(birds chirping)
- The train has left the station.
(electronic warbling)
It is inevitable
that artificial intelligence will consume our lives.
(upbeat music)
People don't realize that they are interacting
with AI agents every day, multiple times a day.
If you are online, if you are using any type of map,
if you are calling someone on the phone,
you are using a ton of algorithms.
(phone chimes)
There is so much opportunity to enhance our quality of life.
But with that opportunity, it comes responsibility as well.
(static crackling)
(birds chirping)
My whole thing is, how do you take control?
How are you provided the power to ensure
that this doesn't have a negative impact?
(bright music) (computers warbling)
(phone chiming)
- [Reporter] Just what are digital computers?
Are they super human machines
that can solve any kind of problem?
(robots whirring)
- Our technology is impacting the world in positive ways,
but also negative ways.
And therefore it is our responsibility to ensure
that we are mitigating the negative,
because we can do it on the algorithm side
if we just take a moment to think about it.
(clapperboard clicks)
Hi, my name is Ayanna Howard, Dr. H, and I am a roboticist.
(bell dings)
It is an exciting time to be a roboticist,
to be designing and developing AI algorithms,
because AI sort of rules the world.
(robot warbles)
- [Robot] Hello, human.
(computer warbling)
- One of the things that AI is used for
is more social interactions,
everything from social media, to even dating apps.
And so you think, oh, there's no harm in that.
But the fact is, people are fairly easy to model,
which means that AI can influence our behaviors.
(bright music)
These AI systems are cast as authority figures.
These AI systems are cast as the experts,
because they have more data
than I possibly could know about as an individual human.
And so we trust that these systems know more than us,
and therefore, we are more likely
to take whatever the AI system says, and take it as truth.
And that's kind of a problem,
because these AI agents make mistakes.
(dramatic music)
So after NASA, I came to Georgia Tech,
and started up my own lab.
My group works in this area of Deception and Trust.
So if an AI system tells a human something,
if an AI system suggests something,
an individual is more likely to take that guidance as truth.
That's a form of trust.
What we wanted to look at is if a robot made mistakes,
and did something that might harm you,
would you trust the robot
in terms of its decision making?
And so we brought people into a building.
(suspenseful music)
And we simulated emergency evacuation smoke and fire alarms.
And, you know, the robot, it just would spin in place,
and things like that.
(bell ringing)
And people, time and time again,
would follow the guidance of the robot.
And in certain cases, alarms are going, smoke is going,
and the robot's just sitting there, like,
I don't know what I'm doing,
and people would just stand there,
and be like, hm, well, robot must know what it's doing,
because, you know, it's smart, right?
And again, it blew away our hypothesis,
because we did not expect that.
(suspenseful music)
My lab and my students,
we also work on creating solutions for some of these systems
that aren't done right,
because we can very easily lose our ability
to have autonomy,
once we start believing and trusting all the algorithms
that come out.
(suspenseful music)
So ethics is really important when it comes to AI,
because these systems are gonna be used by everybody.
I wanna make sure that people
and the general public understands that AI is here, right?
It's in everything that we do.
But also that we have a power to decide
how we're gonna use the systems,
and understand that we have a choice.
I want people to understand what AI is.
(dramatic orchestra music)
- [Reporter] Yet as complicated as they might appear,
digital computers are basically simple.
- So an algorithm, and we throw out,
algorithm, artificial intelligence,
So basically, an algorithm is
(computer warbling) a piece of software
that takes data inputs,
and makes a decision based on that input.
(fanfare music)
This is not new, right?
So the algorithms, people think,
oh deep neural networks, like this is,
no, no, no, no, honey.
A lot of these algorithms have existed.
at least since the sixties and the seventies.
(robot warbling)
- [Reporter] We are experimenting
with a mobile robot associated with intelligence.
(upbeat jazz music)
- To create these intelligent agents,
it has to have data, and the data is based on people.
So one of the things about using these data sets
is that they maintain some historic biases.
(drum rolling)
Explicit bias is discrimination, right? That's racism.
