back to indexAyanna Howard: Human-Robot Interaction & Ethics of Safety-Critical Systems | Lex Fridman Podcast #66
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The following is a conversation with Ayana Howard.
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She's a roboticist, professor Georgia Tech,
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and director of the Human Automation Systems Lab,
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with research interests in human robot interaction,
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assisted robots in the home, therapy gaming apps,
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and remote robotic exploration of extreme environments.
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Like me, in her work, she cares a lot
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about both robots and human beings,
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and so I really enjoyed this conversation.
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This is the Artificial Intelligence Podcast.
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And now, here's my conversation with Ayanna Howard.
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What or who is the most amazing robot you've ever met,
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or perhaps had the biggest impact on your career?
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I haven't met her, but I grew up with her,
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but of course, Rosie.
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So, and I think it's because also.
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Rosie from the Jetsons.
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She is all things to all people, right?
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Like anything you wanted, it was like magic, it happened.
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So people not only anthropomorphize,
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but project whatever they wish for the robot to be onto.
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But also, I mean, think about it.
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She was socially engaging.
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She every so often had an attitude, right?
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She kept us honest.
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She would push back sometimes
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when George was doing some weird stuff.
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But she cared about people, especially the kids.
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She was like the perfect robot.
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And you've said that people don't want
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their robots to be perfect.
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Can you elaborate that?
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What do you think that is?
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Just like you said, Rosie pushed back a little bit
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every once in a while.
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Yeah, so I think it's that.
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So if you think about robotics in general,
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we want them because they enhance our quality of life.
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And usually that's linked to something that's functional.
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Even if you think of self driving cars,
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why is there a fascination?
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Because people really do hate to drive.
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Like there's the like Saturday driving
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where I can just speed,
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but then there's the I have to go to work every day
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and I'm in traffic for an hour.
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I mean, people really hate that.
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And so robots are designed to basically enhance
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our ability to increase our quality of life.
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And so the perfection comes from this aspect of interaction.
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If I think about how we drive, if we drove perfectly,
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we would never get anywhere, right?
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So think about how many times you had to run past the light
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because you see the car behind you
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is about to crash into you.
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Or that little kid kind of runs into the street
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and so you have to cross on the other side
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because there's no cars, right?
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Like if you think about it, we are not perfect drivers.
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Some of it is because it's our world.
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And so if you have a robot that is perfect
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in that sense of the word,
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they wouldn't really be able to function with us.
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Can you linger a little bit on the word perfection?
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So from the robotics perspective,
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what does that word mean
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and how is sort of the optimal behavior
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as you're describing different
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than what we think is perfection?
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Yeah, so perfection, if you think about it
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in the more theoretical point of view,
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it's really tied to accuracy, right?
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So if I have a function,
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can I complete it at 100% accuracy with zero errors?
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And so that's kind of, if you think about perfection
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in the sense of the word.
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And in the self driving car realm,
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do you think from a robotics perspective,
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we kind of think that perfection means
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following the rules perfectly,
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sort of defining, staying in the lane, changing lanes.
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When there's a green light, you go.
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When there's a red light, you stop.
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And that's the, and be able to perfectly see
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all the entities in the scene.
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That's the limit of what we think of as perfection.
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And I think that's where the problem comes
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is that when people think about perfection for robotics,
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the ones that are the most successful
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are the ones that are quote unquote perfect.
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Like I said, Rosie is perfect,
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but she actually wasn't perfect in terms of accuracy,
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but she was perfect in terms of how she interacted
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and how she adapted.
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And I think that's some of the disconnect
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is that we really want perfection
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with respect to its ability to adapt to us.
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We don't really want perfection with respect to 100% accuracy
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with respect to the rules that we just made up anyway, right?
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And so I think there's this disconnect sometimes
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between what we really want and what happens.
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And we see this all the time, like in my research, right?
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Like the optimal, quote unquote optimal interactions
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are when the robot is adapting based on the person,
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not 100% following what's optimal based on the rules.
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Just to link on autonomous vehicles for a second,
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just your thoughts, maybe off the top of the head,
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how hard is that problem do you think
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based on what we just talked about?
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There's a lot of folks in the automotive industry,
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they're very confident from Elon Musk to Waymo
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to all these companies.
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How hard is it to solve that last piece?
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The gap between the perfection and the human definition
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of how you actually function in this world.
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Yeah, so this is a moving target.
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So I remember when all the big companies
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started to heavily invest in this
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and there was a number of even roboticists
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as well as folks who were putting in the VCs
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and corporations, Elon Musk being one of them that said,
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self driving cars on the road with people
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within five years, that was a little while ago.
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And now people are saying five years, 10 years, 20 years,
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some are saying never, right?
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I think if you look at some of the things
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that are being successful is these
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basically fixed environments
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where you still have some anomalies, right?
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You still have people walking, you still have stores,
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but you don't have other drivers, right?
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Like other human drivers are,
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it's a dedicated space for the cars.
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Because if you think about robotics in general,
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where has always been successful?
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I mean, you can say manufacturing,
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like way back in the day, right?
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It was a fixed environment, humans were not part
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of the equation, we're a lot better than that.
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But like when we can carve out scenarios
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that are closer to that space,
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then I think that it's where we are.
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So a closed campus where you don't have self driving cars
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and maybe some protection so that the students
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don't jet in front just because they wanna see what happens.
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Like having a little bit, I think that's where
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we're gonna see the most success in the near future.
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And be slow moving.
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Right, not 55, 60, 70 miles an hour,
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but the speed of a golf cart, right?
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So that said, the most successful
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in the automotive industry robots operating today
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in the hands of real people are ones that are traveling
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over 55 miles an hour and in unconstrained environments,
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which is Tesla vehicles, so Tesla autopilot.
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So I would love to hear sort of your,
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just thoughts of two things.
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So one, I don't know if you've gotten to see,
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you've heard about something called smart summon
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where Tesla system, autopilot system,
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where the car drives zero occupancy, no driver
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in the parking lot slowly sort of tries to navigate
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the parking lot to find itself to you.
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And there's some incredible amounts of videos
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and just hilarity that happens as it awkwardly tries
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to navigate this environment, but it's a beautiful
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nonverbal communication between machine and human
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that I think is a, it's like, it's some of the work
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that you do in this kind of interesting
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human robot interaction space.
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So what are your thoughts in general about it?
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So I do have that feature.
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Do you drive a Tesla?
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I do, mainly because I'm a gadget freak, right?
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So I say it's a gadget that happens to have some wheels.
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And yeah, I've seen some of the videos.
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But what's your experience like?
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I mean, you're a human robot interaction roboticist,
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you're a legit sort of expert in the field.
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So what does it feel for a machine to come to you?
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It's one of these very fascinating things,
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but also I am hyper, hyper alert, right?
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Like I'm hyper alert, like my butt, my thumb is like,
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oh, okay, I'm ready to take over.
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Even when I'm in my car or I'm doing things like automated
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backing into, so there's like a feature where you can do
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this automating backing into a parking space,
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or bring the car out of your garage,
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or even, you know, pseudo autopilot on the freeway, right?
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I am hypersensitive.
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I can feel like as I'm navigating,
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like, yeah, that's an error right there.
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Like I am very aware of it, but I'm also fascinated by it.
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And it does get better.
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Like I look and see it's learning from all of these people
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who are cutting it on, like every time I cut it on,
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it's getting better, right?
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And so I think that's what's amazing about it is that.
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This nice dance of you're still hyper vigilant.
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So you're still not trusting it at all.
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And yet you're using it.
