you will frequently encounter. This presentation will show how AI can help automate financial service provision, enhance efficiency, and reduce costs. It begins by briefing you about machine learning and its application in four primary segments: capital markets, consumer banking, the insurance industry, and the stock market. The AI PPT will explain financial institutions in the context of big data and discuss several case studies for each primary segment, explaining how artificial intelligence and machine learning are used in the industry.

• The Future of AR, VR, and Self-Driving Cars

In this future of artificial intelligence PPT, you will get numerical insights on how artificial intelligence is utilized in virtual reality, wearable technology, and self-driving vehicles. It explains the efficiency and applicability of AI in the mentioned areas and enables you to decide whether to go for a self-driving car based on its relevance in daily life. The presentation talks about VR headsets and their usefulness. Finally, the concluding slides show current trends and future predictions of rising demands and advancements in these areas. 

• Introduction to Machine Learning

This presentation is an AI applications PPT that will teach you about one of the most utilized sub-field of AI, machine learning. It is an introductory presentation that will brief you about the concept without getting into detail. The first few slides explain machine learning and the difference between ML and standard computer software. You will also read about different types of machine learning: supervised, unsupervised, and reinforcement learning. The PPT also mentions some advantages and disadvantages of machine learning.

You can download it from here.

• Deep Learning

Deep learning is another sub-field of artificial intelligence that deals with applications that function like human brains. The word “deep” is related to the multiple layers used in the learning process. This poster presentation on AI, specifically on a sub-field of AI, combines 2-3 presentations. The first few slides introduce several deep learning models, specifically logistic regression and gradient boosting. These two models have been explained in detail, covering the types and their basic architectures. In the second half, the presentation discusses convolutional neural networks (CNN) in detail. It also explains how you can create one by pooling multiple layers. The third section discusses GANs (generative adversarial networks) and RNNs (recurrent neural networks). Going through this presentation will give you a great insight into deep learning.  You can download it from here.

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25+ AI PowerPoint Templates (For AI Presentations)

Artificial Intelligence (AI) is one of the most discussed topics around the world these days. If you’re also working on preparing a presentation related to AI, we have the perfect set of PowerPoint templates for your project.

Diving into the world of artificial intelligence can be complex, but presenting your findings or concepts doesn’t have to be. This post has been created to make your life easier by providing you with some of the best AI PowerPoint templates with cool technology-themed designs. These are ideal for designers and marketers who want to structure visually appealing and effective presentations on topics related to AI.

Whether you are a startup working on new AI tech or an agency promoting its AI-powered services, our list has templates to give your presentation a professional edge and make your audience dive deep into the futuristic world of artificial intelligence.

The PowerPoint templates in this collection range from both paid and free options, giving you the flexibility to choose what fits your needs the most. Have a look.

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Download thousands of PowerPoint templates, and many other design elements, with a monthly Envato Elements membership. It starts at $16 per month, and gives you unlimited access to a growing library of over 2,000,000 presentation templates, fonts, photos, graphics, and more.

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AI Artificial Intelligence PowerPpoint Presentation

The AIONIC PowerPoint template is a unique and customizable slideshow designed for presentations related to artificial intelligence and technology. It features over 25 unique layouts, at 16:9 aspect ratio, and a high-resolution format of 1920×1080 pixels. Perfect for creating detailed pitch decks or marketing kits, the template is easy to use and provides numerous layout variations to choose from.

Artificial Intelligence PowerPoint Template

Avilon PowerPoint Template is a modern slideshow template for creating technology and AI-themed presentations. With 35 unique slides that are fully customizable, it allows users to easily switch up colors, text, and images. All graphics and shapes are resizable and editable, with various infographics and a 16:9 HD widescreen format included. You can use this template to create bold AI presentations that wow your audience.

Aizone – Artificial Intelligence PowerPoint Template

This PowerPoint template is an ideal choice for creating AI presentations with a futuristic theme. With 30 slides and an array of customizable graphics, it offers unique design elements and professional layouts. Users can easily edit content and images thanks to the drag-and-drop feature. It’s modern and visually appealing, ensuring an engaging presentation experience.

Prompt Artificial Intelligence PowerPoint Template

This is a versatile PowerPoint template ideal for those needing to create engaging presentations revolving around prompt engineering and AI technology. With 35 unique, high-resolution layouts available, the template is fully editable, allowing for a tailored approach to fit your brand. It comes with a set of stylish slides with a bold dark color theme as well.

Aexos – AI Tech Presentation PowerPoint Template

A PowerPoint template specially designed for tech enthusiasts who need to create engaging presentations related to AI. With 36 easily editable slides, users can simply drag and drop to create visually captivating presentations to articulate their tech narratives with precision. It includes free fonts, resizable shapes, icons, and much more as well.

SynthAI – AI PowerPoint Presentation Template

SynthAI is a creative PowerPoint template designed for creating sleek, modern presentations. With a focus on artificial intelligence, business, and technology, its fully editable slides give you the freedom of customization. It features a widescreen 16:9 ratio, useful data charts, and convenient drag and drop functionality.

AI Presentation – Technology PowerPoint Template

This is an expertly crafted PowerPoint template perfect for crafting striking presentations about artificial intelligence. With its modern design, 30 creative slides, standard and widescreen formats, and six color combinations, it is highly versatile for business and educational presentations or marketing purposes. Its customizable nature and impressive icons enhance its appeal significantly.

Artificial Intelligence AI PowerPoint Template

A modern, infographic-style PowerPoint template ideal for exploring vast topics related to AI. With 20 unique, editable slides boasting a 16x9HD, retina-ready resolution, this template touches on intriguing facets of AI such as machine learning, AI subfields, and their usages. It offers ten pre-made colour themes, detailed instructions, and the flexibility to customize your own theme.

AI Industry PowerPoint Presentation Template

A minimalist yet flexible PowerPoint template to assist you in producing engaging AI-themed presentations. Perfect for marketing, technology startups, and broad business usage, the package offers 30 easily editable slides in HD widescreen format (1920×1080 pixels). With this template, elements, colors, shapes, and charts can all be tailored to your context.

AI Technology Presentation Template for PowerPoint

A user-friendly PowerPoint template for creating professional AI-related presentations. Its elegant design, complete with gradient-style slides, flat colors, and a variety of infographics, is fully customizable and multipurpose. Its 30 clean and creative slide templates in HD 16:9 widescreen format are simple to use; all graphs are editable and customizable.

Futura – Modern AI Presentation Template

Futura is a modern PowerPoint template for creating top-notch presentations focusing on AI, VR, or other futuristic technologies. It’s adaptable for Powerpoint, Keynote, and Google Slides, and completely editable to suit any topic, like Security or Networking. The package includes 2400 total slides with 30 unique slides each, in five color themes, accommodating both dark and light backgrounds.

Stylish Artificial Intelligence PowerPoint Template

A sleek and modern PowerPoint template ideal for developers, researchers, and scientists wishing to create educational and visually appealing presentations. With 35 customizable slides, integrating graphics, diagrams, and images has never been easier. Predesigned with 16:9 HD widescreen slide format and editable fonts, this template effortlessly handles data representation and typography modifications.

Modern Artificial Intelligence PowerPoint Template

This PowerPoint template enriches your presentations with a sleek, contemporary design. This set of over 30 unique slides gives your content a polished look and features like an editable chart and elements deliver flexibility to cater to your presentation needs. Available in both light and dark versions, this AI-themed template enhances your business narratives, rendering them more engaging for your audience.

Blouniverse – Artificial Intelligence PowerPoint Template

A meticulously designed, ultra-modern PowerPoint template for AI-themed presentations. It presents a blend of usability and aesthetics across its 27 unique slides, tailored for a range of presentations from business to branding. The template features easy customizability, over a variety of vectors and icons, paired with free support and HD quality.

Neurimo – Artificial Intelligence AI PowerPoint Template

The Neurimo is a PowerPoint template designed for a wide range of tech-related presentations, including AI, augmented reality, and cryptocurrency. This professional and modern template features over 30 easily editable slides with resizable graphics, free web fonts, and a wide screen ratio. It’s intricately thought-out yet convenient to use, ensuring a powerful presentation every time.

Cognify – AI PowerPoint Presentation

The Cognify PowerPoint template provides a robust and user-friendly slideshow for AI-related presentations. Designed with over 30 unique slides that are easily customizable, this PowerPoint template fits a 16:9 widescreen ratio and includes picture placeholders.

Rebotech – Artificial Intelligence PowerPoint Template

This PowerPoint template offers a sleek, modern design for a variety of AI-related presentations. It includes a unique layout with editable infographics, graphs, and icons, suitable for market reviews, funding pitches, product analysis, and more. Additionally, it boasts a 16:9 wide-screen ratio and features like picture placeholders, vector icons, and easy editability.

Cyborge – AI PowerPoint Template

The Cyborge is an advanced, professionally styled PowerPoint template ideal for future technology presentations. It includes 30 unique, easy-to-use slides, presented in a trending style theme. The template features various slide layouts, including cover, portfolio, product, and contact slides, and a widescreen ratio of 16:9. All of these elements combine to create a presentation that will easily attract and engage your audience.

Metaspace – AI, Virtual Reality and Mataverse PPT

Metaspace is an adaptable presentation template perfect for a range of purposes including AI, digital marketing, startups, and more. With 36 unique slides and over 1,000 easy-to-edit icons, this PowerPoint resource prioritizes simplicity and creativity. Its versatile design, equipped with a 16:9 widescreen ratio and drag-and-drop functionality, makes it a standout choice for your presentation needs.

DeepMind – Artificial Intelegence PowerPoint Template

This PowerPoint template is a valuable resource for AI startups and tech businesses. It’s a time saver, allowing users to focus on the content while providing a visually appealing design. This template features resizable and editable graphics, free web fonts, and an easily editable format for creating presentations with ease.

Metaficial – Artificial Intelligence PowerPoint Template

The Metaficial is a PowerPoint template perfect for creating AI-themed slideshows. With its customizable features including 35 unique slides, resizable graphics, and drag-and-drop image placeholders, crafting a presentation to your liking is seamless. It also includes a variety of infographics and templates for diagrams, tables, and charts.

Artific – Artificial Intelligence Presentation

Artific is an AI-themed PowerPoint presentation template ideal for any Artificial Intelligence and technology-related content. The modern, sleek, and futuristic pre-designed slides can easily be customized using PowerPoint or Google Slides. It offers 25 unique slides in a 16:9 widescreen ratio with image placeholders, editable icons, and elements, all resizable and detachable without losing quality.

