How to keep human bias out of AI by Kriti Sharma (TED transcript). How many decisions have been made about you today, or this week or this year, by artificial intelligence? I build AI for a living so, full disclosure, I’m kind of a nerd.
And because I’m kind of a nerd, wherever some new news story comes out about artificial intelligence stealing all our jobs, or robots getting citizenship of an actual country, I’m the person my friends and followers message freaking out about the future. We see this everywhere. This media panic that our robot overlords are taking over.
We could blame Hollywood for that. But in reality, that’s not the problem we should be focusing on. There is a more pressing danger, a bigger risk with AI, that we need to fix first. So we are back to this question: How many decisions have been made about you today by AI?
And how many of these were based on your gender, your race or your background? Algorithms are being used all the time to make decisions about who we are and what we want. Some of the women in this room will know what I’m talking about if you’ve been made to sit through those pregnancy test adverts on YouTube like 1,000 times.
Or you’ve scrolled past adverts of fertility clinics on your Facebook feed. Or in my case, Indian marriage bureaus. (Laughter) But AI isn’t just being used to make decisions about what products we want to buy or which show we want to binge watch next. I wonder how you’d feel about someone who thought things like this: “A black or Latino person is less likely than a white person to pay off their loan on time.” “A person called John makes a better programmer than a person called Mary.” “A black man is more likely to be a repeat offender than a white man.”
You’re probably thinking, “Wow, that sounds like a pretty sexist, racist person,” right? These are some real decisions that AI has made very recently, based on the biases it has learned from us, from the humans. AI is being used to help decide whether or not you get that job interview; how much you pay for your car insurance; how good your credit score is; and even what rating you get in your annual performance review.
But these decisions are all being filtered through its assumptions about our identity, our race, our gender, our age. How is that happening? Now, imagine an AI is helping a hiring manager find the next tech leader in the company. So far, the manager has been hiring mostly men. So the AI learns men are more likely to be programmers than women. And it’s a very short leap from there to: men make better programmers than women.
We have reinforced our own bias into the AI. And now, it’s screening out female candidates. Hang on, if a human hiring manager did that, we’d be outraged, we wouldn’t allow it. This kind of gender discrimination is not OK. And yet somehow, AI has become above the law, because a machine made the decision. That’s not it. We are also reinforcing our bias in how we interact with AI. How often do you use a voice assistant like Siri, Alexa or even Cortana?
They all have two things in common: one, they can never get my name right, and second, they are all female. They are designed to be our obedient servants, turning your lights on and off, ordering your shopping. You get male AIs too, but they tend to be more high-powered, like IBM Watson, making business decisions, Salesforce Einstein or ROSS, the robot lawyer. So poor robots, even they suffer from sexism in the workplace.
Think about how these two things combine and affect a kid growing up in today’s world around AI. So they’re doing some research for a school project and they Google images of CEO. The algorithm shows them results of mostly men. And now, they Google personal assistant. As you can guess, it shows them mostly females.
And then they want to put on some music, and maybe order some food, and now, they are barking orders at an obedient female voice assistant. Some of our brightest minds are creating this technology today. Technology that they could have created in any way they wanted. And yet, they have chosen to create it in the style of 1950s “Mad Man” secretary.
Yay! But OK, don’t worry, this is not going to end with me telling you that we are all heading towards sexist, racist machines running the world. The good news about AI is that it is entirely within our control. We get to teach the right values, the right ethics to AI. So there are three things we can do. One, we can be aware of our own biases and the bias in machines around us. Two, we can make sure that diverse teams are building this technology.
And three, we have to give it diverse experiences to learn from. I can talk about the first two from personal experience. When you work in technology and you don’t look like a Mark Zuckerberg or Elon Musk, your life is a little bit difficult, your ability gets questioned. Here’s just one example. Like most developers, I often join online tech forums and share my knowledge to help others.
And I’ve found, when I log on as myself, with my own photo, my own name, I tend to get questions or comments like this: “What makes you think you’re qualified to talk about AI?” “What makes you think you know about machine learning?” So, as you do, I made a new profile, and this time, instead of my own picture, I chose a cat with a jet pack on it. And I chose a name that did not reveal my gender.
You can probably guess where this is going, right? So, this time, I didn’t get any of those patronizing comments about my ability and I was able to actually get some work done. And it sucks, guys. I’ve been building robots since I was 15, I have a few degrees in computer science, and yet, I had to hide my gender in order for my work to be taken seriously.
So, what’s going on here? Are men just better at technology than women? Another study found that when women coders on one platform hid their gender, like myself, their code was accepted four percent more than men. So this is not about the talent. This is about an elitism in AI that says a programmer needs to look like a certain person.
What we really need to do to make AI better is bring people from all kinds of backgrounds. We need people who can write and tell stories to help us create personalities of AI. We need people who can solve problems. We need people who face different challenges and we need people who can tell us what are the real issues that need fixing and help us find ways that technology can actually fix it.
Because, when people from diverse backgrounds come together, when we build things in the right way, the possibilities are limitless. And that’s what I want to end by talking to you about. Less racist robots, less machines that are going to take our jobs — and more about what technology can actually achieve.
So, yes, some of the energy in the world of AI, in the world of technology is going to be about what ads you see on your stream. But a lot of it is going towards making the world so much better. Think about a pregnant woman in the Democratic Republic of Congo, who has to walk 17 hours to her nearest rural prenatal clinic to get a checkup.
What if she could get diagnosis on her phone, instead? Or think about what AI could do for those one in three women in South Africa who face domestic violence. If it wasn’t safe to talk out loud, they could get an AI service to raise alarm, get financial and legal advice. These are all real examples of projects that people, including myself, are working on right now, using AI. So, I’m sure in the next couple of days there will be yet another news story about the existential risk, robots taking over and coming for your jobs.
And when something like that happens, I know I’ll get the same messages worrying about the future. But I feel incredibly positive about this technology. This is our chance to remake the world into a much more equal place. But to do that, we need to build it the right way from the get go. We need people of different genders, races, sexualities and backgrounds. We need women to be the makers and not just the machines who do the makers’ bidding.
We need to think very carefully what we teach machines, what data we give them, so they don’t just repeat our own past mistakes. So I hope I leave you thinking about two things. First, I hope you leave thinking about bias today. And that the next time you scroll past an advert that assumes you are interested in fertility clinics or online betting websites, that you think and remember that the same technology is assuming that a black man will reoffend.
Or that a woman is more likely to be a personal assistant than a CEO. And I hope that reminds you that we need to do something about it. And second, I hope you think about the fact that you don’t need to look a certain way or have a certain background in engineering or technology to create AI, which is going to be a phenomenal force for our future.
You don’t need to look like a Mark Zuckerberg, you can look like me. And it is up to all of us in this room to convince the governments and the corporations to build AI technology for everyone, including the edge cases. And for us all to get education about this phenomenal technology in the future. Because if we do that, then we’ve only just scratched the surface of what we can achieve with AI.
What do you think about this? remember to rate this article “How to keep human bias out of AI” by Kriti Sharma and share it with your friends.
Credit: Kriti Sharma