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On the highway, if I were to, like what,
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as a roboticist, we'll talk about trust a little bit.
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How do you explain that?
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Is it the gadget freak part?
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Like where you just enjoy exploring technology?
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Or is that the right actually balance
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between robotics and humans is where you use it,
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but don't trust it.
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And somehow there's this dance
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that ultimately is a positive.
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Yeah, so I think I'm,
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I just don't necessarily trust technology,
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but I'm an early adopter, right?
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So when it first comes out,
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I will use everything,
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but I will be very, very cautious of how I use it.
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Do you read about it or do you explore it by just try it?
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Do you like crudely, to put it crudely,
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do you read the manual or do you learn through exploration?
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If I have to read the manual, then I do design.
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Then it's a bad user interface.
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Elon Musk is very confident that you kind of take it
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from where it is now to full autonomy.
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So from this human robot interaction,
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where you don't really trust and then you try
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and then you catch it when it fails to,
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it's going to incrementally improve itself
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into full where you don't need to participate.
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What's your sense of that trajectory?
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So the promise there is by the end of next year,
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by the end of 2020 is the current promise.
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What's your sense about that journey that Tesla's on?
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So there's kind of three things going on though.
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I think in terms of will people go like as a user,
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as a adopter, will you trust going to that point?
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I think so, right?
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Like there are some users and it's because what happens is
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when you're hypersensitive at the beginning
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and then the technology tends to work,
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your apprehension slowly goes away.
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And as people, we tend to swing to the other extreme, right?
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Because it's like, oh, I was like hyper, hyper fearful
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or hypersensitive and it was awesome.
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And we just tend to swing.
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That's just human nature.
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And so you will have, I mean, and I...
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That's a scary notion because most people
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are now extremely untrusting of autopilot.
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They use it, but they don't trust it.
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And it's a scary notion that there's a certain point
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where you allow yourself to look at the smartphone
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for like 20 seconds.
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And then there'll be this phase shift
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where it'll be like 20 seconds, 30 seconds,
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one minute, two minutes.
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It's a scary proposition.
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But that's people, right?
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That's just, that's humans.
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I mean, I think of even our use of,
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I mean, just everything on the internet, right?
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Like think about how reliant we are on certain apps
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and certain engines, right?
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20 years ago, people have been like, oh yeah, that's stupid.
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Like that makes no sense.
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Like, of course that's false.
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Like now it's just like, oh, of course I've been using it.
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It's been correct all this time.
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Of course aliens, I didn't think they existed,
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but now it says they do, obviously.
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100%, earth is flat.
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So, okay, but you said three things.
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So one is the human.
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Okay, so one is the human.
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And I think there will be a group of individuals
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that will swing, right?
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Teenage, I mean, it'll be, it'll be adults.
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There's actually an age demographic
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that's optimal for technology adoption.
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And you can actually find them.
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And they're actually pretty easy to find.
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Just based on their habits, based on,
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so if someone like me who wasn't a roboticist
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would probably be the optimal kind of person, right?
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Early adopter, okay with technology,
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very comfortable and not hypersensitive, right?
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I'm just hypersensitive cause I designed this stuff.
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So there is a target demographic that will swing.
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The other one though,
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is you still have these humans that are on the road.
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That one is a harder, harder thing to do.
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And as long as we have people that are on the same streets,
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that's gonna be the big issue.
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And it's just because you can't possibly,
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I wanna say you can't possibly map the,
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some of the silliness of human drivers, right?
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Like as an example, when you're next to that car
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that has that big sticker called student driver, right?
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Like you are like, oh, either I'm going to like go around.
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Like we are, we know that that person
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is just gonna make mistakes that make no sense, right?
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How do you map that information?
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Or if I am in a car and I look over
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and I see two fairly young looking individuals
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and there's no student driver bumper
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and I see them chit chatting to each other,
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I'm like, oh, that's an issue, right?
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So how do you get that kind of information
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and that experience into basically an autopilot?
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And there's millions of cases like that
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where we take little hints to establish context.
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I mean, you said kind of beautifully poetic human things,
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but there's probably subtle things about the environment
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about it being maybe time for commuters
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to start going home from work
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and therefore you can make some kind of judgment
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about the group behavior of pedestrians, blah, blah, blah,
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and so on and so on.
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Or even cities, right?
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Like if you're in Boston, how people cross the street,
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like lights are not an issue versus other places
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where people will actually wait for the crosswalk.
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Seattle or somewhere peaceful.
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But what I've also seen sort of just even in Boston
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that intersection to intersection is different.
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So every intersection has a personality of its own.
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So certain neighborhoods of Boston are different.
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So we kind of, and based on different timing of day,
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at night, it's all, there's a dynamic to human behavior
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that we kind of figure out ourselves.
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We're not able to introspect and figure it out,
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but somehow our brain learns it.
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And so you're saying, is there a shortcut?
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Is there a shortcut, though, for a robot?
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Is there something that could be done, you think,
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that, you know, that's what we humans do.
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It's just like bird flight, right?
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That's the example they give for flight.
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Do you necessarily need to build a bird that flies
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or can you do an airplane?
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Is there a shortcut to it?
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So I think the shortcut is, and I kind of,
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I talk about it as a fixed space,
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where, so imagine that there's a neighborhood
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that's a new smart city or a new neighborhood
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that says, you know what?
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We are going to design this new city
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based on supporting self driving cars.
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And then doing things, knowing that there's anomalies,
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knowing that people are like this, right?
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And designing it based on that assumption
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that like, we're gonna have this.
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That would be an example of a shortcut.
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So you still have people,
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but you do very specific things
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to try to minimize the noise a little bit
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And the people themselves become accepting of the notion
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that there's autonomous cars, right?
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Right, like they move into,
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so right now you have like a,
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you will have a self selection bias, right?
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Like individuals will move into this neighborhood
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knowing like this is part of like the real estate pitch,
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And so I think that's a way to do a shortcut.
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One, it allows you to deploy.
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It allows you to collect then data with these variances
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and anomalies, cause people are still people,
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but it's a safer space and it's more of an accepting space.
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I.e. when something in that space might happen
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because things do,
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because you already have the self selection,
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like people would be, I think a little more forgiving
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than other places.
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And you said three things, did we cover all of them?
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The third is legal law, liability,
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which I don't really want to touch,
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but it's still of concern.
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And the mishmash with like with policy as well,
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sort of government, all that whole.
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That big ball of stuff.
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So that's, so we're out of time now.
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Do you think from a robotics perspective,
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you know, if you're kind of honest of what cars do,
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they kind of threaten each other's life all the time.
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So cars are various.
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I mean, in order to navigate intersections,
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there's an assertiveness, there's a risk taking.
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And if you were to reduce it to an objective function,
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there's a probability of murder in that function,
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meaning you killing another human being
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and you're using that.
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First of all, it has to be low enough
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to be acceptable to you on an ethical level
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as an individual human being,
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but it has to be high enough for people to respect you
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to not sort of take advantage of you completely
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and jaywalk in front of you and so on.
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So, I mean, I don't think there's a right answer here,
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but what's, how do we solve that?
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How do we solve that from a robotics perspective
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when danger and human life is at stake?
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Yeah, as they say, cars don't kill people,
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people kill people.
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People kill people.
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And now robotic algorithms would be killing people.
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Right, so it will be robotics algorithms that are pro,
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no, it will be robotic algorithms don't kill people.
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Developers of robotic algorithms kill people, right?
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I mean, one of the things is people are still in the loop
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and at least in the near and midterm,
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I think people will still be in the loop at some point,
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even if it's a developer.
