Defining what is, or isn’t artificial intelligence can be tricky (or tough). So much so, even the experts get it wrong sometimes. That’s why MIT Technology Review’s Senior AI Editor Karen Hao created a flowchart to explain it all. In this bonus content our host and her team reimagined Hao’s reporting, gamifying it into a radio play.  If you would like to see the original reporting visit:  https://www.technologyreview.com/2018/11/10/139137/is-this-ai-we-drew-you-a-flowchart-to-work-it-out/  Credits: This episode was reported by Karen Hao. It was adapted for audio and produced by Jennifer Strong and Emma Cillekens. The voices you hear are Emma Cillekens, as well as Eric Mongeon and Kyle Thomas Hemingway. (If you like our show art they made it!) We’re edited by Michael Reilly and Niall Firth. 

In this episode, we meet Sophie Zhang—a former data scientist at Facebook. Before she was fired, she had become consumed by the task of finding and taking down fake accounts that were being used to sway elections globally.  I Was There When is a new oral history project from the In Machines We Trust podcast. It features stories of how breakthroughs and watershed moments in artificial intelligence and computing happened, as told by the people who witnessed them. Credits:  This episode was produced by Jennifer Strong, Anthony Green and Emma Cillekens, and edited by Niall Firth and Mat Honan. It’s mixed by Garret Lang, with theme music by Jacob Gorski.

Algorithms now determine how much things cost. It’s called dynamic pricing and it adjusts according to current market conditions in order to increase profits. The rise of ecommerce has propelled pricing algorithms into an everyday occurrence—whether you’re shopping on Amazon, booking a flight, hotel or ordering an Uber.  We Meet:  Lisa Wilkins, UX designer  Gabe Smith, chief evangelist, Pricefx Aylin Caliskan, assistant professor, University of Washington Joseph Harrington, professor of business, economics and public policy, University of Pennsylvania Maxime Cohen, Scale AI Chair professor, McGill University  Credits: This episode was reported by Anthony Green and produced by Jennifer Strong and Emma Cillekens. We’re edited by Mat Honan and our mix engineer is Garret Lang, with sound design and music by Jacob Gorski.

I Was There When is an oral history project that's part of the In Machines We Trust podcast. It features stories of how breakthroughs in artificial intelligence and computing happened, as told by the people who witnessed them. In this first installment we meet Joseph Atick who helped create the first commercially viable facial recognition system. Do you have a story to tell for this series? Do you want to nominate someone who does? We want to hear from you! Please reach out to us at podcasts@technologyreview.com. CREDITS: This episode was produced by Jennifer Strong, Anthony Green and Emma Cillekens with help from Lindsay Muscato. It’s edited by Michael Reilly and Mat Honan, and mixed by Garret Lang, with sound design and music by Jacob Gorski. 

From chess to Jeopardy to e-sports, AI is increasingly beating humans at their own games. But that was never the ultimate goal. In this episode we dig into the symbiotic relationship between games and AI. We meet the big players in the space, and we take a trip to an arcade. We Meet:  Julian Togelius Will Douglas-Heaven David Silver  David Fahri  We Talked To:  Julian Togelius Will Douglas-Heaven Karen Hao David Silver  David Fahri  Natasha Regan Sounds From: Jeopardy 2011-02:The IBM Challenge https://archive.org/details/Jeopardy.2011.02.The.IBM.Challenge/Jeopardy.2011.02.16.The.IBM.Challenge.Day.3.HDTV.XviD-FQM.avi  Garry Kasparov VS Deep Blue 1997 6th game (Kasparov Resigns) https://www.youtube.com/watch?v=EsMk1Nbcs-s  Attack Like AlphaZero: The Power of the King https://www.youtube.com/watch?v=c0JK5Fa3AqI  Miracle Perfect Anti Mage 16/0 - Dota 2 Pro Gameplay https://www.youtube.com/watch?v=59KnNcU9iKc  DOTA 2 - ALL GAME-WINNING Moments in The International History (TI1-TI9) https://www.youtube.com/watch?v=RJcNbuASl-Y  Credits: This episode was reported by Jennifer Strong and Will Douglas Heaven and produced by Anthony Green, Emma Cillekens and Karen Hao. We’re edited by Niall Firth, Michael Reilly and Mat Honan. Our mix engineer is Garret Lang. Sound design and music by Jacob Gorski.