Ashoiy – AI Technology PowerPoint Template

Ashoiy is an ultra-modern, professionally designed set of slides for a wide range of presentations such as business, branding, and advertising. Boasting over 25 unique slides with high attention to detail, the template features a clean, multipurpose design built on master slides, with easy-to-use vector icons and changeable colors.

Best Free AI PowerPoint Templates

Artificial intelligence (ai) startup business plan free ppt.

This is a free PowerPoint template you can use to create presentations related to artificial intelligence and technology. It’s especially ideal for new startups to create a business plan slideshow. The template has 35 unique slides.

Artificial Intelligence (AI) Technology Project Proposal Free PPT

Create your AI-related project proposals in style using this free PowerPoint template. It comes with 29 unique slides with dark and creative layouts. It also uses free fonts and an icon pack.

AI Technology Thesis Free PowerPoint Template

This free PowerPoint template is designed to help you create more engaging and effective slideshows for your AI-related thesis defense. It has 35 unique slides to choose from and has a fully customizable slide design.

Cyber-Futuristic AI Technology Thesis Free PPT

Another free PowerPoint template for your AI-related thesis defense. This template has a much more modern and colorful design with lots of space for images. There are 25 slides in this template.

AI Marketing Free AI PowerPoint Template

This PowerPoint template comes with a multipurpose design featuring more than 25 slides for creating various AI-related presentations. You can fully customize each slide to your preference as well.

From the world wide web to AI: 11 technology milestones that changed our lives

The world wide web is a key technological milestone in the past 40 years. Image:  Unsplash/Ales Nesetril

.chakra .wef-1c7l3mo{-webkit-transition:all 0.15s ease-out;transition:all 0.15s ease-out;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;outline:none;color:inherit;}.chakra .wef-1c7l3mo:hover,.chakra .wef-1c7l3mo[data-hover]{-webkit-text-decoration:underline;text-decoration:underline;}.chakra .wef-1c7l3mo:focus,.chakra .wef-1c7l3mo[data-focus]{box-shadow:0 0 0 3px rgba(168,203,251,0.5);} Stephen Holroyd

.chakra .wef-9dduvl{margin-top:16px;margin-bottom:16px;line-height:1.388;font-size:1.25rem;}@media screen and (min-width:56.5rem){.chakra .wef-9dduvl{font-size:1.125rem;}} Explore and monitor how .chakra .wef-15eoq1r{margin-top:16px;margin-bottom:16px;line-height:1.388;font-size:1.25rem;color:#F7DB5E;}@media screen and (min-width:56.5rem){.chakra .wef-15eoq1r{font-size:1.125rem;}} Artificial Intelligence is affecting economies, industries and global issues

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Stay up to date:, emerging technologies.

• It’s been 40 years since the launch of the Apple Macintosh personal computer.
• Since then, technological innovation has accelerated – here are some of the most notable tech milestones over the past four decades.
• The World Economic Forum’s EDISON Alliance aims to digitally connect 1 billion people to essential services like healthcare, education and finance by 2025.

On 24 January 1984, Apple unveiled the Macintosh 128K and changed the face of personal computers forever.

Steve Jobs’ compact, user-friendly computer introduced the graphical user interface to the world, marking a pivotal moment in the evolution of personal technology.

Since that day, the rate of technological innovation has exploded, with developments in computing, communication, connectivity and machine learning expanding at an astonishing rate.

Here are some of the key technological milestones that have changed our lives over the past 40 years.

Have you read?

9 ways ai is helping tackle climate change, driving trust: paving the road for autonomous vehicles, these are the top 10 emerging technologies of 2023: here's how they can impact the world, 1993: the world wide web.

Although the internet’s official birthday is often debated, it was the invention of the world wide web that drove the democratization of information access and shaped the modern internet we use today.

Created by British scientist Tim Berners-Lee, the World Wide Web was launched to the public in 1993 and brought with it the dawn of online communication, e-commerce and the beginning of the digital economy.

Despite the enormous progress since its invention, 2.6 billion people still lack internet access and global digital inclusion is considered a priority. The World Economic Forum’s EDISON Alliance aims to bridge this gap and digitally connect 1 billion people to essential services like healthcare, education and finance by 2025.

1997: Wi-Fi

The emergence of publicly available Wi-Fi in 1997 changed the face of internet access – removing the need to tether to a network via a cable. Without Wi-Fi, the smartphone and the ever-present internet connection we’ve come to rely on, wouldn’t have been possible, and it has become an indispensable part of our modern, connected world.

1998: Google

The launch of Google’s search engine in 1998 marked the beginning of efficient web search, transforming how people across the globe accessed and navigated online information . Today, there are many others to choose from – Bing, Yahoo!, Baidu – but Google remains the world’s most-used search engine.

2004: Social media

Over the past two decades, the rise of social media and social networking has dominated our connected lives. In 2004, MySpace became the first social media site to reach one million monthly active users. Since then, platforms like Facebook, Instagram and TikTok have reshaped communication and social interaction , nurturing global connectivity and information sharing on an enormous scale, albeit not without controversy .

2007: The iPhone

More than a decade after the first smartphone had been introduced, the iPhone redefined mobile technology by combining a phone, music player, camera and internet communicator in one sleek device. It set new standards for smartphones and ultimately accelerated the explosion of smartphone usage we see across the planet today.

2009: Bitcoin

The foundations for modern digital payments were laid in the late 1950s with the introduction of the first credit and debit cards, but it was the invention of Bitcoin in 2009 that set the stage for a new era of secure digital transactions. The first decentralized cryptocurrency, Bitcoin introduced a new form of digital payment system that operates independently of traditional banking systems. Its underlying technology, blockchain, revolutionized the concept of digital transactions by providing a secure, transparent, and decentralized method for peer-to-peer payments. Bitcoin has not only influenced the development of other cryptocurrencies but has also sparked discussions about the future of money in the digital age.

2014: Virtual reality

2014 was a pivotal year in the development of virtual reality (VR) for commercial applications. Facebook acquired the Oculus VR company for $2 billion and kickstarted a drive for high-quality VR experiences to be made accessible to consumers. Samsung and Sony also announced VR products, and Google released the now discontinued Cardboard – a low-cost, do-it-yourself viewer for smartphones. The first batch of Oculus Rift headsets began shipping to consumers in 2016.

2015: Autonomous vehicles

Autonomous vehicles have gone from science fiction to science fact in the past two decades, and predictions suggest that almost two-thirds of registered passenger cars worldwide will feature partly-assisted driving and steering by 2025 . In 2015, the introduction of Tesla’s Autopilot brought autonomous features to consumer vehicles, contributing to the mainstream adoption of self-driving technology.

2019: Quantum computing

A significant moment in the history of quantum computing was achieved in October 2019 when Google’s Sycamore processor demonstrated “quantum supremacy” by solving a complex problem faster than the world’s most powerful supercomputers. Quantum technologies can be used in a variety of applications and offer transformative impacts across industries. The World Economic Forum’s Quantum Economy Blueprint provides a framework for value-led, democratic access to quantum resources to help ensure an equitable global distribution and avoid a quantum divide.

2020: The COVID-19 pandemic

The COVID-19 pandemic accelerated digital transformation on an unprecedented scale . With almost every aspect of human life impacted by the spread of the virus – from communicating with loved ones to how and where we work – the rate of innovation and uptake of technology across the globe emphasized the importance of remote work, video conferencing, telemedicine and e-commerce in our daily lives.

In response to the uncertainties surrounding generative AI and the need for robust AI governance frameworks to ensure responsible and beneficial outcomes for all, the Forum’s Centre for the Fourth Industrial Revolution (C4IR) has launched the AI Governance Alliance .

The Alliance will unite industry leaders, governments, academic institutions, and civil society organizations to champion responsible global design and release of transparent and inclusive AI systems.

2022: Artificial intelligence

Artificial intelligence (AI) technology has been around for some time and AI-powered consumer electronics, from smart home devices to personalized assistants, have become commonplace. However, the emergence of mainstream applications of generative AI has dominated the sector in recent years.

In 2022, OpenAI unveiled its chatbot, ChatGPT. Within a week, it had gained over one million users and become the fastest-growing consumer app in history . In the same year, DALL-E 2, a text-to-image generative AI tool, also launched.

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License and Republishing

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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Presenting our Artificial Intelligence Machine Learning Deep Learning PPT PowerPoint Presentation Slide Templates. This is a completely adaptable PPT slide that allows you to add images, charts, icons, tables, and animation effects according to your requirements. Create and edit your text in this 100% customizable slide. You can change the orientation of any element in your presentation according to your liking. The slide is available in both 4:3 and 16:9 aspect ratios. This PPT presentation is also compatible with Google Slides.

Introduction to Artificial Intelligence is for the mid level managers giving information about what is AI, AI levels, types of AI, where AI is used. You can also know the difference between AI vs Machine learning vs Deep learning to understand expert system in a better way for business growth.

Enthrall your audience with this ChatGPT IT Powerpoint Presentation Slides. Increase your presentation threshold by deploying this well-crafted template. It acts as a great communication tool due to its well-researched content. It also contains stylized icons, graphics, visuals etc, which make it an immediate attention-grabber. Comprising seventy two slides, this complete deck is all you need to get noticed. All the slides and their content can be altered to suit your unique business setting. Not only that, other components and graphics can also be modified to add personal touches to this prefabricated set.

Machine Learning ML Overview Algorithms Use Cases and Applications is for the mid level managers giving information about Machine Learning, how Machine Learning works, Machine Learning algorithms and its use cases. You can also learn the difference between Machine learning vs Traditional programming to understand how to implement machine learning in a better way for business growth.

Presenting artificial intelligence presentation slides. This deck comprises of total of 50 slides. Each slide includes professional visuals with an appropriate content. These templates have been designed keeping the customers requirement in mind. This complete presentation covers all the design elements such as layout, diagrams, icons, and more. This deck has been crafted after an extensive research. You can easily customize each template. Edit the color, text, icon, and font size as per your requirement. Easy to download. Compatible with all screen types and monitors. Supports Google Slides. Premium Customer Support available.

Enthrall your audience with this Regenerative AI Powerpoint Presentation Slides. Increase your presentation threshold by deploying this well-crafted template. It acts as a great communication tool due to its well-researched content. It also contains stylized icons, graphics, visuals etc, which make it an immediate attention-grabber. Comprising sixty nine slides, this complete deck is all you need to get noticed. All the slides and their content can be altered to suit your unique business setting. Not only that, other components and graphics can also be modified to add personal touches to this prefabricated set.