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Like we're not necessarily at the stage
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where robots are programming autonomous robots
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with different behaviors quite yet.
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It's a scary notion, sorry to interrupt,
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that a developer has some responsibility
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in the death of a human being.
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That's a heavy burden.
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I mean, I think that's why the whole aspect of ethics
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in our community is so, so important, right?
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Like, because it's true.
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If you think about it, you can basically say,
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I'm not going to work on weaponized AI, right?
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Like people can say, that's not what I'm gonna do.
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But yet you are programming algorithms
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that might be used in healthcare algorithms
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that might decide whether this person
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should get this medication or not.
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And they don't and they die.
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Okay, so that is your responsibility, right?
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And if you're not conscious and aware
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that you do have that power when you're coding
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and things like that, I think that's just not a good thing.
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Like we need to think about this responsibility
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as we program robots and computing devices
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much more than we are.
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Yeah, so it's not an option to not think about ethics.
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I think it's a majority, I would say, of computer science.
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Sort of, it's kind of a hot topic now,
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I think about bias and so on, but it's,
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and we'll talk about it, but usually it's kind of,
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it's like a very particular group of people
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that work on that.
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And then people who do like robotics are like,
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well, I don't have to think about that.
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There's other smart people thinking about it.
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It seems that everybody has to think about it.
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It's not, you can't escape the ethics,
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whether it's bias or just every aspect of ethics
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that has to do with human beings.
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So think about, I'm gonna age myself,
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but I remember when we didn't have like testers, right?
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And so what did you do?
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As a developer, you had to test your own code, right?
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Like you had to go through all the cases and figure it out
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and then they realized that,
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we probably need to have testing
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because we're not getting all the things.
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And so from there, what happens is like most developers,
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they do a little bit of testing, but it's usually like,
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okay, did my compiler bug out?
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Let me look at the warnings.
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Okay, is that acceptable or not, right?
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Like that's how you typically think about as a developer
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and you'll just assume that it's going to go
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to another process and they're gonna test it out.
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But I think we need to go back to those early days
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when you're a developer, you're developing,
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there should be like the say,
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okay, let me look at the ethical outcomes of this
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because there isn't a second like testing ethical testers,
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We did it back in the early coding days.
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I think that's where we are with respect to ethics.
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Like let's go back to what was good practices
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and only because we were just developing the field.
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Yeah, and it's a really heavy burden.
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I've had to feel it recently in the last few months,
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but I think it's a good one to feel like
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I've gotten a message, more than one from people.
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You know, I've unfortunately gotten some attention recently
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and I've gotten messages that say that
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I have blood on my hands
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because of working on semi autonomous vehicles.
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So the idea that you have semi autonomy means
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people will become, will lose vigilance and so on.
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That's actually be humans, as we described.
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And because of that, because of this idea
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that we're creating automation,
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there'll be people be hurt because of it.
link |
And I think that's a beautiful thing.
link |
I mean, it's, you know, there's many nights
link |
where I wasn't able to sleep because of this notion.
link |
You know, you really do think about people that might die
link |
because of this technology.
link |
Of course, you can then start rationalizing saying,
link |
well, you know what, 40,000 people die in the United States
link |
every year and we're trying to ultimately try to save lives.
link |
But the reality is your code you've written
link |
might kill somebody.
link |
And that's an important burden to carry with you
link |
as you design the code.
link |
I don't even think of it as a burden
link |
if we train this concept correctly from the beginning.
link |
And I use, and not to say that coding is like
link |
being a medical doctor, but think about it.
link |
Medical doctors, if they've been in situations
link |
where their patient didn't survive, right?
link |
Do they give up and go away?
link |
No, every time they come in,
link |
they know that there might be a possibility
link |
that this patient might not survive.
link |
And so when they approach every decision,
link |
like that's in the back of their head.
link |
And so why isn't that we aren't teaching,
link |
and those are tools though, right?
link |
They are given some of the tools to address that
link |
so that they don't go crazy.
link |
But we don't give those tools
link |
so that it does feel like a burden
link |
versus something of I have a great gift
link |
and I can do great, awesome good,
link |
but with it comes great responsibility.
link |
I mean, that's what we teach in terms of
link |
if you think about the medical schools, right?
link |
Great gift, great responsibility.
link |
I think if we just change the messaging a little,
link |
great gift, being a developer, great responsibility.
link |
And this is how you combine those.
link |
But do you think, I mean, this is really interesting.
link |
It's outside, I actually have no friends
link |
who are sort of surgeons or doctors.
link |
I mean, what does it feel like
link |
to make a mistake in a surgery and somebody to die
link |
Like, is that something you could be taught
link |
in medical school, sort of how to be accepting of that risk?
link |
So, because I do a lot of work with healthcare robotics,
link |
I have not lost a patient, for example.
link |
The first one's always the hardest, right?
link |
But they really teach the value, right?
link |
So, they teach responsibility,
link |
but they also teach the value.
link |
Like, you're saving 40,000,
link |
but in order to really feel good about that,
link |
when you come to a decision,
link |
you have to be able to say at the end,
link |
I did all that I could possibly do, right?
link |
Versus a, well, I just picked the first widget, right?
link |
Like, so every decision is actually thought through.
link |
It's not a habit, it's not a,
link |
let me just take the best algorithm
link |
that my friend gave me, right?
link |
It's a, is this it, is this the best?
link |
Have I done my best to do good, right?
link |
You're right, and I think burden is the wrong word.
link |
It's a gift, but you have to treat it extremely seriously.
link |
So, on a slightly related note,
link |
in a recent paper,
link |
The Ugly Truth About Ourselves and Our Robot Creations,
link |
you discuss, you highlight some biases
link |
that may affect the function of various robotic systems.
link |
Can you talk through, if you remember, examples of some?
link |
There's a lot of examples.
link |
I usually... What is bias, first of all?
link |
Yeah, so bias is this,
link |
and so bias, which is different than prejudice.
link |
So, bias is that we all have these preconceived notions
link |
about particular, everything from particular groups
link |
to habits to identity, right?
link |
So, we have these predispositions,
link |
and so when we address a problem,
link |
we look at a problem and make a decision,
link |
those preconceived notions might affect our outputs,
link |
So, there the bias can be positive and negative,
link |
and then is prejudice the negative kind of bias?
link |
Prejudice is the negative, right?
link |
So, prejudice is that not only are you aware of your bias,
link |
but you are then take it and have a negative outcome,
link |
even though you're aware, like...
link |
And there could be gray areas too.
link |
There's always gray areas.
link |
That's the challenging aspect of all ethical questions.
link |
So, I always like...
link |
So, there's a funny one,
link |
and in fact, I think it might be in the paper,
link |
because I think I talk about self driving cars,
link |
but think about this.
link |
We, for teenagers, right?
link |
Typically, insurance companies charge quite a bit of money
link |
if you have a teenage driver.
link |
So, you could say that's an age bias, right?
link |
But no one will claim...
link |
I mean, parents will be grumpy,
link |
but no one really says that that's not fair.
link |
That's interesting.
link |
That's right, that's right.
link |
It's everybody in human factors and safety research almost...
link |
I mean, it's quite ruthlessly critical of teenagers.
link |
And we don't question, is that okay?
link |
Is that okay to be ageist in this kind of way?
link |
It is, and it is ageist, right?
link |
It's definitely ageist, there's no question about it.
link |
And so, this is the gray area, right?
link |
Because you know that teenagers are more likely
link |
to be in accidents,
link |
and so, there's actually some data to it.
