The editors at Solutions Review curated this list of the best AI and machine learning TED talks for practitioners in the field.
TED Talks are influential videos from expert speakers in a variety of verticals. TED began in 1984 as a conference where Technology, Entertainment and Design converged, and today covers almost all topics — from business to technology to global issues — in more than 110 languages. TED is building a clearinghouse of free knowledge from the world’s top thinkers, and their library of videos is expansive and rapidly growing.
Solutions Review has curated this list of AI and machine learning TED talks to watch if you are a practitioner in the field. Talks were selected based on relevance, ability to add business value, and individual speaker expertise. We’ve also curated TED talk lists for topics like data visualization and big data.
Erik Brynjolfsson is the director of the MIT Center for Digital Business and a research associate at the National Bureau of Economic Research. He asks how IT affects organizations, markets and the economy. His books include Wired for Innovation and Race Against the Machine. Brynjolfsson was among the first researchers to measure the productivity contributions of information and community technology (ICT) and the complementary role of organizational capital and other intangibles.
In this talk, Brynjolfsson argues that machine learning and intelligence are not the end of growth — it’s simply the growing pains of a radically reorganized economy. A riveting case for why big innovations are ahead of us if we think of computers as our teammates. Be sure to watch the opposing viewpoint from Robert Gordon.
Jeremy Howard is the CEO of Enlitic, an advanced machine learning company in San Francisco. Previously, he was the president and chief scientist at Kaggle, a community and competition platform of over 200,000 data scientists. Howard is a faculty member at Singularity University, where he teaches data science. He is also a Young Global Leader with the World Economic Forum, and spoke at the World Economic Forum Annual Meeting 2014 on Jobs for the Machines.
Technologist Jeremy Howard shares some surprising new developments in the fast-moving field of deep learning, a technique that can give computers the ability to learn Chinese, or to recognize objects in photos, or to help think through a medical diagnosis.
Nick Bostrom is a professor at the Oxford University, where he heads the Future of Humanity Institute, a research group of mathematicians, philosophers and scientists tasked with investigating the big picture for the human condition and its future. Bostrom was honored as one of Foreign Policy‘s 2015 Global Thinkers. His book Superintelligence advances the ominous idea that “the first ultraintelligent machine is the last invention that man need ever make.”
In this talk, Nick Bostrom calls machine intelligence “the last invention that humanity will ever need to make.” Bostrom asks us to think hard about the world we’re building right now, driven by thinking machines. Will our smart machines help to preserve humanity and our values — or will they have values of their own?
Li’s work with neural networks and computer vision (with Stanford’s Vision Lab) marks a significant step forward for AI research, and could lead to applications ranging from more intuitive image searches to robots able to make autonomous decisions in unfamiliar situations. Fei-Fei was honored as one of Foreign Policy‘s 2015 Global Thinkers.
This talk digs into how computers are getting smart enough to identify simple elements. Computer vision expert Fei-Fei Li describes the state of the art — including the database of 15 million photos her team built to “teach” a computer to understand pictures — and the key insights yet to come.
Anthony Goldbloom is the co-founder and CEO of Kaggle. Kaggle hosts machine learning competitions, where data scientists download data and upload solutions to difficult problems. Kaggle has a community of over 600,000 data scientists. In 2011 and 2012, Forbes named Anthony one of the 30 under 30 in technology; in 2013 the MIT Tech Review named him one of top 35 innovators under the age of 35, and the University of Melbourne awarded him an Alumni of Distinction Award.
This talk by Anthony Goldbloom describes some of the current use cases for machine learning, far beyond simple tasks like assessing credit risk and sorting mail.
Tufekci is a contributing opinion writer at the New York Times, an associate professor at the School of Information and Library Science at University of North Carolina, Chapel Hill, and a faculty associate at Harvard’s Berkman Klein Center for Internet and Society. Her book, Twitter and Tear Gas was published in 2017 by Yale University Press.
Machine intelligence is here, and we’re already using it to make subjective decisions. But the complex way AI grows and improves makes it hard to understand and even harder to control. In this cautionary talk, techno-sociologist Zeynep Tufekci explains how intelligent machines can fail in ways that don’t fit human error patterns — and in ways we won’t expect or be prepared for.
In his book The Business Romantic, Tim Leberecht invites us to rediscover romance, beauty and serendipity by designing products, experiences, and organizations that “make us fall back in love with our work and our life.” The book inspired the creation of the Business Romantic Society, a global collective of artists, developers, designers and researchers who share the mission of bringing beauty to business.
In this talk, Tim Leberecht makes the case for a new radical humanism in a time of artificial intelligence and machine learning. For the self-described “business romantic,” this means designing organizations and workplaces that celebrate authenticity instead of efficiency and questions instead of answers. Leberecht proposes four principles for building beautiful organizations.
Grady Booch is Chief Scientist for Software Engineering as well as Chief Scientist for Watson/M at IBM Research, where he leads IBM’s research and development for embodied cognition. Having originated the term and the practice of object-oriented design, he is best known for his work in advancing the fields of software engineering and software architecture.
Grady Booch allays our worst (sci-fi induced) fears about superintelligent computers by explaining how we’ll teach, not program, them to share our human values. Rather than worry about an unlikely existential threat, he urges us to consider how artificial intelligence will enhance human life.
Tom Gruber is a product designer, entrepreneur, and AI thought leader who uses technology to augment human intelligence. He was co-founder, CTO, and head of design for the team that created the Siri virtual assistant. At Apple for over 8 years, Tom led the Advanced Development Group that designed and prototyped new capabilities for products that bring intelligence to the interface.