When it comes to hiring, it’s increasingly becoming an AI’s world, we’re just working in it. In this, the final episode of Season 2, and the conclusion of our series on AI and hiring, we take a look at how AI-based systems are increasingly playing gatekeeper in the hiring process—screening out applicants by the millions, based on little more than what they see in your resume. But we aren’t powerless against the machines. In fact, an increasing number of people and services are designed to help you play by—and in some cases bend—their rules to give you an edge. We Meet:  Jamaal Eggleston, Work Readiness Instructor, The HOPE Program Ian Siegel, CEO, ZipRecruiter Sami Mäkeläinen, Head of Strategic Foresight, Telstra Salil Pande, CEO, VMock Gracy Sarkissian, Interim Executive Director, Wasserman Center for Career Development, New York University We Talked To:  Jamaal Eggleston, Work Readiness Instructor, The HOPE Program Students and Teachers from The HOPE Program in Brooklyn, NY Jonathan Kestenbaum, Co-founder & Managing Director of Talent Tech Labs Josh Bersin, Global Industry Analyst Brian Kropp, Vice President Research, Gartner Ian Siegel, CEO, ZipRecruiter Sami Mäkeläinen, Head of Strategic Foresight, Telstra Salil Pande, CEO, VMock Kiran Pande, Co-Founder, VMock Gracy Sarkissian, Interim Executive Director, Wasserman Center for Career Development, New York University Sounds From: Curious Thing AI (Sound from their AI tool) HireVue Video Interview: How To Beat The Algorithm and Get The Job: https://youtu.be/jn0dc1cOctA  HIREVUE Interview Questions, Tips and Answers! How to PASS a HireVue Interview!: https://youtu.be/ycG5_uccoNk  Video Interview Techniques - 3 Easy Hacks To Prepare for Hirevue / Spark Hire / VidCruiter: https://youtu.be/tp0jt4hoHsI  How to PASS Psychometric Tests | Tips & Tricks for Aptitude Tests, Numerical Reasoning, Game Based: https://youtu.be/u_nWOnJevaA  Credits: This miniseries on hiring was reported by Hilke Schellmann and produced by Jennifer Strong, Emma Cillekens, Anthony Green and Karen Hao. We’re edited by Michael Reilly.

Increasingly, job seekers need to pass a series of ‘tests’ in the form of artificial intelligence games—just to be seen by a hiring manager. In this third, of a four-part miniseries on AI and hiring, we speak to someone who helped create these tests, we ask who might get left behind in the process and why there isn’t more policy in place. We also try out some of these tools ourselves. We Meet: Matthew Neale, Vice President of Assessment Products, Criteria Corp.  Frida Polli, CEO, Pymetrics  Henry Claypool, Consultant and former Obama Administration Member, Commission on Long-Term Care Safe Hammad, CTO, Arctic Shores   Alexandra Reeve Givens, President and CEO, Center for Democracy and Technology Nathaniel Glasser, Employment Lawyer, Epstein Becker Green Keith Sonderling, Commissioner, Equal Employment Opportunity Commission (EEOC) We Talked To:  Aaron Rieke, Managing Director, Upturn Adam Forman, Employment Lawyer, Epstein Becker Green Brian Kropp, Vice President Research, Gartner Josh Bersin, Research Analyst Jonathan Kestenbaum, Co-Founder and Managing Director, Talent Tech Labs Frank Pasquale, Professor, Brooklyn Law School Patricia (Patti) Sanchez, Employment Manager, MacDonald Training Center  Matthew Neale, Vice President of Assessment Products, Criteria Corp.  Frida Polli, CEO, pymetrics  Henry Claypool, Consultant and former Obama Administration Member, Commission on Long-Term Care Safe Hammad, CTO, Arctic Shores   Alexandra Reeve Givens, President and CEO, Center for Democracy and Technology Nathaniel Glasser, Employment Lawyer, Epstein Becker Green Keith Sonderling, Commissioner, Equal Employment Opportunity Commission (EEOC) Sounds From: *Science 4-Hire, podcast *Matthew Kirkwold’s cover of XTC’s, Complicated Game, https://www.youtube.com/watch?v=tumM_6YYeXs Credits: This miniseries on hiring was reported by Hilke Schellmann and produced by Jennifer Strong, Emma Cillekens, Anthony Green and Karen Hao. We’re edited by Michael Reilly.

