MIT Technology Review Narrated

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 CareSafe Hammad, CTO, Arctic Shores  Alexandra Reeve Givens, President and CEO, Center for Democracy and TechnologyNathaniel Glasser, Employment Lawyer, Epstein Becker GreenKeith Sonderling, Commissioner, Equal Employment Opportunity Commission (EEOC)We Talked To: Aaron Rieke, Managing Director, UpturnAdam Forman, Employment Lawyer, Epstein Becker GreenBrian Kropp, Vice President Research, GartnerJosh Bersin, Research AnalystJonathan Kestenbaum, Co-Founder and Managing Director, Talent Tech LabsFrank Pasquale, Professor, Brooklyn Law SchoolPatricia (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 CareSafe Hammad, CTO, Arctic Shores  Alexandra Reeve Givens, President and CEO, Center for Democracy and TechnologyNathaniel Glasser, Employment Lawyer, Epstein Becker GreenKeith 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_6YYeXsCredits: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 FloridaTanya Basu, MIT Technology ReviewCredits: 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 BaltimoreMike de Vere, CEO Zest AICredits: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 SiriCade Metz, The New York TimesCharlotte Jee, MIT Technology ReviewCreditsThis 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 ChaseJosh Woodward, Director of product management for Google PayEd McLaughlin, President of operations and technology for MasterCardCraig Vosburg, Chief product officer for MasterCardCreditsThis 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 BusinessCredits: 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.