This complete deck covers various topics and highlights important concepts. It has PPT slides which cater to your business needs. This complete deck presentation emphasizes Prompt Engineering For Effective Interaction With AI Powerpoint Presentation Slides and has templates with professional background images and relevant content. This deck consists of total of one hundred one slides. Our designers have created customizable templates, keeping your convenience in mind. You can edit the color, text and font size with ease. Not just this, you can also add or delete the content if needed. Get access to this fully editable complete presentation by clicking the download button below.

Presenting this set of slides with name - Artificial Intelligence Overview Powerpoint Presentation Slides. This complete deck with thirty-seven slides consists of all sorts of editable templates, charts and graphs, overviews, analysis templates. It can be edited and saved in formats like PDF, JPG, and PNG depending upon your needs and requirements. It is also available in two screen sizes- standard screen and widescreen without any fear of pixelation.

EduDecks are professionally-created comprehensive decks that provide complete coverage of the subject under discussion. These are also innovatively-designed for a powerful learning experience and maximum retention

Presenting this set of slides with name - Artificial Intelligence For Digital Transformation Powerpoint Presentation Slides. This PPT deck displays eighteen slides with in-depth research. This template is compatible with Google Slides, which makes it accessible at once. Can be converted into various formats like PDF, JPG, and PNG. The slide is easily available in both 4:3 and 16:9 aspect ratio. You can change the colors, fonts, font size, and font types of the template as per the business requirements.

Presenting Training Deck on Building an AI-Driven Future Essential Strategies for Business Success. This deck comprises of 72 slides. Each slide is well crafted and designed by our PowerPoint experts. This PPT presentation is thoroughly researched by the experts, and every slide consists of appropriate content. All slides are customizable. You can add or delete the content as per your need. Not just this, you can also make the required changes in the charts and graphs. Download this professionally designed business presentation, add your content, and present it confidently.

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Presenting this set of slides with name - Technology Driven Process Powerpoint Presentation Slides. This deck has a total of thirty-nine slides. Our designers have created customizable templates for your convenience. You can make the required changes in the templates like color, text and font size. Other than this, content can be added or deleted from the slide as per the requirement.

Differences between Machine Learning ML Artificial Intelligence AI and Deep Learning DL is for the mid level managers to give information about what is AI, what is Machine Learning, what is deep learning, Machine learning process. You can also know the difference between Machine learning and Deep learning to understand AI, ML, and DL in a better way for business growth.

Presenting Training Deck on Deep Learning Mastering the Fundamentals. This deck comprises of 104 slides. Each slide is well crafted and designed by our PowerPoint experts. This PPT presentation is thoroughly researched by the experts, and every slide consists of appropriate content. All slides are customizable. You can add or delete the content as per your need. Not just this, you can also make the required changes in the charts and graphs. Download this professionally designed business presentation, add your content, and present it with confidence.

Deliver an informational PPT on various topics by using this Recommender Systems IT Powerpoint Presentation Slides. This deck focuses and implements best industry practices, thus providing a birds-eye view of the topic. Encompassed with ninty seven slides, designed using high-quality visuals and graphics, this deck is a complete package to use and download. All the slides offered in this deck are subjective to innumerable alterations, thus making you a pro at delivering and educating. You can modify the color of the graphics, background, or anything else as per your needs and requirements. It suits every business vertical because of its adaptable layout.

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SlideTeam presents an Artificial Intelligence Powerpoint Presentation Slide Template Complete Deck. There are 99 visually-stunning PPT slides in this 100% custom complete deck. Edit text, font, colors, background, orientation, shapes, and patterns as desired. Change the PowerPoint format into PDF, PNG, or JPG as and when needed. Use standard and widescreen resolutions to view this presentation. It is compatible with Google Slides.

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SlideTeam presents Artificial Intelligence And Machine Learning Powerpoint Presentation Slides. This complete deck is replete with 98 PPT templates. Each PowerPoint slide is made up of 100% modifiable design elements. Customize text, font, colors, shapes, orientation, patterns, and background. Convert the file format into PDF, PNG, or JPG as and when suitable. Use Google Slides for easy access. It is compatible with standard and widescreen resolutions.

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Provide your investors essential insights into your project and company with this influential Artificial Intelligence Pitch Deck Ppt Template. This is an in-depth pitch deck PPT template that covers all the extensive information and statistics of your organization. From revenue models to basic statistics, there are unique charts and graphs added to make your presentation more informative and strategically advanced. This gives you a competitive edge and ample amount of space to showcase your brands USP. Apart from this, all the thirty three slides added to this deck, helps provide a breakdown of various facets and key fundamentals. Including the history of your company, marketing strategies, traction, etc. The biggest advantage of this template is that it is pliable to any business domain be it e-commerce, IT revolution, etc, to introduce a new product or bring changes to the existing one. Therefore, download this complete deck now in the form of PNG, JPG, or PDF.

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What’s the future of AI?

We’re in the midst of a revolution. Just as steam power, mechanized engines, and coal supply chains transformed the world in the 18th century, AI technology is currently changing the face of work, our economies, and society as we know it. We don’t know exactly what the future will look like. But we do know that these seven technologies will play a big role.

What is AI (artificial intelligence)?

What is generative ai.

What is artificial general intelligence (AGI)?

What is deep learning.

What is prompt engineering?

What is machine learning.

What is tokenization?

How to Make a Presentation with AI (Tips, Tools & Templates)

Discover how AI-powered presentations revolutionize communication, captivate audiences, and provide data-driven insights. Elevate your presentations with AI.

Jackie Plaza

6 minute read

Short answer

Why should I make a presentation with AI?

• Captivate your audience with interactive experiences
• Personalize content based on preferences and demographics
• Gain data-driven insights for improved communication outcomes
• Enhance impact with visually appealing multimedia
• Adapt dynamically to audience feedback in real-time
• Showcase innovation and save time with AI-powered tools

AI presentation makers can now make better presentations than you

Traditional presentations often fail to captivate audiences, lacking personalization and interactivity. This results in disengaged listeners and limited effectiveness in conveying information.

Imagine sitting through a boring presentation where the content feels generic, irrelevant, and fails to address your specific interests and needs. It becomes challenging to stay engaged and absorb the presented information.

Fortunately, with the advent of AI technology, a new era of presentations has emerged, revolutionizing communication.

AI-powered presentations can captivate audiences, tailor content to individual preferences, and provide valuable data-driven insights.

This article will explore how AI technology has transformed presentations, enhancing engagement, personalization, and the overall communication experience.

Discover the exciting world of AI-powered presentations that are dynamic, interactive, and tailored to captivate and inform your audience like never before.

The evolution of presentations

Throughout history, presentations have undergone a significant evolution. Traditionally, presentations were limited to static slides and monotonous delivery methods that often failed to captivate audiences.

The repetitive nature of these presentations made it challenging to engage listeners and convey information effectively.

However, a paradigm shift has occurred in the world of presentations .

AI-powered presentations have emerged as a game-changer, revolutionizing the way information is communicated and received.

AI technology has introduced exciting possibilities for transforming presentations into engaging and immersive experiences.

These advancements in AI-powered presentations have revolutionized how information is communicated and received.

Presentations are no longer limited to static, one-size-fits-all approaches but have transformed into personalized, interactive, and visually engaging experiences.

The benefits of AI-powered presentations are undeniable.

They have transformed presentations from static and passive experiences into interactive and personalized journeys.

Stage 1: Personalized presentations

AI-powered presentations analyze audience data to tailor content and delivery based on individual preferences, demographics, and behaviors. This customization ensures that each audience member receives a presentation that meets their specific needs and interests.

Stage 2: Interactive presentations

Natural language processing enables presenters to create digital presentations that respond to audience inputs and questions in real-time. This two-way communication fosters active participation, engagement, and a sense of connection between the presenter and the audience.

Here's Zuora's best sales deck ever magically recreated as an interactive web story with AI:

Stage 3: AI-generated multimedia

AI algorithms can generate visually appealing visuals, animations, and videos that enhance the impact of the presentation. These multimedia elements captivate the audience's attention and convey complex ideas and concepts effectively.

Stage 4: Adaptive presentations

AI algorithms continuously analyze audience feedback and reactions during the presentation.

This real-time analysis allows presenters to dynamically adjust the presentation's direction, content, and delivery to ensure relevance and resonance with the audience.

Adaptive presentations lead to improved engagement and communication outcomes.

Enhancing engagement through AI

One of the key benefits of AI-powered presentations is the ability to captivate audiences through interactive experiences.

Natural language processing enables presenters to create dynamic presentations that respond to audience inputs and questions in real time.

This technology allows for seamless interactions and fosters a sense of participation , keeping the audience engaged throughout the session.

Additionally, AI technology empowers presenters to incorporate visually appealing multimedia elements generated by AI algorithms.

These visuals can be tailored to match the tone and context of the presentation, creating a visually stunning, effective, and impactful presentation for the audience.

Moreover, AI-powered presentations can adapt their content based on audience feedback and reactions .

This adaptability ensures that presentations remain relevant and resonate with the audience, resulting in increased engagement and improved communication outcomes.

Personalizing presentations with AI

AI technology also enables presenters to personalize presentations, tailoring content and delivery based on individual audience members' preferences and characteristics.

Leveraging AI algorithms empowers presenters to analyze audience data to gain insights into their preferences, demographics, and behavioral patterns.

Armed with this information, presenters can customize content, examples, and anecdotes to make presentations more relatable and relevant to each audience member.

In addition, AI-powered recommendation systems can suggest specific content and topics based on an individual's past interactions and interests.

These personalized recommendations create a unique presentation experience for each attendee, fostering a deeper connection and increasing the likelihood of retaining information.

However, personalization in AI-powered presentations raises ethical considerations. Balancing customization with privacy concerns is crucial.

Presenters must obtain explicit consent for collecting and analyzing audience data and adhere to strict data protection guidelines to safeguard individuals' privacy.

Harnessing data-driven insights

AI-powered presentations leverage data analytics to collect and analyze audience data during the presentation.

By monitoring audience behavior and interaction patterns, presenters can gain valuable insights into their preferences, attention spans, and areas of interest.

These insights can refine future presentations, improving their effectiveness and resonance with the audience.

Over 80% of top organizations incorporate various forms of AI technology into their online marketing endeavors.