link |
But then, if you take that same example,
link |
and you say, well, I'm going to make the insurance higher
link |
for an area of Boston,
link |
because there's a lot of accidents.
link |
And then, they find out that that's correlated
link |
with socioeconomics.
link |
Well, then it becomes a problem, right?
link |
Like, that is not acceptable,
link |
but yet, the teenager, which is age...
link |
It's against age, is, right?
link |
We figure that out as a society by having conversations,
link |
by having discourse.
link |
I mean, throughout history,
link |
the definition of what is ethical or not has changed,
link |
and hopefully, always for the better.
link |
So, in terms of bias or prejudice in algorithms,
link |
what examples do you sometimes think about?
link |
So, I think about quite a bit the medical domain,
link |
just because historically, right?
link |
The healthcare domain has had these biases,
link |
typically based on gender and ethnicity, primarily.
link |
A little in age, but not so much.
link |
Historically, if you think about FDA and drug trials,
link |
it's harder to find a woman that aren't childbearing,
link |
and so you may not test on drugs at the same level.
link |
Right, so there's these things.
link |
And so, if you think about robotics, right?
link |
Something as simple as,
link |
I'd like to design an exoskeleton, right?
link |
What should the material be?
link |
What should the weight be?
link |
What should the form factor be?
link |
Who are you gonna design it around?
link |
I will say that in the US,
link |
women average height and weight
link |
is slightly different than guys.
link |
So, who are you gonna choose?
link |
Like, if you're not thinking about it from the beginning,
link |
as, okay, when I design this and I look at the algorithms
link |
and I design the control system and the forces
link |
and the torques, if you're not thinking about,
link |
well, you have different types of body structure,
link |
you're gonna design to what you're used to.
link |
Oh, this fits all the folks in my lab, right?
link |
So, think about it from the very beginning is important.
link |
What about sort of algorithms that train on data
link |
Sadly, our society already has a lot of negative bias.
link |
And so, if we collect a lot of data,
link |
even if it's a balanced way,
link |
that's going to contain the same bias
link |
that our society contains.
link |
And so, yeah, is there things there that bother you?
link |
Yeah, so you actually said something.
link |
You had said how we have biases,
link |
but hopefully we learn from them and we become better, right?
link |
And so, that's where we are now, right?
link |
So, the data that we're collecting is historic.
link |
So, it's based on these things
link |
when we knew it was bad to discriminate,
link |
but that's the data we have and we're trying to fix it now,
link |
but we're fixing it based on the data
link |
that was used in the first place.
link |
Right, and so the decisions,
link |
and you can look at everything from the whole aspect
link |
of predictive policing, criminal recidivism.
link |
There was a recent paper that had the healthcare algorithms,
link |
which had a kind of a sensational titles.
link |
I'm not pro sensationalism in titles,
link |
but again, you read it, right?
link |
So, it makes you read it,
link |
but I'm like, really?
link |
Like, ugh, you could have.
link |
What's the topic of the sensationalism?
link |
I mean, what's underneath it?
link |
What's, if you could sort of educate me
link |
on what kind of bias creeps into the healthcare space.
link |
I mean, you already kind of mentioned.
link |
Yeah, so this one was the headline was
link |
racist AI algorithms.
link |
Okay, like, okay, that's totally a clickbait title.
link |
And so you looked at it and so there was data
link |
that these researchers had collected.
link |
I believe, I wanna say it was either Science or Nature.
link |
It just was just published,
link |
but they didn't have a sensational title.
link |
It was like the media.
link |
And so they had looked at demographics,
link |
I believe, between black and white women, right?
link |
And they showed that there was a discrepancy
link |
in the outcomes, right?
link |
And so, and it was tied to ethnicity, tied to race.
link |
The piece that the researchers did
link |
actually went through the whole analysis, but of course.
link |
I mean, the journalists with AI are problematic
link |
across the board, let's say.
link |
And so this is a problem, right?
link |
And so there's this thing about,
link |
oh, AI, it has all these problems.
link |
We're doing it on historical data
link |
and the outcomes are uneven based on gender
link |
or ethnicity or age.
link |
But I am always saying is like, yes,
link |
we need to do better, right?
link |
We need to do better.
link |
It is our duty to do better.
link |
But the worst AI is still better than us.
link |
Like, you take the best of us
link |
and we're still worse than the worst AI,
link |
at least in terms of these things.
link |
And that's actually not discussed, right?
link |
And so I think, and that's why the sensational title, right?
link |
And so it's like, so then you can have individuals go like,
link |
oh, we don't need to use this AI.
link |
I'm like, oh, no, no, no, no.
link |
I want the AI instead of the doctors
link |
that provided that data,
link |
because it's still better than that, right?
link |
I think that's really important to linger on,
link |
is the idea that this AI is racist.
link |
It's like, well, compared to what?
link |
Sort of, I think we set, unfortunately,
link |
way too high of a bar for AI algorithms.
link |
And in the ethical space where perfect is,
link |
I would argue, probably impossible.
link |
Then if we set the bar of perfection, essentially,
link |
of it has to be perfectly fair, whatever that means,
link |
it means we're setting it up for failure.
link |
But that's really important to say what you just said,
link |
which is, well, it's still better than it is.
link |
And one of the things I think
link |
that we don't get enough credit for,
link |
just in terms of as developers,
link |
is that you can now poke at it, right?
link |
So it's harder to say, is this hospital,
link |
is this city doing something, right?
link |
Until someone brings in a civil case, right?
link |
Well, with AI, it can process through all this data
link |
and say, hey, yes, there was an issue here,
link |
but here it is, we've identified it,
link |
and then the next step is to fix it.
link |
I mean, that's a nice feedback loop
link |
versus waiting for someone to sue someone else
link |
before it's fixed, right?
link |
And so I think that power,
link |
we need to capitalize on a little bit more, right?
link |
Instead of having the sensational titles,
link |
have the, okay, this is a problem,
link |
and this is how we're fixing it,
link |
and people are putting money to fix it
link |
because we can make it better.
link |
I look at like facial recognition,
link |
how Joy, she basically called out a couple of companies
link |
and said, hey, and most of them were like,
link |
oh, embarrassment, and the next time it had been fixed,
link |
right, it had been fixed better, right?
link |
And then it was like, oh, here's some more issues.
link |
And I think that conversation then moves that needle
link |
to having much more fair and unbiased and ethical aspects,
link |
as long as both sides, the developers are willing to say,
link |
okay, I hear you, yes, we are going to improve,
link |
and you have other developers who are like,
link |
hey, AI, it's wrong, but I love it, right?
link |
Yes, so speaking of this really nice notion
link |
that AI is maybe flawed but better than humans,
link |
so just made me think of it,
link |
one example of flawed humans is our political system.
link |
Do you think, or you said judicial as well,
link |
do you have a hope for AI sort of being elected
link |
for president or running our Congress
link |
or being able to be a powerful representative of the people?
link |
So I mentioned, and I truly believe that this whole world
link |
of AI is in partnerships with people.
link |
And so what does that mean?
link |
I don't believe, or maybe I just don't,
link |
I don't believe that we should have an AI for president,
link |
but I do believe that a president
link |
should use AI as an advisor, right?
link |
Like, if you think about it,
link |
every president has a cabinet of individuals
link |
that have different expertise
link |
that they should listen to, right?
link |
Like, that's kind of what we do.
link |
And you put smart people with smart expertise
link |
around certain issues, and you listen.
link |
I don't see why AI can't function
link |
as one of those smart individuals giving input.
