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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)