Data-driven feedback and analytics enable presenters to identify strengths and weaknesses in their presentations.

Analyzing audience engagement, comprehension, and satisfaction data lets presenters make data-informed decisions to optimize their delivery and content.

This iterative approach to presentations ensures continuous improvement and maximizes communication impact.

Nevertheless, data privacy is a paramount concern when harnessing data-driven insights in AI-powered presentations.

Presenters must handle audience data responsibly, anonymize sensitive information, and provide transparent communication about the purpose and use of collected data.

Overcoming challenges and ethical considerations

As with any AI application, challenges and ethical considerations must be addressed when using AI in presentations.

Biases and limitations in AI algorithms can inadvertently influence the content and delivery of presentations.

It is essential for presenters to thoroughly vet AI algorithms, test their performance across diverse audience demographics, and actively mitigate any biases that may arise.

Transparency and accountability in AI algorithms ensure that presentations are fair, unbiased, and objective.

Another ethical consideration is the use of AI to influence the audience's emotions and decision s.

While AI-powered presentations have the potential to evoke emotions and shape opinions, presenters must exercise caution and responsibility in utilizing this capability.

They should be transparent about using AI-generated emotional content and avoid manipulating emotions for unethical purposes.

To ensure the responsible and ethical use of AI in presentations, strategies such as clear guidelines, ethical frameworks, and independent auditing can be implemented.

Collaboration between AI developers, presenters, and stakeholders is essential to establish standards and practices that prioritize ethical considerations and protect the interests of the audience.

Future possibilities and impact of AI-powered presentations

The potential for AI-powered presentations extends far beyond the current capabilities. As AI technology continues to advance, we can expect further enhancements and trends in this field.

For example, AI algorithms may become even more adept at understanding and interpreting audience emotions and non-verbal cues, leading to more sophisticated and emotionally intelligent presentations.

Moreover, AI-powered presentations have significant implications for various sectors and industries.

In education, for instance, personalized AI-powered presentations can revolutionize the learning experience, catering to each student's individual needs and optimizing knowledge retention.

In business settings, AI-powered presentations can enhance sales pitches , customer interactions, and training programs, resulting in improved communication and business outcomes.

A recent Gallup survey found that customers who are fully engaged demonstrate significant advantages compared to the average customer. These advantages include a 23% increase in share of wallet, profitability, revenue, and growth in customer relationships.

However, it is important to strike a balance between human creativity and AI automation in presentations.

While AI can provide valuable support and augmentation, the unique human qualities of storytelling, empathy, and adaptability remain irreplaceable.

Presenters should leverage AI as a tool to enhance their skills and creativity, rather than relying solely on automation.

Future landscape of communication with AI-powered presentations

Looking ahead, AI-powered presentations have the potential to become the new norm in communication. As AI technology advances and becomes more accessible, the widespread adoption of AI-powered presentation tools and platforms is likely.

We can envision a future where presentations seamlessly integrate AI-generated visuals, interactive features, and personalized content to create captivating and impactful experiences.

Furthermore, AI-powered presentations will contribute to a data-driven approach to communication. Presenters will rely on real-time analytics and audience insights to refine their presentations, improving their effectiveness and engaging communication outcomes.

If you're wondering what you can do with a communications degree , the integration of AI technology in presentations opens up new possibilities for professionals in this field.

AI-powered presentations allow communication specialists to leverage data-driven insights and personalized approaches, creating impactful and tailored messages that resonate with diverse audiences.

The fusion of AI and human expertise will lead to a powerful synergy, enabling presenters to deliver content that resonates with audiences on a deeper level.

How to make outstanding presentations with AI

If you're eager to incorporate AI into your presentations and leverage its benefits, here are some steps to get you started:

1) Identify your objectives

Determine the specific goals and objectives you want to achieve with your presentations.

Whether it's enhancing engagement, personalizing content, creating a marketing deck , or harnessing data-driven insights, having clarity on your objectives will guide your AI integration process.

2) Research AI-powered presentation tools

Explore the various AI-powered presentation tools available in the market. Look for tools that align with your objectives and offer the features you need, such as natural language processing, interactive capabilities, adaptive content, and data analytics.

3) Evaluate tool features and ease of use

Assess the features, functionalities, and user-friendliness of the AI-powered presentation tools you shortlist.

Consider factors such as ease of creating and editing presentations, customization options, collaboration features, and compatibility with your existing presentation software or platforms.

4) Choose a tool and familiarize yourself with it

Once you have selected a suitable AI-powered presentation tool, take the time to familiarize yourself with its interface, features, and functionalities.

Explore tutorials, user guides, and online resources provided by the tool's developers to gain a comprehensive understanding of how to make the most of the AI capabilities.

5) Experiment and practice

Start experimenting with the AI-powered features of the chosen tool.

Play around with the customization options, interactive elements, multimedia integration, and adaptive content features. Practice creating and delivering presentations using AI to gain confidence and refine your skills.

6) Seek inspiration and learn from others

Explore examples of AI-powered presentations created by other professionals. Attend webinars , workshops, or conferences that focus on AI in presentations to learn from industry experts and gain insights into best practices.

7) Collect and analyze audience feedback

As you start incorporating AI into your presentations, gather feedback from your audience.

Use surveys, polls, or interactive features within the presentation tool to collect data on audience engagement, preferences, and reactions. Analyze this data to refine and improve your future presentations.

8) Continuously update your skills

AI technology is rapidly evolving, and new tools and features are constantly being developed.

Stay updated with the latest advancements in AI-powered presentations by following industry news, joining relevant communities or forums, and engaging in continuous learning.

By following these steps, you can embark on your journey of creating impactful presentations with AI. Remember to tailor the use of AI to your specific objectives and always keep the audience at the forefront of your presentation design.

If you're ready to start making presentations with AI, there are several top technology tools available in the market that can help you harness the power of AI and enhance your communication.

Explore AI presentation making tools

StoryDoc : This AI-powered presentation platform allows you to create interactive and immersive presentations. It offers features such as automated content generation, data analytics, and audience engagement tools, enabling you to deliver captivating and data-driven presentations.

PowerPoint Designer : Microsoft PowerPoint offers a built-in feature called Designer. It uses AI algorithms to suggest design ideas and layout options based on the content of your slides.

SlideBot : This tool is an AI-powered presentation tool that automates the slide creation process. Analyzing your text using natural language processing generates visually appealing slides with minimal effort.

Emaze : This cloud-based flip-book style presentation platform incorporates AI-powered features to enhance engagement and visual appeal. It provides automatic design suggestions, slide transitions, and interactive elements, allowing you to create captivating and interactive presentations.

By exploring these tools and incorporating AI-powered features into your presentations, you can elevate your communication and deliver more impactful messages to your audience.

Create a presentation from template with AI

Some AI presentation software were built to make presentations faster, but we built ous to make it fast but also better. Grab a design template and let our AI guide you to the best outcome possible.

All these presentation templates were tried and tested for any device and screen size. These templates were built based on best practices and real-world data from over 100,000 reading sessions . They were built scientifically for engagement and conversion.

Grab a template!

Hi, I’m Jackie, Creative Marketing Specialist at Storydoc, I write on everything business presentations. I love to research and bring to light critical information that helps marketing, sales, and design teams get better results with their collateral.

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• Open access
• Published: 18 April 2024

Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research

• James Shaw 1 , 13 ,
• Joseph Ali 2 , 3 ,
• Caesar A. Atuire 4 , 5 ,
• Phaik Yeong Cheah 6 ,
• Armando Guio Español 7 ,
• Judy Wawira Gichoya 8 ,
• Adrienne Hunt 9 ,
• Daudi Jjingo 10 ,
• Katherine Littler 9 ,
• Daniela Paolotti 11 &
• Effy Vayena 12  

BMC Medical Ethics volume  25 , Article number:  46 ( 2024 ) Cite this article

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The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022.

We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships.

Conclusions

The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

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Introduction

The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice [ 1 , 2 , 3 ]. Beyond the growing number of AI applications being implemented in health care, capabilities of AI models such as Large Language Models (LLMs) expand the potential reach and significance of AI technologies across health-related fields [ 4 , 5 ]. Discussion about effective, ethical governance of AI technologies has spanned a range of governance approaches, including government regulation, organizational decision-making, professional self-regulation, and research ethics review [ 6 , 7 , 8 ]. In this paper, we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health research, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Although applications of AI for research, health care, and public health are diverse and advancing rapidly, the insights generated at the forum remain highly relevant from a global health perspective. After summarizing important context for work in this domain, we highlight categories of ethical issues emphasized at the forum for attention from a research ethics perspective internationally. We then outline strategies proposed for research, innovation, and governance to support more ethical AI for global health.

In this paper, we adopt the definition of AI systems provided by the Organization for Economic Cooperation and Development (OECD) as our starting point. Their definition states that an AI system is “a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy” [ 9 ]. The conceptualization of an algorithm as helping to constitute an AI system, along with hardware, other elements of software, and a particular context of use, illustrates the wide variety of ways in which AI can be applied. We have found it useful to differentiate applications of AI in research as those classified as “AI systems for discovery” and “AI systems for intervention”. An AI system for discovery is one that is intended to generate new knowledge, for example in drug discovery or public health research in which researchers are seeking potential targets for intervention, innovation, or further research. An AI system for intervention is one that directly contributes to enacting an intervention in a particular context, for example informing decision-making at the point of care or assisting with accuracy in a surgical procedure.

The mandate of the GFBR is to take a broad view of what constitutes research and its regulation in global health, with special attention to bioethics in Low- and Middle- Income Countries. AI as a group of technologies demands such a broad view. AI development for health occurs in a variety of environments, including universities and academic health sciences centers where research ethics review remains an important element of the governance of science and innovation internationally [ 10 , 11 ]. In these settings, research ethics committees (RECs; also known by different names such as Institutional Review Boards or IRBs) make decisions about the ethical appropriateness of projects proposed by researchers and other institutional members, ultimately determining whether a given project is allowed to proceed on ethical grounds [ 12 ].

However, research involving AI for health also takes place in large corporations and smaller scale start-ups, which in some jurisdictions fall outside the scope of research ethics regulation. In the domain of AI, the question of what constitutes research also becomes blurred. For example, is the development of an algorithm itself considered a part of the research process? Or only when that algorithm is tested under the formal constraints of a systematic research methodology? In this paper we take an inclusive view, in which AI development is included in the definition of research activity and within scope for our inquiry, regardless of the setting in which it takes place. This broad perspective characterizes the approach to “research ethics” we take in this paper, extending beyond the work of RECs to include the ethical analysis of the wide range of activities that constitute research as the generation of new knowledge and intervention in the world.