link |
So maybe there's an AI on healthcare,
link |
maybe there's an AI on education and right,
link |
like all of these things that a human is processing, right?
link |
Because at the end of the day,
link |
there's people that are human
link |
that are going to be at the end of the decision.
link |
And I don't think as a world, as a culture, as a society,
link |
that we would totally, and this is us,
link |
like this is some fallacy about us,
link |
but we need to see that leader, that person as human.
link |
And most people don't realize
link |
that like leaders have a whole lot of advice, right?
link |
Like when they say something, it's not that they woke up,
link |
well, usually they don't wake up in the morning
link |
and be like, I have a brilliant idea, right?
link |
It's usually a, okay, let me listen.
link |
I have a brilliant idea,
link |
but let me get a little bit of feedback on this.
link |
And then it's a, yeah, that was an awesome idea
link |
or it's like, yeah, let me go back.
link |
We already talked through a bunch of them,
link |
but are there some possible solutions
link |
to the bias that's present in our algorithms
link |
beyond what we just talked about?
link |
So I think there's two paths.
link |
One is to figure out how to systematically
link |
do the feedback and corrections.
link |
So right now it's ad hoc, right?
link |
It's a researcher identify some outcomes
link |
that are not, don't seem to be fair, right?
link |
They publish it, they write about it.
link |
And the, either the developer or the companies
link |
that have adopted the algorithms may try to fix it, right?
link |
And so it's really ad hoc and it's not systematic.
link |
There's, it's just, it's kind of like,
link |
I'm a researcher, that seems like an interesting problem,
link |
which means that there's a whole lot out there
link |
that's not being looked at, right?
link |
Cause it's kind of researcher driven.
link |
And I don't necessarily have a solution,
link |
but that process I think could be done a little bit better.
link |
One way is I'm going to poke a little bit
link |
at some of the corporations, right?
link |
Like maybe the corporations when they think
link |
about a product, they should, instead of,
link |
in addition to hiring these, you know, bug,
link |
Oh yeah, yeah, yeah.
link |
Like awards when you find a bug.
link |
Yeah, security bug, you know, let's put it
link |
like we will give the, whatever the award is
link |
that we give for the people who find these security holes,
link |
find an ethics hole, right?
link |
Like find an unfairness hole
link |
and we will pay you X for each one you find.
link |
I mean, why can't they do that?
link |
They show that they're concerned about it,
link |
that this is important and they don't have
link |
to necessarily dedicate it their own like internal resources.
link |
And it also means that everyone who has
link |
like their own bias lens, like I'm interested in age.
link |
And so I'll find the ones based on age
link |
and I'm interested in gender and right,
link |
which means that you get like all
link |
of these different perspectives.
link |
But you think of it in a data driven way.
link |
So like sort of, if we look at a company like Twitter,
link |
it gets, it's under a lot of fire
link |
for discriminating against certain political beliefs.
link |
And sort of, there's a lot of people,
link |
this is the sad thing,
link |
cause I know how hard the problem is
link |
and I know the Twitter folks are working really hard at it.
link |
Even Facebook that everyone seems to hate
link |
are working really hard at this.
link |
You know, the kind of evidence that people bring
link |
is basically anecdotal evidence.
link |
Well, me or my friend, all we said is X
link |
and for that we got banned.
link |
And that's kind of a discussion of saying,
link |
well, look, that's usually, first of all,
link |
the whole thing is taken out of context.
link |
So they present sort of anecdotal evidence.
link |
And how are you supposed to, as a company,
link |
in a healthy way, have a discourse
link |
about what is and isn't ethical?
link |
How do we make algorithms ethical
link |
when people are just blowing everything?
link |
Like they're outraged about a particular
link |
anecdotal piece of evidence that's very difficult
link |
to sort of contextualize in the big data driven way.
link |
Do you have a hope for companies like Twitter and Facebook?
link |
Yeah, so I think there's a couple of things going on, right?
link |
First off, remember this whole aspect
link |
of we are becoming reliant on technology.
link |
We're also becoming reliant on a lot of these,
link |
the apps and the resources that are provided, right?
link |
So some of it is kind of anger, like I need you, right?
link |
And you're not working for me, right?
link |
Not working for me, all right.
link |
But I think, and so some of it,
link |
and I wish that there was a little bit
link |
of change of rethinking.
link |
So some of it is like, oh, we'll fix it in house.
link |
No, that's like, okay, I'm a fox
link |
and I'm going to watch these hens
link |
because I think it's a problem that foxes eat hens.
link |
Like be good citizens and say, look, we have a problem.
link |
And we are willing to open ourselves up
link |
for others to come in and look at it
link |
and not try to fix it in house.
link |
Because if you fix it in house,
link |
there's conflict of interest.
link |
If I find something, I'm probably going to want to fix it
link |
and hopefully the media won't pick it up, right?
link |
And that then causes distrust
link |
because someone inside is going to be mad at you
link |
and go out and talk about how,
link |
yeah, they canned the resume survey because it, right?
link |
Like be nice people.
link |
Like just say, look, we have this issue.
link |
Community, help us fix it.
link |
And we will give you like, you know,
link |
the bug finder fee if you do.
link |
Did you ever hope that the community,
link |
us as a human civilization on the whole is good
link |
and can be trusted to guide the future of our civilization
link |
into a positive direction?
link |
So I'm an optimist, right?
link |
And, you know, there were some dark times in history always.
link |
I think now we're in one of those dark times.
link |
And it's not just US, right?
link |
So if it was just US, I'd be like, yeah, it's a US thing,
link |
but we're seeing it like worldwide, this polarization.
link |
And so I worry about that.
link |
But I do fundamentally believe that at the end of the day,
link |
people are good, right?
link |
And why do I say that?
link |
Because anytime there's a scenario
link |
where people are in danger and I will use,
link |
so Atlanta, we had a snowmageddon
link |
and people can laugh about that.
link |
People at the time, so the city closed for, you know,
link |
little snow, but it was ice and the city closed down.
link |
But you had people opening up their homes and saying,
link |
hey, you have nowhere to go, come to my house, right?
link |
Hotels were just saying like, sleep on the floor.
link |
Like places like, you know, the grocery stores were like,
link |
There was no like, oh, how much are you gonna pay me?
link |
It was like this, such a community.
link |
And like people who didn't know each other,
link |
strangers were just like, can I give you a ride home?
link |
And that was a point I was like, you know what, like.
link |
That reveals that the deeper thing is,
link |
there's a compassionate love that we all have within us.
link |
It's just that when all of that is taken care of
link |
and get bored, we love drama.
link |
And that's, I think almost like the division
link |
is a sign of the times being good,
link |
is that it's just entertaining
link |
on some unpleasant mammalian level to watch,
link |
to disagree with others.
link |
And Twitter and Facebook are actually taking advantage
link |
of that in a sense because it brings you back
link |
to the platform and they're advertiser driven,
link |
so they make a lot of money.
link |
So you go back and you click.
link |
Love doesn't sell quite as well in terms of advertisement.
link |
So you've started your career
link |
at NASA Jet Propulsion Laboratory,
link |
but before I ask a few questions there,
link |
have you happened to have ever seen Space Odyssey,
link |
2001 Space Odyssey?
link |
Okay, do you think HAL 9000,
link |
so we're talking about ethics.
link |
Do you think HAL did the right thing
link |
by taking the priority of the mission
link |
over the lives of the astronauts?
link |
Do you think HAL is good or evil?
link |
HAL was misguided.
link |
You're one of the people that would be in charge
link |
of an algorithm like HAL.
link |
What would you do better?
