Ayanna Howard is a roboticist and professor at Georgia Tech, director of Human-Automation Systems lab, with research interests in human-robot interaction, assistive robots in the home, therapy gaming apps, and remote robotic exploration of extreme environments.

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OUTLINE:
0:00 - Introduction
2:09 - Favorite robot
5:05 - Autonomous vehicles
8:43 - Tesla Autopilot
20:03 - Ethical responsibility of safety-critical algorithms
28:11 - Bias in robotics
38:20 - AI in politics and law
40:35 - Solutions to bias in algorithms
47:44 - HAL 9000
49:57 - Memories from working at NASA
51:53 - SpotMini and Bionic Woman
54:27 - Future of robots in space
57:11 - Human-robot interaction
1:02:38 - Trust
1:09:26 - AI in education
1:15:06 - Andrew Yang, automation, and job loss
1:17:17 - Love, AI, and the movie Her
1:25:01 - Why do so many robotics companies fail?
1:32:22 - Fear of robots
1:34:17 - Existential threats of AI
1:35:57 - Matrix
1:37:37 - Hang out for a day with a robot

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The following is a conversation with Ayana Howard.

She's a roboticist, professor at Georgia Tech and director of the Human Automation Systems Lab with research interests in human-robot interaction, assistive robots in the home, therapy gaming apps, and remote robotic exploration of extreme environments.

Like me, in her work, she cares a lot about both robots and human beings, and so I really enjoyed this conversation.

This is the Artificial Intelligence Podcast.

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And now here's my conversation with Ayana Howard.

What or who is the most amazing robot you've ever met?

Or perhaps had the biggest impact on your career?

I haven't met her, but I grew up with her.

Think about it, Like anything you wanted, it was like magic.

So people not only anthropomorphize, but project whatever they wish for the robot to be onto.

She every so often had an attitude, right, she kept us honest, she would push back sometimes when George was doing some weird stuff.

But she cared about people, especially the kids.

And you've said that people don't want their robots to be perfect.

Just like you said, Rosie pushed back a little bit every once in a while.

Yeah, so I think it's that, so if you think about robotics in general, we want them because they enhance our quality of life.

And usually that's linked to something that's functional.

Even if you think of self-driving cars, why is there a fascination?

Like there's the like Saturday driving where I can just speed, but then there's the, I have to go to work every day and I'm in traffic for an hour.

And so robots are designed to basically enhance our ability to increase our quality of life.

And so the perfection comes from this aspect of interaction.

If I think about how we drive, if we drove perfectly, we would never get anywhere, right?

So think about how many times you had to run past the light because you see the car behind you is about to crash into you, or that little kid kind of runs into the street and so you have to cross on the other side because there's no cars, right?

Like if you think about it, we are not perfect drivers.

And so if you have a robot that is perfect in that sense of the word, they wouldn't really be able to function with us.

Can you linger a little bit on the word perfection?

So from the robotics perspective, what does that word mean and how is sort of the optimal behavior as you're describing different than what we think of as perfection?

Yeah, so perfection if you think about it in the more theoretical point of view, it's really tied to accuracy, right?

So if I have a function, can I complete it at 100% accuracy with 0 errors?

And so that's kind of, if you think about perfection in the sense of the word.

And in a self-driving car realm, do you think from a robotics perspective, we kind of think that perfection means following the rules perfectly, sort of defining, staying in the lane, changing lanes, when there's a green light, you go, when there's a red light, you stop.

And that's the, and be able to perfectly see all the entities in the scene.

That's the limit of what we think of as perfection.

And I think that's where the problem comes is that when people think about perfection for robotics, the ones that are the most successful are the ones that are quote unquote perfect, like I said, Rosie is perfect, but she actually wasn't perfect in terms of accuracy, but she was perfect in terms of how she interacted and how she adapted.

And I think that's some of the disconnect is that we really want perfection with respect to its ability to adapt to us.

We don't really want perfection with respect to 100% accuracy with respect to the rules that we just made up anyway.

Right, and so I think there's this disconnect sometimes between what we really want and what happens.

And we see this all the time, like in my research, right?

