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  • Translator: Ivana Korom Reviewer: Joanna Pietrulewicz

  • 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.

  • (Laughter)

  • 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.

  • (Laughter)

  • 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.

  • Thank you.

  • (Applause)

Translator: Ivana Korom Reviewer: Joanna Pietrulewicz

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TED】Kriti Sharma: How to keep human bias out of AI (How to keep human bias out of AI | Kriti Sharma) (【TED】Kriti Sharma: How to keep human bias out of AI (How to keep human bias out of AI | Kriti Sharma))

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    林宜悉 に公開 2021 年 01 月 14 日
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