link |
If you think about what happened
link |
was there was no fail safe, right?
link |
So perfection, right?
link |
Like what is that?
link |
I'm gonna make something that I think is perfect,
link |
but if my assumptions are wrong,
link |
it'll be perfect based on the wrong assumptions, right?
link |
That's something that you don't know until you deploy
link |
and then you're like, oh yeah, messed up.
link |
But what that means is that when we design software,
link |
such as in Space Odyssey,
link |
when we put things out,
link |
that there has to be a fail safe.
link |
There has to be the ability that once it's out there,
link |
we can grade it as an F and it fails
link |
and it doesn't continue, right?
link |
There's some way that it can be brought in
link |
and removed in that aspect.
link |
Because that's what happened with HAL.
link |
It was like assumptions were wrong.
link |
It was perfectly correct based on those assumptions
link |
and there was no way to change it,
link |
change the assumptions at all.
link |
And the change to fall back would be to a human.
link |
So you ultimately think like human should be,
link |
it's not turtles or AI all the way down.
link |
It's at some point, there's a human that actually.
link |
I still think that,
link |
and again, because I do human robot interaction,
link |
I still think the human needs to be part of the equation
link |
So what, just looking back,
link |
what are some fascinating things in robotic space
link |
that NASA was working at the time?
link |
Or just in general, what have you gotten to play with
link |
and what are your memories from working at NASA?
link |
Yeah, so one of my first memories
link |
was they were working on a surgical robot system
link |
that could do eye surgery, right?
link |
And this was back in, oh my gosh, it must've been,
link |
oh, maybe 92, 93, 94.
link |
So it's like almost like a remote operation.
link |
Yeah, it was remote operation.
link |
In fact, you can even find some old tech reports on it.
link |
So think of it, like now we have DaVinci, right?
link |
Like think of it, but these were like the late 90s, right?
link |
And I remember going into the lab one day
link |
and I was like, what's that, right?
link |
And of course it wasn't pretty, right?
link |
Because the technology, but it was like functional
link |
and you had this individual that could use
link |
a version of haptics to actually do the surgery
link |
and they had this mockup of a human face
link |
and like the eyeballs and you can see this little drill.
link |
And I was like, oh, that is so cool.
link |
That one I vividly remember
link |
because it was so outside of my like possible thoughts
link |
of what could be done.
link |
It's the kind of precision
link |
and I mean, what's the most amazing of a thing like that?
link |
I think it was the precision.
link |
It was the kind of first time
link |
that I had physically seen
link |
this robot machine human interface, right?
link |
Versus, cause manufacturing had been,
link |
you saw those kind of big robots, right?
link |
But this was like, oh, this is in a person.
link |
There's a person and a robot like in the same space.
link |
I'm meeting them in person.
link |
Like for me, it was a magical moment
link |
that I can't, it was life transforming
link |
that I recently met Spot Mini from Boston Dynamics.
link |
I don't know why, but on the human robot interaction
link |
for some reason I realized how easy it is to anthropomorphize
link |
and it was, I don't know, it was almost
link |
like falling in love, this feeling of meeting.
link |
And I've obviously seen these robots a lot
link |
on video and so on, but meeting in person,
link |
just having that one on one time is different.
link |
So have you had a robot like that in your life
link |
that made you maybe fall in love with robotics?
link |
Sort of like meeting in person.
link |
I mean, I loved robotics since, yeah.
link |
So I was a 12 year old.
link |
Like I'm gonna be a roboticist, actually was,
link |
I called it cybernetics.
link |
But so my motivation was Bionic Woman.
link |
I don't know if you know that.
link |
And so, I mean, that was like a seminal moment,
link |
but I didn't meet, like that was TV, right?
link |
Like it wasn't like I was in the same space and I met
link |
and I was like, oh my gosh, you're like real.
link |
Just linking on Bionic Woman, which by the way,
link |
because I read that about you.
link |
I watched bits of it and it's just so,
link |
no offense, terrible.
link |
It's cheesy if you look at it now.
link |
I've seen a couple of reruns lately.
link |
But it's, but of course at the time it's probably
link |
captured the imagination.
link |
But the sound effects.
link |
Especially when you're younger, it just catch you.
link |
But which aspect, did you think of it,
link |
you mentioned cybernetics, did you think of it as robotics
link |
or did you think of it as almost constructing
link |
artificial beings?
link |
Like, is it the intelligent part that captured
link |
your fascination or was it the whole thing?
link |
Like even just the limbs and just the.
link |
So for me, it would have, in another world,
link |
I probably would have been more of a biomedical engineer
link |
because what fascinated me was the parts,
link |
like the bionic parts, the limbs, those aspects of it.
link |
Are you especially drawn to humanoid or humanlike robots?
link |
I would say humanlike, not humanoid, right?
link |
And when I say humanlike, I think it's this aspect
link |
of that interaction, whether it's social
link |
and it's like a dog, right?
link |
Like that's humanlike because it understand us,
link |
it interacts with us at that very social level
link |
to, you know, humanoids are part of that,
link |
but only if they interact with us as if we are human.
link |
Okay, but just to linger on NASA for a little bit,
link |
what do you think, maybe if you have other memories,
link |
but also what do you think is the future of robots in space?
link |
We'll mention how, but there's incredible robots
link |
that NASA's working on in general thinking about
link |
in our, as we venture out, human civilization ventures out
link |
into space, what do you think the future of robots is there?
link |
Yeah, so I mean, there's the near term.
link |
For example, they just announced the rover
link |
that's going to the moon, which, you know,
link |
that's kind of exciting, but that's like near term.
link |
You know, my favorite, favorite, favorite series
link |
is Star Trek, right?
link |
You know, I really hope, and even Star Trek,
link |
like if I calculate the years, I wouldn't be alive,
link |
but I would really, really love to be in that world.
link |
Like, even if it's just at the beginning,
link |
like, you know, like voyage, like adventure one.
link |
So basically living in space.
link |
With, what robots, what are robots?
link |
The data would have to be, even though that wasn't,
link |
you know, that was like later, but.
link |
So data is a robot that has human like qualities.
link |
Right, without the emotion chip.
link |
You don't like emotion.
link |
Well, so data with the emotion chip
link |
was kind of a mess, right?
link |
It took a while for that thing to adapt,
link |
but, and so why was that an issue?
link |
The issue is that emotions make us irrational agents.
link |
That's the problem.
link |
And yet he could think through things,
link |
even if it was based on an emotional scenario, right?
link |
Based on pros and cons.
link |
But as soon as you made him emotional,
link |
one of the metrics he used for evaluation
link |
was his own emotions, not people around him, right?
link |
We do that as children, right?
link |
So we're very egocentric when we're young.
link |
We are very egocentric.
link |
And so isn't that just an early version of the emotion chip
link |
then, I haven't watched much Star Trek.
link |
Except I have also met adults, right?
link |
And so that is a developmental process.
link |
And I'm sure there's a bunch of psychologists
link |
that can go through, like you can have a 60 year old adult
link |
who has the emotional maturity of a 10 year old, right?
link |
And so there's various phases that people should go through
link |
in order to evolve and sometimes you don't.
link |
So how much psychology do you think,
link |
a topic that's rarely mentioned in robotics,
link |
but how much does psychology come to play
link |
when you're talking about HRI, human robot interaction?
link |
When you have to have robots
link |
that actually interact with humans.
link |
So we, like my group, as well as I read a lot
link |
in the cognitive science literature,
link |
as well as the psychology literature.
link |
Because they understand a lot about human, human relations
link |
and developmental milestones and things like that.
