The story of AI as told by the people who invented it

Welcome to I was there when, a new oral history project from In machines that we trust podcast. It features stories of breakthroughs in artificial intelligence and computing, told by people who witnessed them. In this first episode, we meet Joseph Atik, who helped create the first commercially viable facial recognition system.


The episode was produced by Jennifer Strong, Anthony Green and Emma Silllekens with the help of Lindsay Muscato. It was edited by Michael Reilly and Mat Honan. It is mixed by Garrett Lang and sound and music by Jacob Gorski.

Full transcript:


Jennifer: I’m Jennifer Strong, MC In machines that we trust

I want to tell you something that we have been working on behind the scenes for a while.

It is called I was there when

It is an oral history project that tells the story of the breakthroughs in artificial intelligence and computing … narrated by people who witnessed them.

Joseph Atik: And when I entered the room, he noticed my face, made it stand out from the background and said, “I see Joseph,” and that was the moment when the hair on my back … I felt that something had happened. We were witnesses.

Jennifer: We started with the person who helped create the first commercially viable facial recognition system … back in the 90s …


I am Joseph Atik. Today, I am the Executive Chair of ID for Africa, a humanitarian organization dedicated to empowering people in Africa with a digital identity so they can access services and exercise their rights. But I have not always been in the humanitarian field. After earning my PhD in mathematics, I and my co-workers made several fundamental breakthroughs that led to the first commercially viable face recognition. This is why people call me the founding father of facial recognition and the biometric industry. The algorithm for how the human brain recognizes familiar faces became clear when we were doing mathematical research and I was working at the Institute for Advanced Study in Princeton. But he was far from understanding how you would implement such a thing.

It has been a long period of programming and failure, programming and failure. And one night, in fact, in the early morning, we just completed a version of the algorithm. We sent the source code for compilation to get the launch code. And we went out, I went to the toilet. And then when I got back to the room, the source code was compiled by the machine and returned. And usually after compilation it starts automatically, and when I entered the room, he noticed a person entering the room, he noticed my face, pulled it out of the background and said: “I see Joseph.” and that was the moment when the hairs on my back – I felt that something had happened. We were witnesses. And I started calling other people who were still in the laboratory, and each of them came into the room.

And it said, “I see Norman. I will see Paul, I will see Joseph. ” And we kind of took turns running around the room to see how much he could find in the room. This was the moment of truth when, I would say, several years of work finally resulted in a breakthrough, although in theory no additional breakthrough was required. The fact that we figured out how to do this and finally saw this opportunity in action was very, very rewarding and satisfying. We’ve built a team that’s more like a development team than a research team focused on bringing all of these capabilities to the PC platform. And that was the birth, really the birth of commercial face recognition, I would say, in 1994.

My anxiety started very quickly. I saw a future with nowhere to hide, with cameras everywhere, the commercialization of computers, and the improvement in computing power of computers. So in 1998 I lobbied the industry and said that we need to develop principles for responsible use. And for a while I felt good, because I felt that we got it right. I felt that we had introduced responsible use code that any implementation should follow. However, this code has not stood the test of time. The reason is that we did not expect the emergence of social media. In fact, at the time we were creating the code in 1998, we said that the most important element in the face recognition system is the database of famous people with tags. We said that if I was not in the database, the system would be blind.

And it was difficult to create the database. In the best case, we could build thousands of 10,000, 15,000, 20,000, because each image had to be scanned and entered manually – the world we live in today, we are now in a mode where we allowed the beast to get out of the bag. feeding him billions of faces and helping him tag himself. Um, we are now in a world where any hope of controlling and holding everyone accountable in the use of facial recognition is difficult. And at the same time, there is no shortage of famous faces on the Internet, because you can just scrape off, as has happened with some companies recently. And so I started to panic in 2011 and wrote an article that said it was time to press the panic button because the world was moving in a direction where facial recognition would be ubiquitous and faces would be available everywhere. in databases.

At that time people said that I was an alarmist, but today they understand that this is exactly what is happening today. So where do we go from here? I lobbied for legislation. I’ve lobbied for a legal framework that obliges you to use someone else’s face without their consent. So this is no longer a technological problem. We cannot contain this powerful technology by technical means. There must be some kind of legal framework. We cannot let technology get ahead of us. Ahead of our values, ahead of what we think is acceptable.

The issue of consent continues to be one of the most difficult and complex issues when it comes to technology, just notifying someone else doesn’t mean enough. I need to give consent. They need to understand the implications of what this means. And it’s not easy to say that we signed up, and that was enough. We told people, and if they didn’t want to, they could go anywhere.

And I also find it so easy to be seduced by striking technological features that can give us a short-term edge in our lives. And then we realize that we have given up something too precious. And by this point we have reduced the sensitivity of the population and have reached the point where we can no longer retreat. That’s what worries me. I’m worried about the fact that facial recognition is thanks to the work of Facebook, Apple and others. I am not saying that this is all illegal. In many ways, this is legal.

We came to a point where the general public could become jaded and insensitive because they saw it all over the place. And maybe in 20 years you will leave the house. You will no longer have expectations that you did not have. Dozens of people you cross along the way will not recognize. I think that at this point the public will be very alarmed because the media will start reporting cases of people being persecuted. People were targeted, people were even selected based on their condition on the street and kidnapped. I believe that we have a great responsibility.

And so I think the issue of consent will continue to haunt the industry. And until this issue becomes a result, it may not be resolved. I think we need to set limits on what can be done with this technology.

My career also taught me that being ahead too much is not good because face recognition as we know it today was invented in 1994. But most people think it was invented by Facebook and the machine learning algorithms that are now spreading around the world. Basically, at some point I had to step down as CEO because I was cutting back on the technology that my company was going to promote out of fear of negative consequences for humanity. Therefore, I believe that scientists need to have the courage to look into the future and see the consequences of their work. I am not saying that they should stop making breakthroughs. No, you have to act with full force, make more breakthroughs, but we also have to be honest with ourselves and basically warn the world and politicians that this breakthrough has its pros and cons. And therefore, when using this technology, we need some kind of guidance and framework to make sure that it is directed towards a positive application and not a negative one.

Jennifer: I was there when … is an oral history project that tells the stories of people who have witnessed or made breakthroughs in artificial intelligence and computing.

Do you have a story to tell? Do you know anyone who knows? Email us at [email protected]


Jennifer: This episode was recorded in New York in December 2020 and produced by me with the help of Anthony Green and Emma Silllekens. We were edited by Michael Reilly and Mat Honan. Our sound engineer Garrett Lang … with sound design and music by Jacob Gorski.

Thanks for reading, I’m Jennifer Strong.


Source link

Read More

Leave a Reply

Your email address will not be published. Required fields are marked *

Back to top button