In the past, hiring decisions were made by people. Today, some key decisions that lead to whether someone gets a job or not are made by algorithms. The use of AI-based job interviews has increased since the pandemic. As demand increases, so too do questions about whether these algorithms make fair and unbiased hiring decisions, or find the most qualified applicant. In this second episode of a four-part series on AI in hiring, we meet some of the big players making this technology including the CEOs of HireVue and myInterview—and we test some of these tools ourselves. We Meet:  Kevin Parker, Chairman & CEO, HireVue Shelton Banks, CEO, re:work Mark Adams, Vice President of North America, Curious Thing AI Benjamin Gillman, Co-Founder and CEO, myInterview Fred Oswald, Psychology Professor, Rice University  Suresh Venkatasubramanian, Computer Science Professor, Brown University Clayton Donnelly, industrial-organizational psychologist, myInterview We Talked To:  Kevin Parker, Chairman & CEO, HireVue Lindsey Zuloaga, Chief Data Scientist, HireVue Nathan Mondragon, Chief IO Psychologist, HireVue Shelton Banks, CEO, re:work Lisa Feldman Barrett, Psychology Professor, Northeastern University Cathy O’Neil, CEO, O'Neil Risk Consulting & Algorithmic Auditing Mark Adams, Vice President of North America, Curious Thing AI Han Xu, Co-founder & CTO, Curious Thing AI Benjamin Gillman, Co-founder & CEO, myInterview  Fred Oswald, Psychology Professor, Rice University  Suresh Venkatasubramanian, Computer Science Professor, Brown University Clayton Donnelly, industrial-organizational psychologist, myInterview Mark Gray, Director of People, Proper Christoph Hohenberger, Co-founder and Managing Director, Retorio Derek Mracek, Lead Data Scientist, Yobs Raphael Danilo, Co-founder & CEO, Yobs Jonathan Kestenbaum, Co-founder & Managing Director of Talent Tech Labs Josh Bersin, Global Industry Analyst Students and Teachers from the Hope Program in Brooklyn, NY Henry Claypool, policy expert and former Director of the U.S. Health and Human Services Office on Disability Sounds From:  Curious Thing AI  myInterview  Dolly Parton - 9 To 5: https://www.youtube.com/watch?v=UbxUSsFXYo4 Arirang News: https://www.youtube.com/watch?v=30oCHwwLxy4 CBS News: https://www.youtube.com/watch?v=fbRBCU6SHHo  CBS Philly: https://www.youtube.com/watch?v=0wiPoCsZFFs  Credits: This miniseries on hiring was reported by Hilke Schellmann and produced by Jennifer Strong, Emma Cillekens, Karen Hao and Anthony Green with special thanks to James Wall. We’re edited by Michael Reilly. Art direction by Stephanie Arnett.

If you’ve applied for a job lately, it’s all but guaranteed that your application was reviewed by software—in most cases, before a human ever laid eyes on it. In this episode, the first in a four-part investigation into automated hiring practices, we speak with the CEOs of ZipRecruiter and Career Builder, and one of the architects of LinkedIn’s algorithmic job-matching system, to explore how AI is increasingly playing matchmaker between job searchers and employers. But while software helps speed up the process of sifting through the job market, algorithms have a history of biasing the opportunities they present to people by gender, race...and in at least one case, whether you played lacrosse in high school. We Meet:  Mark Girouard, Attorney, Nilan Johnson Lewis Ian Siegel, CEO, ZipRecruiter John Jersin, former Vice President of Product Management, LinkedIn Irina Novoselsky, CEO, CareerBuilder  We Talked To:  Mark Girouard, Attorney, Nilan Johnson Lewis Ian Siegel, CEO, ZipRecruiter John Jersin, former Vice President of Product Management, LinkedIn Irina Novoselsky, CEO, CareerBuilder  Derek Kan, Vice President of Product Management, Monster Aleksandra Korolova, Assistant Professor of Computer Science, University of Southern California  Brian Kropp, Vice President Research, Gartner Matthew Neale, Vice President of Assessment Products, Criteria Corp Josh Bersin, Research Analyst Jonathan Kestenbaum, Co-Founder and Managing Director, Talent Tech Labs Suresh Venkatasubramanian, Assistant Director, White House Office of Science and Technology Policy Sounds From:  How to Keep a Job, Coronet Instructional Films: https://archive.org/details/HowtoKee1949  Curious Thing AI (Sound from their AI tool) Credits: This episode was reported by Hilke Schellmann, and produced by Jennifer Strong, Emma Cillekens and Anthony Green with special thanks to Karen Hao. We’re edited by Michael Reilly. Additional reporting from us: https://www.technologyreview.com/2021/06/23/1026825/linkedin-ai-bias-ziprecruiter-monster-artificial-intelligence/ https://www.technologyreview.com/2021/02/11/1017955/auditors-testing-ai-hiring-algorithms-bias-big-questions-remain/ https://www.technologyreview.com/2021/04/09/1022217/facebook-ad-algorithm-sex-discrimination/ https://www.technologyreview.com/2019/11/07/75194/hirevue-ai-automated-hiring-discrimination-ftc-epic-bias/ https://www.technologyreview.com/2020/02/14/844765/ai-emotion-recognition-affective-computing-hirevue-regulation-ethics/

