How to keep human bias out of AI | Kriti Sharma

99,340 views ・ 2019-04-12

TED


Please double-click on the English subtitles below to play the video.

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