Dr. Joy Buolamwini, president of The Algorithmic Justice League, discusses her book Unmasking AI, which traces her journey from building robots at MIT to discovering how AI reinforces societal harms. She shares stories from testifying before Congress, meetings at Davos, and conversations with President Biden, arguing that anyone with a face has a stake in how AI gets built.
Let's flash forward to now when you've got your new book out. So for people who watching on video, you can see in the background, there's a copy there unmasking AI. So can you just tell us a bit about, like, what the book's about and who it's for?
Yes. The book is for anyone who's caught in between fear and fascination about what the future of AI looks like and wants to be part of the conversation. So I say if you have a face, you have a place in the conversation about technologies that are shaping our lives. And we know that artificial intelligence systems are being adopted, adopted in many areas. So the book is really my journey from an idealistic immigrant, very much a tech geek, building my robots, excited to be at mit, enamored with the possibilities of technology. And then in my journey, learning that this technology I was so excited about can actually perpetuate so many societal ills, and then finding ways to combat that with whether it's working with people on the front lines, working with people at companies, developers themselves, policymakers, lawmakers. So it's also a book of hope with all of these things we can do to actually build technologies that work well for all of us, not just the privileged few, so we can realize the promises of AI. And you get a lot of behind the scenes of what it's like to be a grad student at MIT Media Lab or what it was like to be at Davos, you know, talking to all of these world leaders and realizing I'd come a long way from my art project or testifying in the halls of Congress. I even talk about my meeting with President Biden and a handful of other AI experts. So it's really inviting you in. And along the way you meet many characters who are well known within the AI space as well. So my hope for the book is that people feel inspired and they feel that they can be part of creating better technologies. And they also know that they don't have to accept AI harms. We can push back. We've done it successfully in the past and we'll continue to do it in the future. So it's an invitation to be part of the conversation and to get a little bit of a behind the scenes peek of what it takes to make AI and change AI.
It is a fascinating read. And I have to say my favorite bit of the book was about you writing your thesis and how things sort of gradually sort of spiraled and you were like, finding challenges to overcome and things like that. So I guess, could we go Back to the start of when you were writing your thesis, like, and you found, okay, we've got this problem with computer vision and facial recognition. So where did you begin with that?
So after I had the issue of coding in a white mask to have my face detected, it became the focus of my master's thesis work. And so I wanted to see again if it was just my face, if it was just the lighting conditions, or if there might actually be some systematic bias on the base of skin type and also on the base of somebody's gender. And the way I decided to even focus on gender classification is I had done a TED feature talk, and I decided to take my profile image and run it through online demos from different companies with their facial analysis systems. So some didn't detect my face at all. Like, the white mass fail. And then others that did detect my face, they were labeling me male, which I am not. And so that's when I said, huh, maybe there's something to explore here on the gender aspect of things and looking at gender and skin types. So that's how I ended up going to do this research that then became known as the Gender Shades project. So that was my MIT master's thesis work. And then once I finished the master's, I published it with my good friend and longtime collaborator, Dr. Timit Gabriel. So the Gender Shades paper that most people know is the 2008 published paper. The original work is based on my 2017 master's thesis. And if you go to GS.ajl.org all the various variations, data sets, all. All the things you imagine to know about the project are there for your listeners who might be curious in learning a bit more or reading the various research papers that came from that work.