Despite their popularity with kids, tablets and other connected devices are built on top of systems that weren’t designed for them to easily understand or navigate. Adapting algorithms to interact with a child isn’t without its complications—as no one child is exactly like another. Most recognition algorithms look for patterns and consistency to successfully identify objects. but kids are notoriously inconsistent. In this episode, we examine the relationship AI has with kids.  We Meet: Judith Danovitch, associate professor of psychological and brain sciences at the University of Louisville  Lisa Anthony, associate professor of computer science at the University of Florida Tanya Basu, MIT Technology Review Credits:  This episode was reported and produced by Tanya Basu, Anthony Green, Jennifer Strong, and Emma Cillekens. We’re edited by Michael Reilly.

Clearview AI has built one of the most comprehensive databases of people’s faces in the world. Your picture is probably in there (our host Jennifer Strong’s was). In the second of a four-part series on facial recognition, we meet the CEO of the controversial company who tells us our future is filled with face recognition—regardless of whether it's regulated or not. We meet:  Hoan Ton-That, Clearview AI  Alexa Daniels-Shpall, Police Executive Research Forum  Credits:  This episode was reported and produced by Jennifer Strong, with Tate Ryan-Mosely and Emma Cillekens, with special thanks to Karen Hao and Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield. Our technical director is Jacob Gorski.

Credit scores have been used for decades to assess consumer creditworthiness, but their scope is far greater now that they are powered by algorithms: not only do they consider vastly more data, in both volume and type, but they increasingly affect whether you can buy a car, rent an apartment, or get a full-time job. We meet: Chi Chi Wu, staff attorney at National Consumer Law Center   Michele Gilman, professor of law at University of Baltimore Mike de Vere, CEO Zest AI Credits: This episode was produced by Jennifer Strong, Karen Hao, Emma Cillekens and Anthony Green. We’re edited by Michael Reilly.

Synthetic voice technologies are increasingly passing as human. But today’s voice assistants are still a far cry from the hyper-intelligent thinking machines we’ve been musing about for decades. In this episode, we explore how machines learn to communicate—and what it means for the humans on the other end of the conversation.    We meet: Susan C. Bennett, voice of Siri Cade Metz, The New York Times Charlotte Jee, MIT Technology Review Credits This episode was produced by Jennifer Strong, Emma Cillekens, Anthony Green, Karen Hao and Charlotte Jee. We’re edited by Michael Reilly and Niall Firth.

Tech giants are moving into our wallets—bringing AI and big questions with them. Our entire financial system is built on trust. We can exchange otherwise worthless paper bills for fresh groceries, or swipe a piece of plastic for new clothes. But this trust—typically in a central government-backed bank—is changing. As our financial lives are rapidly digitized, the resulting data turns into fodder for AI. Companies like Apple, Facebook and Google see it as an opportunity to disrupt the entire experience of how people think about and engage with their money. But will we as consumers really get more control over our finances? In this first of a series on automation and our wallets, we explore a digital revolution in how we pay for things. We meet: Umar Farooq, CEO of Onyx by J.P. Morgan Chase Josh Woodward, Director of product management for Google Pay Ed McLaughlin, President of operations and technology for MasterCard Craig Vosburg, Chief product officer for MasterCard Credits This episode was produced by Anthony Green, with help from Jennifer Strong, Karen Hao, Will Douglas Heaven and Emma Cillekens. We’re edited by Michael Reilly. Special thanks to our events team for recording part of this episode at our AI conference, Emtech Digital.