link |
And so we tend to look to see what's been done out there.
link |
Sometimes what we'll do is we'll try to match that to see,
link |
is that human, human relationship the same as human robot?
link |
Sometimes it is, and sometimes it's different.
link |
And then when it's different, we have to,
link |
we try to figure out, okay,
link |
why is it different in this scenario?
link |
But it's the same in the other scenario, right?
link |
And so we try to do that quite a bit.
link |
Would you say that's, if we're looking at the future
link |
of human robot interaction,
link |
would you say the psychology piece is the hardest?
link |
Like if, I mean, it's a funny notion for you as,
link |
I don't know if you consider, yeah.
link |
I mean, one way to ask it,
link |
do you consider yourself a roboticist or a psychologist?
link |
Oh, I consider myself a roboticist
link |
that plays the act of a psychologist.
link |
But if you were to look at yourself sort of,
link |
20, 30 years from now,
link |
do you see yourself more and more
link |
wearing the psychology hat?
link |
Another way to put it is,
link |
are the hard problems in human robot interactions
link |
fundamentally psychology, or is it still robotics,
link |
the perception manipulation, planning,
link |
all that kind of stuff?
link |
It's actually neither.
link |
The hardest part is the adaptation and the interaction.
link |
So it's the interface, it's the learning.
link |
And so if I think of,
link |
like I've become much more of a roboticist slash AI person
link |
than when I, like originally, again,
link |
I was about the bionics.
link |
I was electrical engineer, I was control theory, right?
link |
And then I started realizing that my algorithms
link |
needed like human data, right?
link |
And so then I was like, okay, what is this human thing?
link |
How do I incorporate human data?
link |
And then I realized that human perception had,
link |
like there was a lot in terms of how we perceive the world.
link |
And so trying to figure out
link |
how do I model human perception for my,
link |
and so I became a HRI person,
link |
human robot interaction person,
link |
from being a control theory and realizing
link |
that humans actually offered quite a bit.
link |
And then when you do that,
link |
you become more of an artificial intelligence, AI.
link |
And so I see myself evolving more in this AI world
link |
under the lens of robotics,
link |
having hardware, interacting with people.
link |
So you're a world class expert researcher in robotics,
link |
and yet others, you know, there's a few,
link |
it's a small but fierce community of people,
link |
but most of them don't take the journey
link |
into the H of HRI, into the human.
link |
So why did you brave into the interaction with humans?
link |
It seems like a really hard problem.
link |
It's a hard problem, and it's very risky as an academic.
link |
And I knew that when I started down that journey,
link |
that it was very risky as an academic
link |
in this world that was nuance, it was just developing.
link |
We didn't even have a conference, right, at the time.
link |
Because it was the interesting problems.
link |
That was what drove me.
link |
It was the fact that I looked at what interests me
link |
in terms of the application space and the problems.
link |
And that pushed me into trying to figure out
link |
what people were and what humans were
link |
and how to adapt to them.
link |
If those problems weren't so interesting,
link |
I'd probably still be sending rovers to glaciers, right?
link |
But the problems were interesting.
link |
And the other thing was that they were hard, right?
link |
So it's, I like having to go into a room
link |
and being like, I don't know what to do.
link |
And then going back and saying, okay,
link |
I'm gonna figure this out.
link |
I do not, I'm not driven when I go in like,
link |
oh, there are no surprises.
link |
Like, I don't find that satisfying.
link |
If that was the case,
link |
I'd go someplace and make a lot more money, right?
link |
I think I stay in academic because and choose to do this
link |
because I can go into a room and like, that's hard.
link |
Yeah, I think just from my perspective,
link |
maybe you can correct me on it,
link |
but if I just look at the field of AI broadly,
link |
it seems that human robot interaction has the most,
link |
one of the most number of open problems.
link |
Like people, especially relative to how many people
link |
are willing to acknowledge that there are this,
link |
because most people are just afraid of the humans
link |
so they don't even acknowledge
link |
how many open problems there are.
link |
But it's in terms of difficult problems
link |
to solve exciting spaces,
link |
it seems to be incredible for that.
link |
It is, and it's exciting.
link |
You've mentioned trust before.
link |
What role does trust from interacting with autopilot
link |
to in the medical context,
link |
what role does trust play in the human robot interactions?
link |
So some of the things I study in this domain
link |
is not just trust, but it really is over trust.
link |
How do you think about over trust?
link |
Like what is, first of all, what is trust
link |
and what is over trust?
link |
Basically, the way I look at it is,
link |
trust is not what you click on a survey,
link |
trust is about your behavior.
link |
So if you interact with the technology
link |
based on the decision or the actions of the technology
link |
as if you trust that decision, then you're trusting.
link |
And even in my group, we've done surveys
link |
that on the thing, do you trust robots?
link |
Would you follow this robot in a burdening building?
link |
And then you look at their actions and you're like,
link |
clearly your behavior does not match what you think
link |
or what you think you would like to think.
link |
And so I'm really concerned about the behavior
link |
because that's really at the end of the day,
link |
when you're in the world,
link |
that's what will impact others around you.
link |
It's not whether before you went onto the street,
link |
you clicked on like, I don't trust self driving cars.
link |
Yeah, that from an outsider perspective,
link |
it's always frustrating to me.
link |
Well, I read a lot, so I'm insider
link |
in a certain philosophical sense.
link |
It's frustrating to me how often trust is used in surveys
link |
and how people say, make claims out of any kind of finding
link |
they make while somebody clicking on answer.
link |
You just trust is a, yeah, behavior just,
link |
you said it beautifully.
link |
I mean, the action, your own behavior is what trust is.
link |
I mean, that everything else is not even close.
link |
It's almost like absurd comedic poetry
link |
that you weave around your actual behavior.
link |
So some people can say their trust,
link |
you know, I trust my wife, husband or not,
link |
whatever, but the actions is what speaks volumes.
link |
You bug their car, you probably don't trust them.
link |
I trust them, I'm just making sure.
link |
No, no, that's, yeah.
link |
Like even if you think about cars,
link |
I think it's a beautiful case.
link |
I came here at some point, I'm sure,
link |
on either Uber or Lyft, right?
link |
I remember when it first came out, right?
link |
I bet if they had had a survey,
link |
would you get in the car with a stranger and pay them?
link |
How many people do you think would have said,
link |
Wait, even worse, would you get in the car
link |
with a stranger at 1 a.m. in the morning
link |
to have them drop you home as a single female?
link |
Like how many people would say, that's stupid.
link |
And now look at where we are.
link |
I mean, people put kids, right?
link |
Like, oh yeah, my child has to go to school
link |
and yeah, I'm gonna put my kid in this car with a stranger.
link |
I mean, it's just fascinating how, like,
link |
what we think we think is not necessarily
link |
matching our behavior.
link |
Yeah, and certainly with robots, with autonomous vehicles
link |
and all the kinds of robots you work with,
link |
that's, it's, yeah, it's, the way you answer it,
link |
especially if you've never interacted with that robot before,
link |
if you haven't had the experience,
link |
you being able to respond correctly on a survey is impossible.
link |
But what do you, what role does trust play
link |
in the interaction, do you think?
link |
Like, is it good to, is it good to trust a robot?
link |
What does over trust mean?
link |
Or is it, is it good to kind of how you feel
link |
about autopilot currently, which is like,
link |
from a roboticist's perspective, is like,
link |
oh, still very cautious?
link |
Yeah, so this is still an open area of research,
link |
but basically what I would like in a perfect world
link |
is that people trust the technology when it's working 100%,
link |
and people will be hypersensitive
link |
and identify when it's not.