Like the optimal, quote unquote optimal interactions are when the robot is adapting based on the person, not 100% following what's optimal based on the roles.

Just to linger on autonomous vehicles for a second, just your thoughts maybe off the top of your head, how hard is that problem do you think based on what we just talked about?

You know, there's a lot of folks in the automotive industry that are very confident from Elon Musk to Waymo to all these companies.

The gap between the perfection and the human definition of how you actually function in this world.

So I remember when all the big companies started to heavily invest in this.

And there was a number of, even roboticists, as well as folks who were putting in the VCs and corporations, Elon Musk being 1 of them, that said, self-driving cars on the road with people, you know, within 5 years.

And now people are saying, 5 years, 10 years, 20 years.

I think if you look at some of the things that are being successful is these basically fixed environments where you still have some anomalies, right?

You still have people walking, you still have stores, but you don't have other drivers, like other human drivers, or is a dedicated space for the cars.

Because if you think about robotics in general, where it's always been successful is in, I mean, you can say manufacturing, like way back in the day, right?

But like when we can carve out scenarios that are closer to that space, then I think that it's where we are.

So a closed campus where you don't have self-driving cars and maybe some protection so that the students don't jet in front just because they wanna see what happens.

Like having a little bit, I think that's where we're gonna see the most success in the near future.

Right, not 55, 60, 70 miles an hour, but the speed of a golf cart, right?

So that said, the most successful in the automotive industry robots operating today in the hands of real people are ones that are traveling over 55 miles an hour and in unconstrained environments, which is Tesla vehicles, so Tesla autopilot.

So I would love to hear sort of your, just thoughts of 2 things.

So 1, I don't know if you've gotten to see, you've heard about something called Smart Summon, where Tesla system, autopilot system, where the car drives 0 occupancy, no driver in the parking lot, slowly sort of tries to navigate the parking lot to find itself to you.

And there's some incredible amounts of videos and just hilarity that happens as it awkwardly tries to navigate this environment.

But it's a beautiful nonverbal communication between machine and human that I think is a, it's like, it's some of the work that you do in this kind of interesting human-robot interaction space.

So what are your thoughts in general about

Mainly because I'm a gadget freak, right?

So I say it's a gadget that happens to have some wheels.

I mean, You're a human-robot interaction roboticist.

You're a legit sort of expert in the field.

So what does it feel for a machine to come to you?

It's 1 of these very fascinating things, but also I am hyper, hyper alert, right?

Like my thumb is like, oh, okay, I'm ready to take over.

Even when I'm in my car or I'm doing things like automated backing into, so there's like a feature where you can do this automated backing into a parking space or bring the car out of your garage, or even, you know, pseudo autopilot on the freeway, right?

I can feel like as I'm navigating, I'm like, Yeah, that's an error right there.

Like I am very aware of it, but I'm also fascinated by it.

Like I look and see it's learning from all of these people who are cutting it on.

Like every time I cut it on, it's getting better, right?

And so I think that's what's amazing about it is that.

This nice dance of you're still hypervigilant.

What on the highway if I were to, like what as a roboticist, we'll talk about trust a little bit.

Is it the gadget freak part, like where you just enjoy exploring technology?

Or is that the right actually balance between robotics and humans is where you use it but don't trust it and somehow there's this dance that ultimately is a positive?

Yeah, so I think I just don't necessarily trust technology, but I'm an early adopter, right?

So when it first comes out, I will use everything, but I will be very, very cautious of how I use it.

Do you read about it or do you explore it by just try it?

Do you do like, crudely, to put it crudely, do you read the manual or do you learn through exploration?

If I have to read the manual, then I do design.

Elon Musk is very confident that you kind of take it from where it is now to full autonomy.

So from this human robot interaction where you don't really trust and then you try and then you catch it when it fails to, it's going to incrementally improve itself into full, full where you don't need to participate.

So the promise there is by the end of next year, by the end of 2020 is the current promise.

What's your sense about that journey that Tesla's on?

So there's kind of 3 things going on now.

I think in terms of will people go like as a user, as a adopter, will you trust going to that point?