Computers are ranking the way people look—and the results are influencing the things we do, the posts we see, and the way we think. Ideas about what constitutes “beauty” are complex, subjective, and by no means limited to physical appearances. Elusive though it is, everyone wants more of it. That means big business and increasingly, people harnessing algorithms to create their ideal selves in the digital and, sometimes, physical worlds. In this episode, we explore the popularity of beauty filters, and sit down with someone who’s convinced his software will show you just how to nip and tuck your way to a better life. We meet: Shafee Hassan, Qoves Studio founder  Lauren Rhue, Assistant Professor of Information Systems at the Robert H. Smith School of Business Credits: This episode was reported by Tate Ryan-Mosley, and produced by Jennifer Strong, Emma Cillekens, Karen Hao and Anthony Green. We’re edited by Michael Reilly and Bobbie Johnson.  

Host Jennifer Strong and MIT Technology Review’s editors explore what it means to entrust AI with our most sensitive decisions.

Cameras in stores aren’t anything new—but these days there are AI brains behind the electric eyes. In some stores, sophisticated systems are tracking customers in almost every imaginable way, from recognizing their faces to gauging their age, their mood, and virtually gussying them up with makeup. The systems rarely ask for people’s permission, and for the most part they don’t have to. In our season 1 finale, we look at the explosion of AI and face recognition technologies in retail spaces, and what it means for the future of shopping. We meet: RetailNext CTO Arun Nair, L'Oreal's Technology Incubator Global VP Guive Balooch, Modiface CEO Parham Aarabi Biometrics pioneer and Chairman of ID4Africa Joseph Atick Credits: This episode was reported and produced by Jennifer Strong, Anthony Green, Tate Ryan-Mosley, Emma Cillekens and Karen Hao. We’re edited by Michael Reilly and Gideon Lichfield.

Two weeks after her forced exit, the AI ethics researcher reflects on her time at Google, how to increase corporate accountability, and the state of the AI field. We meet: Dr. Timnit Gebru Find more reporting: https://www.technologyreview.com/2020/12/16/1014634/google-ai-ethics-lead-timnit-gebru-tells-story/ https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/ Google's email to employees: https://twitter.com/JeffDean/status/1334953632719011840 Gebru's email to the listserv Google Brain Women and Allies: https://www.platformer.news/p/the-withering-email-that-got-an-ethical The petition from Google Walkout: https://googlewalkout.medium.com/standing-with-dr-timnit-gebru-isupporttimnit-believeblackwomen-6dadc300d382 Credits: This episode was reported by Karen Hao, edited by Jennifer Strong, Niall Firth, Gideon Lichfield and Michael Reilly, and produced with help from Anthony Green, Emma Cillekens and Benji Rosen.

Face mapping and other tracking systems are changing the sports experience in the stands and on the court. In part-three of this latest series on facial recognition, Jennifer Strong and the team at MIT Technology Review jump on the court to unpack just how much things are changing.  We meet:  Donnie Scott, senior vice president of public security, IDEMIA Michael D'Auria, vice president of business development, Second Spectrum Jason Gay, sports columnist, The Wall Street Journal Rachel Goodger, director of business development, Fancam Rich Wang, director of analytics and fan engagement, Minnesota Vikings Credits:  This episode was reported and produced by Jennifer Strong, Anthony Green, Tate Ryan-Mosley, Emma Cillekens and Karen Hao. We’re edited by Michael Reilly and Gideon Lichfield. 

Facial recognition technology is being deployed in housing projects, homeless shelters, schools, even across entire cities—usually without much fanfare or discussion. To some, this represents a critical technology for helping vulnerable communities gain access to social services. For others, it’s a flagrant invasion of privacy and human dignity. In this episode, we speak to the advocates, technologists, and dissidents dealing with the messy consequences that come when a technology that can identify you almost anywhere (even if you’re wearing a mask) is deployed without any clear playbook for regulating or managing it. We meet:  Eric Williams, senior staff attorney at Detroit Justice Center Fabian Rogers, community advocate at Surveillance Technology Oversight Project Helen Knight, founder of Tech for Social Good Ray Bolling, president and co-founder of Eyemetric Identity Systems Mary Sunden, executive director of the Christ Church Community Development Corporation Credits:  This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley, Emma Cillekens, and Karen Hao. We’re edited by Michael Reilly and Gideon Lichfield.