Ethical governance of AI in global health

The ethical governance of AI for global health has been widely discussed in recent years. The World Health Organization (WHO) released its guidelines on ethics and governance of AI for health in 2021, endorsing a set of six ethical principles and exploring the relevance of those principles through a variety of use cases. The WHO guidelines also provided an overview of AI governance, defining governance as covering “a range of steering and rule-making functions of governments and other decision-makers, including international health agencies, for the achievement of national health policy objectives conducive to universal health coverage.” (p. 81) The report usefully provided a series of recommendations related to governance of seven domains pertaining to AI for health: data, benefit sharing, the private sector, the public sector, regulation, policy observatories/model legislation, and global governance. The report acknowledges that much work is yet to be done to advance international cooperation on AI governance, especially related to prioritizing voices from Low- and Middle-Income Countries (LMICs) in global dialogue.

One important point emphasized in the WHO report that reinforces the broader literature on global governance of AI is the distribution of responsibility across a wide range of actors in the AI ecosystem. This is especially important to highlight when focused on research for global health, which is specifically about work that transcends national borders. Alami et al. (2020) discussed the unique risks raised by AI research in global health, ranging from the unavailability of data in many LMICs required to train locally relevant AI models to the capacity of health systems to absorb new AI technologies that demand the use of resources from elsewhere in the system. These observations illustrate the need to identify the unique issues posed by AI research for global health specifically, and the strategies that can be employed by all those implicated in AI governance to promote ethically responsible use of AI in global health research.

RECs and the regulation of research involving AI

RECs represent an important element of the governance of AI for global health research, and thus warrant further commentary as background to our paper. Despite the importance of RECs, foundational questions have been raised about their capabilities to accurately understand and address ethical issues raised by studies involving AI. Rahimzadeh et al. (2023) outlined how RECs in the United States are under-prepared to align with recent federal policy requiring that RECs review data sharing and management plans with attention to the unique ethical issues raised in AI research for health [ 13 ]. Similar research in South Africa identified variability in understanding of existing regulations and ethical issues associated with health-related big data sharing and management among research ethics committee members [ 14 , 15 ]. The effort to address harms accruing to groups or communities as opposed to individuals whose data are included in AI research has also been identified as a unique challenge for RECs [ 16 , 17 ]. Doerr and Meeder (2022) suggested that current regulatory frameworks for research ethics might actually prevent RECs from adequately addressing such issues, as they are deemed out of scope of REC review [ 16 ]. Furthermore, research in the United Kingdom and Canada has suggested that researchers using AI methods for health tend to distinguish between ethical issues and social impact of their research, adopting an overly narrow view of what constitutes ethical issues in their work [ 18 ].

The challenges for RECs in adequately addressing ethical issues in AI research for health care and public health exceed a straightforward survey of ethical considerations. As Ferretti et al. (2021) contend, some capabilities of RECs adequately cover certain issues in AI-based health research, such as the common occurrence of conflicts of interest where researchers who accept funds from commercial technology providers are implicitly incentivized to produce results that align with commercial interests [ 12 ]. However, some features of REC review require reform to adequately meet ethical needs. Ferretti et al. outlined weaknesses of RECs that are longstanding and those that are novel to AI-related projects, proposing a series of directions for development that are regulatory, procedural, and complementary to REC functionality. The work required on a global scale to update the REC function in response to the demands of research involving AI is substantial.

These issues take greater urgency in the context of global health [ 19 ]. Teixeira da Silva (2022) described the global practice of “ethics dumping”, where researchers from high income countries bring ethically contentious practices to RECs in low-income countries as a strategy to gain approval and move projects forward [ 20 ]. Although not yet systematically documented in AI research for health, risk of ethics dumping in AI research is high. Evidence is already emerging of practices of “health data colonialism”, in which AI researchers and developers from large organizations in high-income countries acquire data to build algorithms in LMICs to avoid stricter regulations [ 21 ]. This specific practice is part of a larger collection of practices that characterize health data colonialism, involving the broader exploitation of data and the populations they represent primarily for commercial gain [ 21 , 22 ]. As an additional complication, AI algorithms trained on data from high-income contexts are unlikely to apply in straightforward ways to LMIC settings [ 21 , 23 ]. In the context of global health, there is widespread acknowledgement about the need to not only enhance the knowledge base of REC members about AI-based methods internationally, but to acknowledge the broader shifts required to encourage their capabilities to more fully address these and other ethical issues associated with AI research for health [ 8 ].

Although RECs are an important part of the story of the ethical governance of AI for global health research, they are not the only part. The responsibilities of supra-national entities such as the World Health Organization, national governments, organizational leaders, commercial AI technology providers, health care professionals, and other groups continue to be worked out internationally. In this context of ongoing work, examining issues that demand attention and strategies to address them remains an urgent and valuable task.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, REC members and other actors to engage with challenges and opportunities specifically related to research ethics. Each year the GFBR meeting includes a series of case studies and keynotes presented in plenary format to an audience of approximately 100 people who have applied and been competitively selected to attend, along with small-group breakout discussions to advance thinking on related issues. The specific topic of the forum changes each year, with past topics including ethical issues in research with people living with mental health conditions (2021), genome editing (2019), and biobanking/data sharing (2018). The forum is intended to remain grounded in the practical challenges of engaging in research ethics, with special interest in low resource settings from a global health perspective. A post-meeting fellowship scheme is open to all LMIC participants, providing a unique opportunity to apply for funding to further explore and address the ethical challenges that are identified during the meeting.

In 2022, the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations (both short and long form) reporting on specific initiatives related to research ethics and AI for health, and 16 governance presentations (both short and long form) reporting on actual approaches to governing AI in different country settings. A keynote presentation from Professor Effy Vayena addressed the topic of the broader context for AI ethics in a rapidly evolving field. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. The 2-day forum addressed a wide range of themes. The conference report provides a detailed overview of each of the specific topics addressed while a policy paper outlines the cross-cutting themes (both documents are available at the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ ). As opposed to providing a detailed summary in this paper, we aim to briefly highlight central issues raised, solutions proposed, and the challenges facing the research ethics community in the years to come.

In this way, our primary aim in this paper is to present a synthesis of the challenges and opportunities raised at the GFBR meeting and in the planning process, followed by our reflections as a group of authors on their significance for governance leaders in the coming years. We acknowledge that the views represented at the meeting and in our results are a partial representation of the universe of views on this topic; however, the GFBR leadership invested a great deal of resources in convening a deeply diverse and thoughtful group of researchers and practitioners working on themes of bioethics related to AI for global health including those based in LMICs. We contend that it remains rare to convene such a strong group for an extended time and believe that many of the challenges and opportunities raised demand attention for more ethical futures of AI for health. Nonetheless, our results are primarily descriptive and are thus not explicitly grounded in a normative argument. We make effort in the Discussion section to contextualize our results by describing their significance and connecting them to broader efforts to reform global health research and practice.

Uniquely important ethical issues for AI in global health research

Presentations and group dialogue over the course of the forum raised several issues for consideration, and here we describe four overarching themes for the ethical governance of AI in global health research. Brief descriptions of each issue can be found in Table  1 . Reports referred to throughout the paper are available at the GFBR website provided above.

The first overarching thematic issue relates to the appropriateness of building AI technologies in response to health-related challenges in the first place. Case study presentations referred to initiatives where AI technologies were highly appropriate, such as in ear shape biometric identification to more accurately link electronic health care records to individual patients in Zambia (Alinani Simukanga). Although important ethical issues were raised with respect to privacy, trust, and community engagement in this initiative, the AI-based solution was appropriately matched to the challenge of accurately linking electronic records to specific patient identities. In contrast, forum participants raised questions about the appropriateness of an initiative using AI to improve the quality of handwashing practices in an acute care hospital in India (Niyoshi Shah), which led to gaming the algorithm. Overall, participants acknowledged the dangers of techno-solutionism, in which AI researchers and developers treat AI technologies as the most obvious solutions to problems that in actuality demand much more complex strategies to address [ 24 ]. However, forum participants agreed that RECs in different contexts have differing degrees of power to raise issues of the appropriateness of an AI-based intervention.

The second overarching thematic issue related to whether and how AI-based systems transfer from one national health context to another. One central issue raised by a number of case study presentations related to the challenges of validating an algorithm with data collected in a local environment. For example, one case study presentation described a project that would involve the collection of personally identifiable data for sensitive group identities, such as tribe, clan, or religion, in the jurisdictions involved (South Africa, Nigeria, Tanzania, Uganda and the US; Gakii Masunga). Doing so would enable the team to ensure that those groups were adequately represented in the dataset to ensure the resulting algorithm was not biased against specific community groups when deployed in that context. However, some members of these communities might desire to be represented in the dataset, whereas others might not, illustrating the need to balance autonomy and inclusivity. It was also widely recognized that collecting these data is an immense challenge, particularly when historically oppressive practices have led to a low-trust environment for international organizations and the technologies they produce. It is important to note that in some countries such as South Africa and Rwanda, it is illegal to collect information such as race and tribal identities, re-emphasizing the importance for cultural awareness and avoiding “one size fits all” solutions.

The third overarching thematic issue is related to understanding accountabilities for both the impacts of AI technologies and governance decision-making regarding their use. Where global health research involving AI leads to longer-term harms that might fall outside the usual scope of issues considered by a REC, who is to be held accountable, and how? This question was raised as one that requires much further attention, with law being mixed internationally regarding the mechanisms available to hold researchers, innovators, and their institutions accountable over the longer term. However, it was recognized in breakout group discussion that many jurisdictions are developing strong data protection regimes related specifically to international collaboration for research involving health data. For example, Kenya’s Data Protection Act requires that any internationally funded projects have a local principal investigator who will hold accountability for how data are shared and used [ 25 ]. The issue of research partnerships with commercial entities was raised by many participants in the context of accountability, pointing toward the urgent need for clear principles related to strategies for engagement with commercial technology companies in global health research.