Like there are some users, and it's because what happens is, when you're hypersensitive at the beginning, and then the technology tends to work, your apprehension slowly goes away and as people we tend to swing to the other extreme, right?

Because like, oh, I was like hyper, hyper fearful or hypersensitive and it was awesome.

And we just tend to swing, that's just human nature.

And so you will have, I mean, and I- It's

a scary notion because most people are now extremely untrusting of autopilot.

And it's a scary notion that there's a certain point where you allow yourself to look at the smartphone for like 20 seconds, and then there'll be this phase shift where it'll be like 20 seconds, 30 seconds, 1 minute, 2 minutes.

I mean, I think of even our use of, I mean, just everything on the internet, right?

Like think about how reliant we are on certain apps and certain engines, right?

20 years ago, people have been like, oh yeah, that's stupid, like that makes no sense.

Like now it's just like, oh, of course, I've been using it.

Of course, aliens, I didn't think they existed, but now it says they do?

Okay, so 1 is the human, And I think there will be a group of individuals that will swing, right?

Teenage, I mean, it'll be teenage, it'll be adults.

There's actually an age demographic that's optimal for technology adoption.

And they're actually pretty easy to find.

So someone like me, who wasn't a roboticist, would probably be the optimal kind of person, right?

Early adopter, okay with technology, very comfortable and not hypersensitive, right?

I'm just hypersensitive because I designed this stuff.

So there is a target demographic that will swing.

The other 1 though is you still have these humans that are on the road.

And as long as we have people that are on the same streets, that's gonna be the big issue.

And it's just because you can't possibly, I won't say, you can't possibly map some of the silliness of human drivers, right?

Like as an example, when you're next to that car that has that big sticker called student driver, right?

Like you are like, oh, either I am going to like go around.

Like we know that that person is just gonna make mistakes that make no sense, right?

Or if I'm in a car and I look over and I see, you know, 2 fairly young looking individuals and there's no student driver bumper and I see them chit chatting to each other, I'm like, oh, that's an issue, right?

So how do you get that kind of information and that experience into basically an autopilot?

And there's millions of cases like that where we take little hints to establish context.

I mean, you said kind of beautifully poetic human things, but there's probably subtle things about the environment, about it being maybe time for commuters to start going home from work, and therefore you can make some kind of judgment about the group behavior of pedestrians, blah, blah, blah,

Like if you're in Boston, how people cross the street, like lights are not an issue, versus other places where people will actually wait for the crosswalk.

And but what I've also seen, so just even in Boston, that intersection to intersection is different.

So every intersection has a personality of its own.

So certain neighborhoods of Boston are different.

So we're kind of, and based on different timing of day, at night, it's all, there's a dynamic to human behavior that we kinda figure out ourselves.

We're not able to introspect and figure it out, but somehow our brain learns it.

And so you're saying, is there a shortcut?

Is there something that could be done, you think, that, you know, that's what we humans do.

Do you necessarily need to build a bird that flies or can you do an airplane?

So I think the shortcut is, and I kind of, I talk about it as a fixed space, where...

So imagine that there's a neighborhood that's a new smart city or a new neighborhood that says, you know what, we are going to design this new city based on supporting self-driving cars.

And then doing things, knowing that there's anomalies, knowing that people are like this, right?

And designing it based on that assumption that like, we're gonna have this, that would be an example of a shortcut.

So you still have people, but you do very specific things to try to minimize the noise a little bit, as an example.

And the people themselves become accepting of the notion that there's autonomous cars, right?

Right, like they move into, so right now you have like a, you will have a self-selection bias, right?

Individuals will move into this neighborhood knowing this is part of the real estate pitch, right?

And so I think that's a way to do a shortcut.

It allows you to collect then data with these variances and anomalies because people are still people, but it's a safer space and is more of an accepting space.

When something in that space might happen because things do, because you already have the self-selection, like people would be, I think, a little more forgiving than other places.

And you said 3 things, did we cover all of

The third is legal law, liability, which I don't really wanna touch, but it's still of concern.

And the mishmash with policy as well, sort of government, all that whole mess.