Moves have been made to restrict the use of facial recognition across the globe. In part one of this series on face ID, Jennifer Strong and the team at MIT Technology Review explore the unexpected ways the technology is being used, including how the technology is being turned on police.   We meet:  Christopher Howell, data scientist and protester.  Credits:  This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley and Emma Cillekens, and Karen Hao. We’re edited by Michael Reilly and Gideon Lichfield.

The use of facial recognition by police has come under a lot of scrutiny. In part three of our four-part series on face ID, host Jennifer Strong takes you to Sin City, which actually has one of America’s most buttoned-up policies on when cops can capture your likeness. She also finds out why celebrities like Woody Harrelson are playing a starring role in conversations about this technology. This episode was originally published August 12, 2020. We meet:  Albert Fox Cahn, Surveillance Technology Oversight Project Phil Mayor, ACLU Michigan Captain Dori Koren, Las Vegas Police  Assistant Chief Armando Aguilar, Miami Police  Credits:  This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley and Emma Cillekens. We had help from Benji Rosen and Karen Hao. We’re edited by Michael Reilly and Gideon Lichfield.

In the second of two exclusive interviews, Technology Review’s Editor-in-Chief Gideon Lichfield sat down with Parag Agrawal, Twitter’s Chief Technology officer to discuss the rise of misinformation on the social media platform. Agrawal discusses some of the measures the company has taken to fight back, while admitting Twitter is trying to thread a needle of mitigating harm caused by false content without becoming an arbiter of truth. This conversation is from the EmTech MIT virtual conference and has been edited for clarity. For more of coverage on this topic, check out this week's episode of Deep Tech: https://cms.megaphone.fm/channel/deep-tech?selected=MIT6065037377 and our coverage at https://www.technologyreview.com/topic/tech-policy/ Credits: This episode from EmTech MIT was produced by Jennifer Strong and Emma Cillekens, with special thanks to Brian Bryson and Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield.

Misinformation and social media have become inseparable from one another; as platforms like Twitter and Facebook have grown to globe-spanning size, so too has the threat posed by the spread of false content. In the midst of a volatile election season in the US and a raging global pandemic, the power of information to alter opinions and save lives (or endanger them) is on full display. In the first of two exclusive interviews with two of the tech world’s most powerful people, Technology Review’s Editor-in-Chief Gideon Lichfield sits down with Facebook CTO Mike Schroepfer to talk about the challenges of combating false and harmful content on an online platform used by billions around the world. This conversation is from the EmTech MIT virtual conference and has been edited for length and clarity. For more of coverage on this topic, check out this week's episode of Deep Tech: https://cms.megaphone.fm/channel/deep-tech?selected=MIT6065037377 and our coverage at https://www.technologyreview.com/topic/tech-policy/ Credits: This episode from EmTech was produced by Jennifer Strong and Emma Cillekens, with special thanks to Brian Bryson and Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield.

Defining what is, or isn’t artificial intelligence can be tricky (or tough). So much so, even the experts get it wrong sometimes. That’s why MIT Technology Review’s Senior AI Reporter Karen Hao created a flowchart to explain it all. In this bonus content our Host Jennifer Strong and her team reimagine Hao’s reporting, gamifying it into an audio postcard of sorts.  If you would like to see the original reporting visit:  https://www.technologyreview.com/2018/11/10/139137/is-this-ai-we-drew-you-a-flowchart-to-work-it-out/  Credits: This episode was reported by Karen Hao. It was adapted for audio and produced by Jennifer Strong and Emma Cillekens. The voices you heard were Emma Cillekens, as well as Eric Mongeon and Kyle Thomas Hemingway from our art team. We’re edited by Michael Reilly and Niall Firth.

AI can read your emotional response to advertising and your facial expressions in a job interview. But if it can already do all this, what happens next? In part two of a series on emotion AI, Jennifer Strong and the team at MIT Technology Review explore the implications of how it’s used and where it’s heading in the future. We meet:  Shruti Sharma, VSCO  Gabi Zijderveld, Affectiva Tim VanGoethem, Harman Rohit Prasad, Amazon Meredith Whittaker, NYU's AI Now Institute Credits: This episode was reported and produced by Jennifer Strong, Karen Hao, Tate Ryan-Mosley, and Emma Cillekens. We had help from Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield. 

