In Machines We Trust

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 do...

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 

Na...

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, a...

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 Assessm...

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 me...

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 be...

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, ...

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, Polic...

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 ...

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

Cr...

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, Faceboo...

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 wor...

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 explosi...

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 t...

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...

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 ...

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 an...

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 Aug...