The fourth and final overarching thematic issue raised here is that of consent. The issue of consent was framed by the widely shared recognition that models of individual, explicit consent might not produce a supportive environment for AI innovation that relies on the secondary uses of health-related datasets to build AI algorithms. Given this recognition, approaches such as community oversight of health data uses were suggested as a potential solution. However, the details of implementing such community oversight mechanisms require much further attention, particularly given the unique perspectives on health data in different country settings in global health research. Furthermore, some uses of health data do continue to require consent. One case study of South Africa, Nigeria, Kenya, Ethiopia and Uganda suggested that when health data are shared across borders, individual consent remains necessary when data is transferred from certain countries (Nezerith Cengiz). Broader clarity is necessary to support the ethical governance of health data uses for AI in global health research.

Recommendations for ethical governance of AI in global health research

Dialogue at the forum led to a range of suggestions for promoting ethical conduct of AI research for global health, related to the various roles of actors involved in the governance of AI research broadly defined. The strategies are written for actors we refer to as “governance leaders”, those people distributed throughout the AI for global health research ecosystem who are responsible for ensuring the ethical and socially responsible conduct of global health research involving AI (including researchers themselves). These include RECs, government regulators, health care leaders, health professionals, corporate social accountability officers, and others. Enacting these strategies would bolster the ethical governance of AI for global health more generally, enabling multiple actors to fulfill their roles related to governing research and development activities carried out across multiple organizations, including universities, academic health sciences centers, start-ups, and technology corporations. Specific suggestions are summarized in Table  2 .

First, forum participants suggested that governance leaders including RECs, should remain up to date on recent advances in the regulation of AI for health. Regulation of AI for health advances rapidly and takes on different forms in jurisdictions around the world. RECs play an important role in governance, but only a partial role; it was deemed important for RECs to acknowledge how they fit within a broader governance ecosystem in order to more effectively address the issues within their scope. Not only RECs but organizational leaders responsible for procurement, researchers, and commercial actors should all commit to efforts to remain up to date about the relevant approaches to regulating AI for health care and public health in jurisdictions internationally. In this way, governance can more adequately remain up to date with advances in regulation.

Second, forum participants suggested that governance leaders should focus on ethical governance of health data as a basis for ethical global health AI research. Health data are considered the foundation of AI development, being used to train AI algorithms for various uses [ 26 ]. By focusing on ethical governance of health data generation, sharing, and use, multiple actors will help to build an ethical foundation for AI development among global health researchers.

Third, forum participants believed that governance processes should incorporate AI impact assessments where appropriate. An AI impact assessment is the process of evaluating the potential effects, both positive and negative, of implementing an AI algorithm on individuals, society, and various stakeholders, generally over time frames specified in advance of implementation [ 27 ]. Although not all types of AI research in global health would warrant an AI impact assessment, this is especially relevant for those studies aiming to implement an AI system for intervention into health care or public health. Organizations such as RECs can use AI impact assessments to boost understanding of potential harms at the outset of a research project, encouraging researchers to more deeply consider potential harms in the development of their study.

Fourth, forum participants suggested that governance decisions should incorporate the use of environmental impact assessments, or at least the incorporation of environment values when assessing the potential impact of an AI system. An environmental impact assessment involves evaluating and anticipating the potential environmental effects of a proposed project to inform ethical decision-making that supports sustainability [ 28 ]. Although a relatively new consideration in research ethics conversations [ 29 ], the environmental impact of building technologies is a crucial consideration for the public health commitment to environmental sustainability. Governance leaders can use environmental impact assessments to boost understanding of potential environmental harms linked to AI research projects in global health over both the shorter and longer terms.

Fifth, forum participants suggested that governance leaders should require stronger transparency in the development of AI algorithms in global health research. Transparency was considered essential in the design and development of AI algorithms for global health to ensure ethical and accountable decision-making throughout the process. Furthermore, whether and how researchers have considered the unique contexts into which such algorithms may be deployed can be surfaced through stronger transparency, for example in describing what primary considerations were made at the outset of the project and which stakeholders were consulted along the way. Sharing information about data provenance and methods used in AI development will also enhance the trustworthiness of the AI-based research process.

Sixth, forum participants suggested that governance leaders can encourage or require community engagement at various points throughout an AI project. It was considered that engaging patients and communities is crucial in AI algorithm development to ensure that the technology aligns with community needs and values. However, participants acknowledged that this is not a straightforward process. Effective community engagement requires lengthy commitments to meeting with and hearing from diverse communities in a given setting, and demands a particular set of skills in communication and dialogue that are not possessed by all researchers. Encouraging AI researchers to begin this process early and build long-term partnerships with community members is a promising strategy to deepen community engagement in AI research for global health. One notable recommendation was that research funders have an opportunity to incentivize and enable community engagement with funds dedicated to these activities in AI research in global health.

Seventh, forum participants suggested that governance leaders can encourage researchers to build strong, fair partnerships between institutions and individuals across country settings. In a context of longstanding imbalances in geopolitical and economic power, fair partnerships in global health demand a priori commitments to share benefits related to advances in medical technologies, knowledge, and financial gains. Although enforcement of this point might be beyond the remit of RECs, commentary will encourage researchers to consider stronger, fairer partnerships in global health in the longer term.

Eighth, it became evident that it is necessary to explore new forms of regulatory experimentation given the complexity of regulating a technology of this nature. In addition, the health sector has a series of particularities that make it especially complicated to generate rules that have not been previously tested. Several participants highlighted the desire to promote spaces for experimentation such as regulatory sandboxes or innovation hubs in health. These spaces can have several benefits for addressing issues surrounding the regulation of AI in the health sector, such as: (i) increasing the capacities and knowledge of health authorities about this technology; (ii) identifying the major problems surrounding AI regulation in the health sector; (iii) establishing possibilities for exchange and learning with other authorities; (iv) promoting innovation and entrepreneurship in AI in health; and (vi) identifying the need to regulate AI in this sector and update other existing regulations.

Ninth and finally, forum participants believed that the capabilities of governance leaders need to evolve to better incorporate expertise related to AI in ways that make sense within a given jurisdiction. With respect to RECs, for example, it might not make sense for every REC to recruit a member with expertise in AI methods. Rather, it will make more sense in some jurisdictions to consult with members of the scientific community with expertise in AI when research protocols are submitted that demand such expertise. Furthermore, RECs and other approaches to research governance in jurisdictions around the world will need to evolve in order to adopt the suggestions outlined above, developing processes that apply specifically to the ethical governance of research using AI methods in global health.

Research involving the development and implementation of AI technologies continues to grow in global health, posing important challenges for ethical governance of AI in global health research around the world. In this paper we have summarized insights from the 2022 GFBR, focused specifically on issues in research ethics related to AI for global health research. We summarized four thematic challenges for governance related to AI in global health research and nine suggestions arising from presentations and dialogue at the forum. In this brief discussion section, we present an overarching observation about power imbalances that frames efforts to evolve the role of governance in global health research, and then outline two important opportunity areas as the field develops to meet the challenges of AI in global health research.

Dialogue about power is not unfamiliar in global health, especially given recent contributions exploring what it would mean to de-colonize global health research, funding, and practice [ 30 , 31 ]. Discussions of research ethics applied to AI research in global health contexts are deeply infused with power imbalances. The existing context of global health is one in which high-income countries primarily located in the “Global North” charitably invest in projects taking place primarily in the “Global South” while recouping knowledge, financial, and reputational benefits [ 32 ]. With respect to AI development in particular, recent examples of digital colonialism frame dialogue about global partnerships, raising attention to the role of large commercial entities and global financial capitalism in global health research [ 21 , 22 ]. Furthermore, the power of governance organizations such as RECs to intervene in the process of AI research in global health varies widely around the world, depending on the authorities assigned to them by domestic research governance policies. These observations frame the challenges outlined in our paper, highlighting the difficulties associated with making meaningful change in this field.

Despite these overarching challenges of the global health research context, there are clear strategies for progress in this domain. Firstly, AI innovation is rapidly evolving, which means approaches to the governance of AI for health are rapidly evolving too. Such rapid evolution presents an important opportunity for governance leaders to clarify their vision and influence over AI innovation in global health research, boosting the expertise, structure, and functionality required to meet the demands of research involving AI. Secondly, the research ethics community has strong international ties, linked to a global scholarly community that is committed to sharing insights and best practices around the world. This global community can be leveraged to coordinate efforts to produce advances in the capabilities and authorities of governance leaders to meaningfully govern AI research for global health given the challenges summarized in our paper.

Limitations

Our paper includes two specific limitations that we address explicitly here. First, it is still early in the lifetime of the development of applications of AI for use in global health, and as such, the global community has had limited opportunity to learn from experience. For example, there were many fewer case studies, which detail experiences with the actual implementation of an AI technology, submitted to GFBR 2022 for consideration than was expected. In contrast, there were many more governance reports submitted, which detail the processes and outputs of governance processes that anticipate the development and dissemination of AI technologies. This observation represents both a success and a challenge. It is a success that so many groups are engaging in anticipatory governance of AI technologies, exploring evidence of their likely impacts and governing technologies in novel and well-designed ways. It is a challenge that there is little experience to build upon of the successful implementation of AI technologies in ways that have limited harms while promoting innovation. Further experience with AI technologies in global health will contribute to revising and enhancing the challenges and recommendations we have outlined in our paper.

Second, global trends in the politics and economics of AI technologies are evolving rapidly. Although some nations are advancing detailed policy approaches to regulating AI more generally, including for uses in health care and public health, the impacts of corporate investments in AI and political responses related to governance remain to be seen. The excitement around large language models (LLMs) and large multimodal models (LMMs) has drawn deeper attention to the challenges of regulating AI in any general sense, opening dialogue about health sector-specific regulations. The direction of this global dialogue, strongly linked to high-profile corporate actors and multi-national governance institutions, will strongly influence the development of boundaries around what is possible for the ethical governance of AI for global health. We have written this paper at a point when these developments are proceeding rapidly, and as such, we acknowledge that our recommendations will need updating as the broader field evolves.

Ultimately, coordination and collaboration between many stakeholders in the research ethics ecosystem will be necessary to strengthen the ethical governance of AI in global health research. The 2022 GFBR illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Data availability

All data and materials analyzed to produce this paper are available on the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ .

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Benatar S. Politics, power, poverty and global health: systems and frames. Int J Health Policy Manag. 2016;5(10):599.

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Acknowledgements

We would like to acknowledge the outstanding contributions of the attendees of GFBR 2022 in Cape Town, South Africa. This paper is authored by members of the GFBR 2022 Planning Committee. We would like to acknowledge additional members Tamra Lysaght, National University of Singapore, and Niresh Bhagwandin, South African Medical Research Council, for their input during the planning stages and as reviewers of the applications to attend the Forum.