Researchers have spent years trying to crack the mystery of how we express our feelings. Pioneers in the field of emotion detection will tell you the problem is far from solved. But that hasn’t stopped a growing number of companies from claiming their algorithms have cracked the puzzle. In part one of a two-part series on emotion AI, Jennifer Strong and the team at MIT Technology Review explore what emotion AI is, where it is, and what it means. We meet:  Rana El Kaliouby, Affectiva Lisa Feldman Barrett, Northeastern University Karen Hao, MIT Technology Review Credits: This episode was reported and produced by Jennifer Strong and Karen Hao, with Tate Ryan-Mosley and Emma Cillekens. We had help from Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield. 

Automated driving is advancing all the time, but there’s still a critical missing ingredient: trust. Host Jennifer Strong meets engineers building a new language of communication between automated vehicles and their human occupants, a crucial missing piece in the push toward a driverless future. We meet:  Dr. Richard Corey and Dr. Nicholas Giudice, founders of the VEMI Lab at the University of Maine Ryan Powell, UX Design & Research at Waymo. Rashed Haq, VP of Robotics at Cruise Credits: This episode was reported and produced by Jennifer Strong,Tanya Basu, Emma Cillekens and Tate Ryan-Mosley. We had help from Karen Hao and Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield. 

What weird bugs did you pick up last time you rode a subway train? A global network of scientists mapping the DNA of urban microbes and using AI to look for patterns pivots to tracking covid-19. Join host Jennifer Strong as she rides along on a subway-swabbing mission and talks to scientists racing to find an existing drug that might treat the disease. We meet:  Weill Cornell Medicine's Christopher Mason and David Danko BenevolentAI CEO Baroness Joanna Shields Credits: This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley, Emma Cillekens and Karen Hao with help from Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield. Our technical director is Jacob Gorski. 

What happens when an algorithm gets it wrong? In the first of a four-part series on face ID, Jennifer Strong and the team at MIT Technology Review explore the arrest of a man who was falsely accused of a crime using facial recognition. The episode also starts to unpack the complexities of this technology and introduce some thorny questions about its use.   We meet:  Robert and Melissa Williams  Peter Fussey, University of Essex Hamid Khan, Stop LAPD Spying Coalition Credits: This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley and Emma Cillekens. We had help from Karen Hao and Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield. Our technical director is Jacob Gorski. Special thanks to Kyle Thomas Hemingway and Eric Mongeon.

Clearview AI has built one of the most comprehensive databases of people’s faces in the world. Your picture is probably in there (our host Jennifer Strong’s was). In the second of a four-part series on facial recognition, we meet the CEO of the controversial company who tells us our future is filled with face recognition—regardless of whether it's regulated or not. We meet:  Hoan Ton-That, Clearview AI  Alexa Daniels-Shpall, Police Executive Research Forum  Credits:  This episode was reported and produced by Jennifer Strong, with Tate Ryan-Mosely and Emma Cillekens, with special thanks to Karen Hao and Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield. Our technical director is Jacob Gorski.

The use of facial recognition by police has come under a lot of scrutiny. In part-three of our series, host Jennifer Strong takes you to Sin City, which actually has one of America’s most buttoned-up policies on when cops can capture your likeness. She also finds out why celebrities like Woody Harrelson are playing a starring role in conversations about this technology.  We meet:  Albert Fox Cahn, Surveillance Technology Oversight Project Phil Mayor, ACLU Michigan Captain Dori Koren, Las Vegas Police  Assistant Chief Armando Aguilar, Miami Police  Credits:  This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley and Emma Cillekens. We had help from Benji Rosen and Karen Hao. We’re edited by Michael Reilly and Gideon Lichfield. Our technical director is Jacob Gorski. 

Police have a history of using face ID to arrest protestors—something not lost on activists since the death of George Floyd. In the last of a four-part series on facial recognition, host Jennifer Strong explores the way forward for the technology and examines what policy might look like.  We meet: Artem Kuharenko, NTechLab Deborah Raji, AI Now Institute Toussaint Morrison, Musician, actor, and Black Lives Matter organizer Jameson Spivack, Center on Privacy & Technology  Credits: This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley, Emma Cillekens, and Karen Hao. We had help from Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield. Our technical director is Jacob Gorski. 

Welcome to a podcast about the automation of everything. Host Jennifer Strong and MIT Technology Review’s editors explore what it means to entrust AI with our most sensitive decisions.