This talk introduces the idea of Humanistic AI. He shares his vision for a future where AI helps us achieve superhuman performance in perception, creativity and cognitive function — from turbocharging our design skills to helping us remember everything we’ve ever read. The idea of an AI-powered personal memory also extends to relationships, with the machine helping us reflect on our interactions with people over time.
Stuart Russell is a professor (and formerly chair) of Electrical Engineering and Computer Sciences at University of California at Berkeley. His book Artificial Intelligence: A Modern Approach (with Peter Norvig) is the standard text in AI; it has been translated into 13 languages and is used in more than 1,300 universities in 118 countries. He also works for the United Nations, developing a new global seismic monitoring system for the nuclear-test-ban treaty.
His talk centers around the question of whether we can harness the power of superintelligent AI while also preventing the catastrophe of robotic takeover. As we move closer toward creating all-knowing machines, AI pioneer Stuart Russell is working on something a bit different: robots with uncertainty. Hear his vision for human-compatible AI that can solve problems using common sense, altruism and other human values.
Dr. Pratik Shah’s research creates novel intersections between engineering, medical imaging, machine learning, and medicine to improve health and diagnose and cure diseases. Research topics include: medical imaging technologies using unorthodox artificial intelligence for early disease diagnoses; novel ethical, secure and explainable artificial intelligence based digital medicines and treatments; and point-of-care medical technologies for real world data and evidence generation to improve public health.
TED Fellow Pratik Shah is working on a clever system to do just that. Using an unorthodox AI approach, Shah has developed a technology that requires as few as 50 images to develop a working algorithm — and can even use photos taken on doctors’ cell phones to provide a diagnosis. Learn more about how this new way to analyze medical information could lead to earlier detection of life-threatening illnesses and bring AI-assisted diagnosis to more health care settings worldwide.
Margaret Mitchell’s research involves vision-language and grounded language generation, focusing on how to evolve artificial intelligence towards positive goals. Her work combines computer vision, natural language processing, social media as well as many statistical methods and insights from cognitive science. Before Google, Mitchell was a founding member of Microsoft Research’s “Cognition” group, focused on advancing artificial intelligence, and a researcher in Microsoft Research’s Natural Language Processing group.
Margaret Mitchell helps develop computers that can communicate about what they see and understand. She tells a cautionary tale about the gaps, blind spots and biases we subconsciously encode into AI — and asks us to consider what the technology we create today will mean for tomorrow.
Kriti Sharma is the Founder of AI for Good, an organization focused on building scalable technology solutions for social good. Sharma was recently named in the Forbes “30 Under 30” list for advancements in AI. She was appointed a United Nations Young Leader in 2018 and is an advisor to both the United Nations Technology Innovation Labs and to the UK Government’s Centre for Data Ethics and Innovation.
AI algorithms make important decisions about you all the time — like how much you should pay for car insurance or whether or not you get that job interview. But what happens when these machines are built with human bias coded into their systems? Technologist Kriti Sharma explores how the lack of diversity in tech is creeping into our AI, offering three ways we can start making more ethical algorithms.
Matt Beane does field research on work involving robots to help us understand the implications of intelligent machines for the broader world of work. Beane is an Assistant Professor in the Technology Management Program at the University of California, Santa Barbara and a Research Affiliate with MIT’s Institute for the Digital Economy. He received his PhD from the MIT Sloan School of Management.
The path to skill around the globe has been the same for thousands of years: train under an expert and take on small, easy tasks before progressing to riskier, harder ones. But right now, we’re handling AI in a way that blocks that path — and sacrificing learning in our quest for productivity, says organizational ethnographer Matt Beane. Beane shares a vision that flips the current story into one of distributed, machine-enhanced mentorship that takes full advantage of AI’s amazing capabilities while enhancing our skills at the same time.
Leila Pirhaji is the founder of ReviveMed, an AI platform that can quickly and inexpensively characterize large numbers of metabolites from the blood, urine and tissues of patients. This allows for the detection of molecular mechanisms that lead to disease and the discovery of drugs that target these disease mechanisms.
Biotech entrepreneur and TED Fellow Leila Pirhaji shares her plan to build an AI-based network to characterize metabolite patterns, better understand how disease develops — and discover more effective treatments.
Janelle Shane is the owner of AIweirdness.com. Her book, You Look Like a Thing and I Love You uses cartoons and humorous pop-culture experiments to look inside the minds of the algorithms that run our world, making artificial intelligence and machine learning both accessible and entertaining.
The danger of artificial intelligence isn’t that it’s going to rebel against us, but that it’s going to do exactly what we ask it to do, says AI researcher Janelle Shane. Sharing the weird, sometimes alarming antics of AI algorithms as they try to solve human problems — like creating new ice cream flavors or recognizing cars on the road — Shane shows why AI doesn’t yet measure up to real brains.
Sylvain Duranton is the global leader of BCG GAMMA, a unit dedicated to applying data science and advanced analytics to business. He manages a team of more than 800 data scientists and has implemented more than 50 custom AI and analytics solutions for companies across the globe.
In this talk, business technologist Sylvain Duranton advocates for a “Human plus AI” approach — using AI systems alongside humans, not instead of them — and shares the specific formula companies can adopt to successfully employ AI while keeping humans in the loop.
For more AI and machine learning TED talks, browse TED’s complete topic collection.
Latest posts by Timothy King (see all)
- DataRobot Updates its AI Platform with DataRobot Paxata Integration - April 3, 2020
- KNIME Unveils Integrated Deployment at Virtual User Conference - April 1, 2020
- 5 Key Embedded Analytics Questions to Ask Solution Providers for 2020 - March 31, 2020