Implicit bias is just the way that we grew up.
The perceptions that we have is implicit,
because we don't necessarily know how we got them.
You know, implicit bias,
we think of as more of a human attribute or characteristic.
And we talk about the data,
but the AI system then inherits that bias,
which then unfairly disadvantages certain groups.
(drum rolling)
(gentle music)
So robots aren't inherently racist or sexist,
but they can learn to be.
One of the problems about AI,
the power is that it's learning from humans.
The negative is that it's learning from humans.
(clock ticking rapidly)
And historically, people have changed their perception.
Historically, people have been biased and realized,
oh yeah, women, maybe they should vote.
Right, and things have changed and shifted.
And that means that when the systems are learning
from human data, they may also be learning some
of that historical bias that is present
that we recognize now, but the AI system doesn't.
(dramatic orchestra music)
- [Announcer] The car is designed from the inside out.
- Engineering traditionally has not really thought
about social impact.
And a lot of times we were like, well, why?
It's engineering.
How does someone who's female,
why does that make a difference?
But the fact is is that when we design solutions,
if we don't have someone with a different experience,
we're gonna design the wrong solution.
As an example, airbags, because the teams were mostly men,
didn't realize that the average human is not 5'9"
and 180 pounds.
That's not the average human.
And then we found out
that more women die in car crashes because of the airbags.
(machinery whirring)
A decision was made where no one just asked,
because no one was in there to say,
"Hey, you know, humans include females as well."
(birds chirping)
My dad was an engineer.
My mom was a mathematician.
I thought it was a typical African-American family.
(gentle music) So as a high school student,
my label was a smart kid, right?
I was in the gifted classes.
I was a brainiac,
but in college, I very quickly realized
that my label was Black.
In my engineering classes, I felt so isolated.
Most of my classmates came from private schools,
and most of my classmates came
from environments that weren't like mine.
And when you look around and no one looks like you,
where your instructors don't look like you, you think,
well, maybe engineering is not what I should be doing,
because obviously, there's not a place for me here.
(gentle music)
If you have someone who wanted to be an engineer,
wanted to be a roboticist since they were basically
in the sixth grade,
and in one year, you have them doubting themselves,
there's something fundamentally wrong with the system.
(gentle music)
Engineering is about problems that have not been solved,
and they haven't been solved for a reason.
They haven't been solved because people are looking
at it the exact same way.
So I started realizing the value of my perspective
when I became basically a project manager at NASA,
because again, I was going into the room,
and I was talking to engineers and I was like,
"Hey, have you thought about it this way?"
And it was so interesting because it was like,
"Oh, no, we hadn't,"
and it wasn't like I read a different book,
or I studied in a different way.
It's just that the lens that I looked
at things was just different.
In order to solve the hard problems
in society and the world, you have to think outside the box.
(robot warbles)
- [Robot] Hello, human.
(bouncy piano music)
Oh, it's nice in here.
- My name is Kantwon Rogers.
I'm currently a third year computer science PhD student.
So in this lab, we investigate and try to understand,
how do humans interact with AI,
artificial intelligence systems, and robotics?
Most people in the lab, and Ayanna herself,
likes to look at trust, how people come to trust robots,
how people come to trust technology.
But for me, I was like, you know, if I'm gonna work
on something for like six years, I have to be interested.
And I like the drama. I like the spice.
(robot warbles)
Why not think about deception,
which is this offset of trust,
but why don't we spin it in this notion here
about thinking about how these systems are lying to humans,
and what's the extent that we can push that
to be preventative?
Of course, I'm not trying to aid in that robot apocalypse.
(robots warbling)
My research is focused on, it's like a spicy question.
Animals lie, humans lie.
And so should robots and technology lie?
So I'm asking a question of if, when,
and should AI and robots lie to humans?
- [Robot] Hm.
- I feel like a lot of people think it's taboo,
and surprisingly, Ayanna was on board.
(upbeat music)
I have told Ayanna,
I was like, "Man, I don't know if you're a human sometimes."