This work was supported by Wellcome [222525/Z/21/Z], the US National Institutes of Health, the UK Medical Research Council (part of UK Research and Innovation), and the South African Medical Research Council through funding to the Global Forum on Bioethics in Research.

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Department of Physical Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada

Berman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, USA

Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

Department of Philosophy and Classics, University of Ghana, Legon-Accra, Ghana

Caesar A. Atuire

Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand

Phaik Yeong Cheah

Berkman Klein Center, Harvard University, Bogotá, Colombia

Armando Guio Español

Department of Radiology and Informatics, Emory University School of Medicine, Atlanta, GA, USA

Judy Wawira Gichoya

Health Ethics & Governance Unit, Research for Health Department, Science Division, World Health Organization, Geneva, Switzerland

Adrienne Hunt & Katherine Littler

African Center of Excellence in Bioinformatics and Data Intensive Science, Infectious Diseases Institute, Makerere University, Kampala, Uganda

Daudi Jjingo

ISI Foundation, Turin, Italy

Daniela Paolotti

Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland

Effy Vayena

Joint Centre for Bioethics, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

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JS led the writing, contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. CA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. PYC contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AE contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JWG contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AH contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DJ contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. KL contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DP contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. EV contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper.

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Shaw, J., Ali, J., Atuire, C.A. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 25 , 46 (2024). https://doi.org/10.1186/s12910-024-01044-w

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DOI : https://doi.org/10.1186/s12910-024-01044-w

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The cyber pandemic: AI deepfakes and the future of security and identity verification

Attackers have seen huge success using ai deepfakes for injection and presentation attacks – which means we’ll only see more of them. advanced technology can help prevent (not just detect them)..

Security and risk management pros have a lot keeping them up at night. The era of AI deepfakes is fully upon us, and unfortunately, today’s identity verification and security methods won’t survive. In fact, Gartner estimates that by 2026, nearly one-third of enterprises will consider identity verification and authentication solutions unreliable due to AI-generated deepfakes. Of all the threats IT organizations face, an injection attack that leverages AI-generated deepfakes is the most dangerous. Recent stories show that deepfake injection attacks are capable of defeating popular Know Your Customer (KYC) systems – and with a 200% rise in injection attacks last year and no way to stop them, CIOs and CISOs must develop a strategy for preventing attacks that use AI-generated deepfakes.

First, you’ll need to understand exactly how bad actors use AI deepfakes to attack your systems. Then, you can develop a strategy that integrates advanced technologies to help you prevent (not just detect) them.

The digital injection attack

A digital injection attack is when someone “injects” fake data, including AI-generated documents, photos, and biometrics images, into the stream of information received by an identity verification (IDV) platform. Bad actors use virtual cameras, emulators, and other tools to circumvent cameras, microphones, or fingerprint sensors and fool systems into believing they’ve received true data.

Injection attacks are now five times more common than presentation attacks, and when used in combination with AI-generated deepfakes, they’re nearly impossible to detect. Attackers use deepfake ID documents to fool KYC processes or inject deepfake photos and videos to spoof facial biometrics systems . A prime example is the recent attack that injected an AI deepfake video feed to defraud a Hong Kong company for $25 million. As expected with the rise of Generative AI, AI deepfakes are also on the rise, with Onfido reporting a 3,000% increase in deepfake attacks last year. The NSA, FBI, and CISA collaboratively shared their concerns about the threat of AI deepfakes, saying that, “The increasing availability and efficiency of synthetic media techniques available to less capable malicious cyber actors indicate these types of techniques will likely increase in frequency and sophistication.” 

The key to stopping injection attacks is to prevent digitally altered images or documents from being introduced in the first place. And the only way to do this is to leverage advanced security technologies such as mobile cryptography. The cryptographic signatures provided by mobile devices, operating systems, and apps are practically impossible to spoof because they’re backed by the extremely high-security practices of Apple and Android. Using mobile cryptography to determine the authenticity of the device, its operating system, and the app it’s running is a crucial and decisive measure for stopping injection attacks in their tracks.

The presentation attack

Presentation attacks present fake data to a sensor or document scanner with the intent to impersonate an end user and fool a system into granting access. Facial biometrics presentation attacks take many forms, using deepfake ID documents, “face-swaps,” and even hyper-realistic masks to impersonate someone. IDV and KYC platforms use presentation attack detection (PAD) to verify the documents and selfies that are presented, but many PAD techniques can be beaten by injection attacks that leverage AI deepfakes. 

Staying ahead of injection and presentation attacks

Over the past couple of years, we’ve seen thousands of companies fall victim to these attacks. The impacts are incalculable: hundreds of millions of dollars looted, ransomware shutdowns that impact millions of people, personal information stolen, and reputations damaged beyond repair. And the problem is only getting worse. 

The only strategy for stopping these attacks is to use identity verification tools that prevent injection attacks from happening in the first place and then apply focus on verifying the actual person behind the screen. This way, IT organizations can also shut down human social engineering vectors that circumvent or exploit IDV processes. In addition, by adding verification technologies like device intelligence, AI models, and behavioral biometrics, IT organizations can further reduce the risk of first-party fraud. Finally, invest in solutions that protect your multi-factor authentication (MFA) and password recovery processes: this is a primary attack vector and a key vulnerability that companies often overlook.

Attackers have seen huge success using AI deepfakes for injection and presentation attacks – which means we’ll only see more of them. The key to stopping this threat is to develop a multi-layered approach that combines PAD, injection attack detection (IAD), and image inspection. This strategy forms the basis for companies to navigate the “cyber pandemic” we face and onto a more secure, trusted future.

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Aaron Painter is a deepfake expert and CEO of Nametag Inc., the world's first identity verification platform designed to safeguard accounts against impersonators and AI-generated deepfakes.

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AI, space, integrated sensing and cyber dominate Pentagon’s S&T funding plans

By Jon Harper

May 1, 2024

The Department of Defense is requesting $17.2 billion for science and technology projects in fiscal 2025, and most of it would be dedicated to three capability areas — AI and autonomy, space, and integrated sensing and cyber — according to a presentation by the Pentagon’s CTO.

Heidi Shyu, undersecretary of defense for research and engineering, has identified 14 “critical technology areas” that she is prioritizing, including trusted AI and autonomy, space, integrated sensing and cyber, integrated network systems of systems, renewable energy generation and storage, and microelectronics. They also include human-machine interface, advanced materials, directed energy, advanced computing and software, hypersonics, biotech, quantum, and 5G/FutureG.

Although S&T funding for budget activities 6.1 basic research, 6.2 applied research and 6.3 advanced technology development only account for about 2% of the Pentagon’s overall budget, it’s considered critical for military modernization because it lays the seed corn for next-generation capabilities.

Of the $17.2 billion that the Pentagon has requested for these budget activities in fiscal 2025, 98% would be divided among those 14 critical tech areas, according to Shyu’s slide presentation during a webinar hosted by NDIA’s Emerging Technologies Institute on Tuesday.

“If you see where the bulk of our funding is going … the biggest bar chart is trusted AI and autonomy. So that’s not going to be surprising. The second area that we found a lot of money in is in the space technology arena. The third piece is the integrators sensing and cyber … Those three categories of areas we’re funding composed about 65% of our S&T budget,” Shyu noted.

The proposal includes about $4.9 billion for trusted AI and autonomy, $4.3 billion for space, and $1.9 billion for integrated sensing and cyber.

Additionally, it includes $1.6 billion for integrated network system of system, $1.5 billion for renewable energy generation and storage, $515 million for microelectronics, $458 million for human-machine interface, $414 for advanced materials, $355 million for directed energy, $333 million for advanced computing and software, $242 million for hypersonics, $224 million for biotech, $76 million for quantum, and $38 million for 5G/FutureG.

The majority of that — approximately $9 billion — is for advanced tech development, with $5.8 billion and $2.5 billion slated for applied research and basic research, respectively.

Among DOD components, about $8.3 billion would go toward “Defense-wide” agencies not aligned with the services — also known as the Fourth Estate — such as the Defense Advanced Research Projects Agency, Defense Innovation Unit, Strategic Capabilities Office, Missile Defense Agency, and other agencies and field activities under the Office of the Secretary of Defense, according to Shyu’s slides.

Among the services, the Army would receive about $2.8 billion, the Air Force $2.7 billion, the Navy $2.5 billion and the Space Force $840 million.

The total S&T funding request for fiscal 2025 is 3.4% lower than the 2024 request, per Shyu’s slides.

Shyu noted the importance of technology transition from the S&T enterprise as the U.S. aims to field new capabilities at scale.

A total of 105 projects in critical technology areas were transitioned in fiscal 2023, with trusted AI and autonomy topping the list at 30, according to the Pentagon CTO.

There are several potential transition pathways, she noted.

“The most typical way that people think about is transitioning into a program of record. Right. So that’s the one pathway. However, it could be a piece of software that we’re delivering capability to upgrade a capability that’s already been fielded. So that’s a different way of fielding a new capability. The other way could very well be, we have developed a technology, the technology is being utilized by a DOD prime or commercial company, [and] we then end up procuring that technology. And the fourth way is we’ve transitioned technology for the DOD [and] it could be used by another government agency,” she explained.

She highlighted the Rapid Defense Experimentation Reserve ( RDER ) and the Accelerate the Procurement and Fielding of Innovative Technologies (APFIT) programs as examples of initiatives aimed at helping transition promising warfighting capabilities into production.

Several RDER-related technologies are on track to move into production, according to Shyu.

“We have developed some capabilities as part of … the RDER activities. Once we develop it and its mature and the services say, ‘We really would like to have it,’ there are ways that we can just put it right onto the [General Services Administration] schedule and literally a service that wants to procure it just can buy it outright. So it doesn’t have to go through a long procurement process into a program of record,” she explained.

In April, the Pentagon announced the latest tranche of APFIT projects to receive funding, geared toward small and nontraditional contractors. To date, the department has funded 38 companies via the initiative, Shyu said Tuesday.

“We’re helping to fund small companies to get into low-rate initial production. This is helping them to bridge the valley of death that they typically face from [budget activity] 6.3 to get into 6.4 and into-low rate industrial production,” she said, noting that technologies from the first tranche are being fielded by the services and the combatant commands.

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IATEFL 2024 Conference: Leveraging Technology and Harnessing the Entrepreneurial Spirit

Krzl light nuñes.