Do you think from a robotics perspective, you know, if you're kind of honest of what cars do, they kind of threaten each other's life all the time.

So cars are very, I mean, in order to navigate intersections, there's an assertiveness, there's a risk taking.

And if you were to reduce it to an objective function, there's a probability of murder in that function, meaning you killing another human being, and you're using that.

First of all, it has to be low enough to be acceptable to you on an ethical level as an individual human being, but it has to be high enough for people to respect you to not sort of take advantage of you completely and jaywalk and funny and so on.

So, I mean, I don't think there's a right answer here, but how do we solve that?

How do we solve that from a robotics perspective when danger and human life is at stake?

Yeah, as they say, cars don't kill people, people kill people.

Now robotic algorithms would be killing people.

So, it will be robotics algorithms that are pro- no, it will be robotic algorithms don't kill people, developers of robotic algorithms kill people.

Right, I mean 1 of the things is people are still in the loop and at least in the near and midterm, I think people will still be in the loop, at some point, even if it's the developer.

Like we're not necessarily at the stage where, you know, robots are programming autonomous robots with different behaviors quite yet.

Not- It's a scary notion, sorry to interrupt, that a developer has some responsibility in the death of a human being.

I mean, I think that's why the whole aspect of ethics in our community is so, so important, right?

If you think about it, you can basically say, I'm not going to work on weaponized AI, right?

Like people can say, that's not what I'm gonna do.

But yet you are programming algorithms that might be used in healthcare algorithms that might decide whether this person should get this medication or not.

Okay, so that is your responsibility, right?

And if you're not conscious and aware that you do have that power when you're coding and things like that, I think that's just not a good thing.

Like we need to think about this responsibility as we program robots and computing devices much more than we are.

Yeah, so it's not an option to not think about ethics.

I think it's a majority, I would say, of computer science.

It's kind of a hot topic now, I think, about bias and so on, and we'll talk about it, but usually it's kind of, it's like a very particular group of people that work on that.

And then people who do like robotics are like, well, I don't have to think about that.

There's other smart people thinking about it.

It seems that everybody has to think about it.

It's not, you can't escape the ethics, whether it's bias or just every aspect of ethics that has to do with human beings.

So think about, I'm going to age myself, but I remember when we didn't have like testers, right?

As a developer, you had to test your own code, right?

Like you had to go through all the cases and figure it out.

And, you know, and then they realized that, you know, like we probably need to have testing because we're not getting all the things.

And so from there, what happens is like most developers, they do, you know, a little bit of testing, but it's usually like, okay, did my compiler bug out?

Right, like that's how you typically think about as a developer and you'll just assume that it's going to go to another process and they're gonna test it out.

But I think we need to go back to those early days when, you know, you're a developer, you're developing.

There should be like this, a, you know, okay, let me look at the ethical outcomes of this because there isn't a second, like, testing ethical testers, right?

I think that's where we are with respect to ethics.

Like, let's go back to what was good practices and only because we were just developing the field.

I've had to feel it recently in the last few months, but I think it's a good 1 to feel.

Like I've gotten a message, more than 1 from people.

I've unfortunately gotten some attention recently, and I've gotten messages that say that I have blood on my hands because of working on semi-autonomous vehicles.

So the idea that you have semi-autonomy means people would become, would lose vigilance and so on.

That's actually, be humans, as we describe.

And because of that, because of this idea that we're creating automation, there'll be people be hurt because of it.

I mean, it's, you know, it's many nights where I wasn't able to sleep because of this notion.

You really do think about people that might die because of this technology.

Of course, you can then start rationalizing and saying, well, you know what, 40,000 people die in the United States every year and we're trying to ultimately try to save lives.

But the reality is your code you've written might kill somebody.

And that's an important burden to carry with you as you design the code.

of it as a burden if we train this concept correctly from the beginning.

And I use, and not to say that coding is like being a medical doctor, but think about it.

Medical doctors, if they've been in situations where their patient didn't survive, right?

No, every time they come in, they know that there might be a possibility that this patient might not survive.

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Ayanna Howard: Human-Robot Interaction & Ethics of Safety-Critical Systems | Lex Fridman Podcast #66