I swear she doesn't sleep.
(laughs)
Ayanna's goals, I've said that for a while,
when I grow up, I wanna be like Ayanna,
just having her presence in being such a thought leader,
and kind of defying the odds
and breaking the mold of who is seen to be successful
in these spaces is so very empowering for people like me,
who are on the come up,
trying to make a name for themselves.
Ayanna is always thinking about the future,
and how the things that she's working on
and her students are working on are affecting the world.
- Hey, Kantwon.
- What's up?
- How you doing?
- She was not only on board, but very supportive,
and constantly asking me questions,
like, why, like, why is it that you think
that this is something that we should care about?
Whose lives is this actually impacting?
(upbeat jazz music)
When we are creating chatbots
and things that people are interacting with,
those are programmed
in such a way to make people believe that it's a human.
(robot warbles)
- [Robot] I'll try my best to help you.
- To believe that there's certain genders
that this robot or something has,
and it has none of that.
It's just a bunch of wires and circuitry,
but they do this on purpose to manipulate
how people interact with these systems,
and it is a type of deception,
and I think it's important for us to name it as such,
because then as we start pushing
that boundary more and more,
we can then start thinking
about regulation and what should or shouldn't happen.
I've been very fortunate to be mentored
by people in my life that have forced me to think
about these questions, but also life in general.
Being a Black man in the US,
you have to think about (laughs)
who's getting hurt by systems, and yeah.
And so being kind of cultivated in that space,
I think, does give my perspective added value.
(upbeat music)
- Diversity is important for engineering,
diversity of thought, diversity of experiences.
My PhD students represent the world.
They are diverse in terms of gender,
in terms of domestic US versus international,
underrepresented minorities, about half of them
are from those groups versus not.
We learn through interaction.
We learn through questioning, we learn through each other.
And so traditionally when I'm in a classroom, I'm there,
I will ask hard questions.
I will ask sometimes provocative questions.
Just because you can create a perfect gadget
that's fun, should you?
And they are going to think differently.
If we think
about our roles and responsibilities as engineers,
and we think about the role that diversity has
in coming up with solutions,
it means energy, and water, and food scarcity,
and education can be solved by engineers, right?
That's the power of engineering.
(birds chirping)
If we as engineers don't claim this,
we as engineers don't think about our responsibility
when we're creating new technology,
rules and regulations are going to come down on us.
And the problem is, is that when these regulations come,
they will sort of extinguish creativity,
and that's not in anyone's best interest.
And so thinking about what we need to do,
thinking about the checks and balances we can instill
so that the public understands that we got this.
We can do this better.
Let's look at the systems where we know
that there's negative impact, and lean into fixing those.
And so we know that AI is being used in surveillance.
There's some issues.
Well, if it's being used, let's go and lean and fix that.
We know AI is being used in healthcare, for the good,
but there's still some negatives.
Let's go in and fix that.
And I think right now,
making sure we fix what's already being used
is our first priority.
(dramatic music)
And then as we've accomplished that,
one, we'll we'll learn how it's done,
which means as we're designing new applications,
we can then fix them
before these systems are even out there and deployed.
AI is inevitable.
It is part of our future.
It will, and has started to,
become part of our DNA, part of who we are as a society,
part of who we are as a culture and a nation.
And that's the power of AI, but we have to make sure
that we do it right in order to receive all of the benefits,
and mitigate any of the negatives.
I will be the dean
of the College of Engineering at the Ohio State University.
So to be the dean
of a college of engineering is a major deal.
Like all the things I've talking about,
like responsible engineering, as dean,
I can influence the curriculum, so that that happens,
and then it becomes the gold standard
for the rest of the institutions to do this right.
It's a big deal because I get
to mold what the face of engineering looks like.
I get to actually have an impact on ensuring
that engineering looks like the world around,
looks like the solutions that we're creating for the world.
I didn't have that when I was young.
And to be able to do that
for someone makes it so that I know that this is my role.
I know that this is one
of my responsibilities to ensure that people see me.
(dramatic music)