• April 27, 2024

As the use of AI and other technologies in English language teaching continues to expand, so do the discussions around the opportunities it brings and the ELT community’s discussions regarding its implications. So, it’s no surprise technology was a hot topic of the 57th IATEFL Conference, held from April 16 to 19, at The Brighton Centre in Brighton, UK.

Attended by English language teaching professionals from over 100 countries, this year’s IATEFL Conference featured plenary sessions, presentations, workshops, exhibitions, and forums on a variety of themes, from materials development to assessment to teaching niches like Business English and English proficiency test prep .

Bridge took part in this year’s conference, with presentations by Anna Hearrell, Director of Operations, Karina Zew, Academic Director, and Umut Ergöz, Academic Operations Coordinator, sharing their insights on corporate language training, teacherprenurship, and tech innovations in language learning.

Interested in training for a TEFL niche? Explore Bridge’s Specialized Certifications and Micro-credential courses!

Leveraging AI and other technology in ELT

AI has come a long way from being a buzzword to becoming a practical complement to language learning and a powerful aid for English teachers. For one, it has helped teachers encourage learning autonomy, such as when teachers recommend students use language apps to practice English after class. On top of that, using AI-powered tools increases a teacher’s efficiency when assessing students’ needs and creating lesson plans and other class materials.

Because of the assistance AI can provide, staying up to date with AI and the latest digital tools has become beneficial for English teachers. It helps them to stay on top of their game, especially when it comes to addressing special learner needs and catering to specific niches. Teaching Business English , for instance, is a specialization that can leverage AI tools in many different ways, including by:

• personalizing learning paths
• carrying out placement tests through adaptive learning platforms
• customizing class content and assessment
• personalizing learners’ extended practice exercises

Throughout the IATEFL Conference, the use of AI and tech innovations were widely discussed, as various educators delved into topics such as the teacher’s role in using AI , selecting online tools, how AI can be used for teaching various English skills, and creating digital class activities.

Sharing his insights on this topic, Ergöz talked about how tech-driven strategies are transforming multicultural language learning and how Business English trainers can leverage AI’s capabilities.

“With the advancement of AI and its integration into various fields, it’s crucial to recognize both its capabilities and limitations,” he said, sharing why he chose to present on this topic at IATEFL. “I wanted to underscore this point. Technology serves as a powerful tool for Business English learners , particularly addressing one of the main challenges adult learners face: time constraints. Adult learners often juggle busy schedules, making it difficult to maintain consistent learning patterns. One day may be filled with meetings, while another offers free time. Technology can adapt to these varying schedules and support flexible learning opportunities.”

In his presentation, Ergöz first tackled the challenges of teaching and learning Business English , challenges that range from learners’ time constraints to their specific language needs. Then, he asked the audience to think about the popularity of language learning apps.

“During my presentation, I asked how many in the audience had a language learning app on their phones and it was quite a big number,” he said. “Then I asked them how many of them learned a language using one of those apps and the answer was zero! Absolutely no one! I wanted the audience to understand why this is happening and how we are dealing with it at Bridge Corporate Language Learning , by putting our teachers at the center of our teaching methodology.”

Sharing data regarding language learning apps and how teachers can leverage technology tools also sparked curiosity among the audience. “The reaction was marvelous!” Ergöz said. “Many photos and notes were taken, especially regarding the tools I mentioned. It made me think that while technology is readily available, it can also present challenges. Finding helpful tools and incorporating them into your teaching methodology can be tricky, especially if you are not from the new generation of teachers who were born with computers and smartphones in hand.”

Finally, Ergöz also talked about the advantages of using AI tools in supporting Business English students’ learning. As Bridge Corporate Language Learning itself makes the most out of AI to enhance its corporate language courses, its teachers use a variety of tech tools to carry out student placement , map out lesson plans based on student needs, and provide learners with avenues to practice English even outside their classes. But while tech tools and apps improve language instruction, Ergöz highlighted that they can never replace the teacher’s role.

“The main idea was that technology and AI could be used for many different things, especially outside of the classroom, but still, the teacher is the heart of education,” he said. “I wanted to show that to the audience. Having technology is truly helpful, especially for asynchronous learning, but still, we should always consider the human factor. I’m a strong believer that technology and teachers can go hand in hand when it comes to Business English teaching!”

Read more about ways to hyper-personalize your Business English teaching with AI.

Additional IATEFL highlights

Aside from technology, the sessions at the IATEFL Conference covered other topics, such as teaching methodologies , professional development , ELT teacher training, Content and Language Integrated Learning (CLIL) , and language testing and assessment.

In her presentation, Hearrell gave a talk on teacherpreneurship , wherein she shared how English teachers can become independent and develop an entrepreneurial mindset.

“I chose to present on teacherpreneurism because I think that running an independent teaching business (of whatever size) is doable for any English teacher who sets their mind to it or realizes it’s a path they want to explore,” she shared. “It is a journey to success, but I tried to highlight that in my presentation by giving teachers examples of pathways and cases where other teachers have worked to build a business and brand behind their teaching services.”

At the start of her presentation, Hearrell pointed out that not many people are still unfamiliar with the concept of being a teacherpreneur , saying, “Within our industry, the phenomenon of an English teacher working to have their own portfolio of private students is not new; in the past it has been referred to as independent teaching or maybe even freelance teaching. However, I love the word “teacherpreneur” because I think it’s incredibly powerful. And, it leans into what teachers often struggle with the most: business and marketing practices.”

Along with introducing the meaning of teacherpreneur and its advantages, she also gave tips on how English teachers can successfully launch their teaching business, from choosing a niche to defining their product offers to creating their Unique Selling Proposition (USP).

“I hope that educators feel motivated and empowered; I hope that they realize that they have inherent traits as educators that can translate to a more business-forward mentality,” Hearrell said. “By becoming a teacherpreneur, they’re finally also advocating for themselves and stepping up to get what they need or deserve out of a teaching job – which I fully support!”

Ready to launch or expand an independent teaching career? Learn more about Teacherpreneur Academy, which provides training, resources, and support for independent English teachers.

Building networks through IATEFL

Aside from learning and gaining fresh perspectives from industry experts, the IATEFL Conference also allowed attendees to meet and connect with other ELT professionals or strengthen relationships with those whom they had met in previous conferences. For Ergöz, the networking aspect of the event, being able to build global connections , was the most exciting part.

“I met so many interesting people and built great connections,” he said. “It also allowed me to realize how much there is to learn about education and teaching. I even met some important linguists whose books I’ve read! Learning, sharing ideas, and growing was so much fun. Representing Bridge Education, which I love and consider my second home, was such an honor!”

Hearrell similarly found the experience enjoyable. “IATEFL is always a great time! From chatting with old friends to meeting new contacts, it’s often the time of the year I feel most connected to our industry and its key players,” she said. “The atmosphere is always full of people who want to learn, whether it be new teaching skills, about innovative products or technologies, or to simply learn about you and your background – there’s no shortage of motivation to continue professional development .”

From staying abreast of current trends or interacting with educators around the world, the IATEFL Conference provides a chance for the ELT community to stay connected, keep learning together, and support each other. If you’re an educator in the English teaching field, make sure that the next IATEFL Conference is on your bucket list so that you too can continue growing and adapting to the ever-evolving English teaching field!

Looking for ways to keep track of upcoming TEFL events? Learn more about the Bridge TEFL/TESOL Events Calendar!

Back in her hometown in the Philippines, Krzl worked as a writer at a TV station before moving to Chile. After she completed her TESOL certification, she worked for language institutes and then decided to become an independent English teacher to business professionals. When she’s not giving classes, she’s either surfing along Chile’s long stretch of coastline, traveling, or practicing photography by the beach.

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Tech platforms make pitch for ad deals as TikTok is roiled by politics

Saturday, 04 May 2024

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FILE PHOTO: A TikTok logo is displayed on a smartphone in this illustration taken January 6, 2020. REUTERS/Dado Ruvic/Illustration/File Photo

(Reuters) - Short-form video took center stage at tech and social media companies' annual presentations to advertisers, as platforms like Snap and Meta look to capitalize on TikTok's political uncertainty in the U.S. to take ad dollars from their rival.

The presentations in New York, known as the NewFronts, come just a week after U.S. President Joe Biden signed a bill that gives Chinese tech company ByteDance up to one year to divest TikTok, or else the app will be banned over national security concerns. TikTok has vowed to fight the legislation.

The short video platform announced new sports and entertainment partnerships at its NewFront on Thursday evening, including an agreement that broadcaster NBCUniversal will post clips of this summer's Paris Olympics on TikTok.

TikTok is expected to generate $8.66 billion in U.S. ad revenue this year according to an estimate from research firm Emarketer. While it is a fraction of the size of Google and Meta, TikTok kicked off the short-form video craze and prompted rivals to build similar features.

"TikTok must show advertisers that it's business-as-normal, even though it's anything but," Emarketer principal analyst Jasmine Enberg said.

On Wednesday, Snap, which owns photo messaging app Snapchat, said it would also partner with NBCUniversal to send popular influencers to the games to film content. It will also host clips of top concerts from events promoter Live Nation.

"We're having very productive conversations about how Snapchat can help, because there is a lot of noise at the moment," said Patrick Harris, Snap's president of Americas and partnerships. "But we have our heads down and we're making sure we're a dependable and viable platform."

The focus on professionally produced videos is designed to attract brands wary of the downside of social media or artificial intelligence (AI) generated content.

"Brands have to spend a little extra time really thinking about the quality of environments, which is why these content partnerships that are being spun up are so important," said Robert Silver, head of media at digital marketing firm Razorfish.

Facebook and Instagram owner Meta focused its NewFront on Reels, its TikTok competitor that now accounts for half of the time users spend on Instagram.

"Instagram Reels already stands to benefit from a TikTok ban, and Meta wants to ensure that it can attract all the potential displaced users and revenues it can," Emarketer's Enberg said.

Google said on Monday that its own short-form video feature called YouTube Shorts are increasingly being viewed on TV screens in addition to phones.

Despite the uncertainty over TikTok's future, advertisers say they intend to focus on the near-term and some plan to continue advertising until it is no longer possible to do so.

"I think we need to put some blinders on and focus and try to understand on what innovative capabilities are available for advertisers," said Alex Stone, senior vice president of agency partnerships at media buying firm Horizon Media, referring to TikTok's NewFront.

(Reporting by Sheila Dang in New York; Editing by Michael Erman)

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Source: Department of Environment, Malaysia

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