link |
But of course we're not there.
link |
That's the ideal world.
link |
And, but we find is that people swing, right?
link |
They tend to swing, which means that if my first,
link |
and like, we have some papers,
link |
like first impressions is everything, right?
link |
If my first instance with technology,
link |
with robotics is positive, it mitigates any risk,
link |
it correlates with like best outcomes,
link |
it means that I'm more likely to either not see it
link |
when it makes some mistakes or faults,
link |
or I'm more likely to forgive it.
link |
And so this is a problem
link |
because technology is not 100% accurate, right?
link |
It's not 100% accurate, although it may be perfect.
link |
How do you get that first moment right, do you think?
link |
There's also an education about the capabilities
link |
and limitations of the system.
link |
Do you have a sense of how do you educate people correctly
link |
in that first interaction?
link |
Again, this is an open ended problem.
link |
So one of the study that actually has given me some hope
link |
that I were trying to figure out how to put in robotics.
link |
So there was a research study
link |
that it showed for medical AI systems,
link |
giving information to radiologists about,
link |
here you need to look at these areas on the X ray.
link |
What they found was that when the system provided
link |
one choice, there was this aspect of either no trust
link |
or over trust, right?
link |
Like I don't believe it at all,
link |
or a yes, yes, yes, yes.
link |
And they would miss things, right?
link |
Instead, when the system gave them multiple choices,
link |
like here are the three, even if it knew like,
link |
it had estimated that the top area you need to look at
link |
was some place on the X ray.
link |
If it gave like one plus others,
link |
the trust was maintained and the accuracy of the entire
link |
population increased, right?
link |
So basically it was a, you're still trusting the system,
link |
but you're also putting in a little bit of like,
link |
your human expertise, like your human decision processing
link |
into the equation.
link |
So it helps to mitigate that over trust risk.
link |
Yeah, so there's a fascinating balance that the strike.
link |
Haven't figured out again, robotics is still an open research.
link |
This is exciting open area research, exactly.
link |
So what are some exciting applications
link |
of human robot interaction?
link |
You started a company, maybe you can talk about
link |
the exciting efforts there, but in general also
link |
what other space can robots interact with humans and help?
link |
Yeah, so besides healthcare,
link |
cause you know, that's my bias lens.
link |
My other bias lens is education.
link |
I think that, well, one, we definitely,
link |
we in the US, you know, we're doing okay with teachers,
link |
but there's a lot of school districts
link |
that don't have enough teachers.
link |
If you think about the teacher student ratio
link |
for at least public education in some districts, it's crazy.
link |
It's like, how can you have learning in that classroom,
link |
Because you just don't have the human capital.
link |
And so if you think about robotics,
link |
bringing that in to classrooms,
link |
as well as the afterschool space,
link |
where they offset some of this lack of resources
link |
in certain communities, I think that's a good place.
link |
And then turning on the other end
link |
is using these systems then for workforce retraining
link |
and dealing with some of the things
link |
that are going to come out later on of job loss,
link |
like thinking about robots and in AI systems
link |
for retraining and workforce development.
link |
I think that's exciting areas that can be pushed even more,
link |
and it would have a huge, huge impact.
link |
What would you say are some of the open problems
link |
in education, sort of, it's exciting.
link |
So young kids and the older folks
link |
or just folks of all ages who need to be retrained,
link |
who need to sort of open themselves up
link |
to a whole nother area of work.
link |
What are the problems to be solved there?
link |
How do you think robots can help?
link |
We have the engagement aspect, right?
link |
So we can figure out the engagement.
link |
What do you mean by engagement?
link |
So identifying whether a person is focused,
link |
is like that we can figure out.
link |
What we can figure out and there's some positive results
link |
in this is that personalized adaptation
link |
based on any concepts, right?
link |
So imagine I think about, I have an agent
link |
and I'm working with a kid learning, I don't know,
link |
algebra two, can that same agent then switch
link |
and teach some type of new coding skill
link |
to a displaced mechanic?
link |
Like, what does that actually look like, right?
link |
Like hardware might be the same, content is different,
link |
two different target demographics of engagement.
link |
Like how do you do that?
link |
How important do you think personalization
link |
is in human robot interaction?
link |
And not just a mechanic or student,
link |
but like literally to the individual human being.
link |
I think personalization is really important,
link |
but a caveat is that I think we'd be okay
link |
if we can personalize to the group, right?
link |
And so if I can label you
link |
as along some certain dimensions,
link |
then even though it may not be you specifically,
link |
I can put you in this group.
link |
So the sample size, this is how they best learn,
link |
this is how they best engage.
link |
Even at that level, it's really important.
link |
And it's because, I mean, it's one of the reasons
link |
why educating in large classrooms is so hard, right?
link |
You teach to the median,
link |
but there's these individuals that are struggling
link |
and then you have highly intelligent individuals
link |
and those are the ones that are usually kind of left out.
link |
So highly intelligent individuals may be disruptive
link |
and those who are struggling might be disruptive
link |
because they're both bored.
link |
Yeah, and if you narrow the definition of the group
link |
or in the size of the group enough,
link |
you'll be able to address their individual,
link |
it's not individual needs, but really the most important
link |
group needs, right?
link |
And that's kind of what a lot of successful
link |
recommender systems do with Spotify and so on.
link |
So it's sad to believe, but as a music listener,
link |
probably in some sort of large group,
link |
it's very sadly predictable.
link |
You have been labeled.
link |
Yeah, I've been labeled and successfully so
link |
because they're able to recommend stuff that I like.
link |
Yeah, but applying that to education, right?
link |
There's no reason why it can't be done.
link |
Do you have a hope for our education system?
link |
I have more hope for workforce development.
link |
And that's because I'm seeing investments.
link |
Even if you look at VC investments in education,
link |
the majority of it has lately been going
link |
to workforce retraining, right?
link |
And so I think that government investments is increasing.
link |
There's like a claim and some of it's based on fear, right?
link |
Like AI is gonna come and take over all these jobs.
link |
What are we gonna do with all these nonpaying taxes
link |
that aren't coming to us by our citizens?
link |
And so I think I'm more hopeful for that.
link |
Not so hopeful for early education
link |
because it's still a who's gonna pay for it.
link |
And you won't see the results for like 16 to 18 years.
link |
It's hard for people to wrap their heads around that.
link |
But on the retraining part, what are your thoughts?
link |
There's a candidate, Andrew Yang running for president
link |
and saying that sort of AI, automation, robots.
link |
Universal basic income.
link |
Universal basic income in order to support us
link |
as we kind of automation takes people's jobs
link |
and allows you to explore and find other means.
link |
Like do you have a concern of society
link |
transforming effects of automation and robots and so on?
link |
I do know that AI robotics will displace workers.
link |
Like we do know that.
link |
But there'll be other workers
link |
that will be defined new jobs.
link |
What I worry about is, that's not what I worry about.
link |
Like will all the jobs go away?
link |
What I worry about is the type of jobs that will come out.
link |
Like people who graduate from Georgia Tech will be okay.
link |
We give them the skills,
link |
they will adapt even if their current job goes away.
link |
I do worry about those
link |
that don't have that quality of an education.
link |
Will they have the ability,
link |
the background to adapt to those new jobs?
link |
That I don't know.
link |
That I worry about,
link |
which will create even more polarization
link |
in our society, internationally and everywhere.
link |
I worry about that.
link |
I also worry about not having equal access
link |
to all these wonderful things that AI can do
link |
and robotics can do.
link |
I worry about that.
link |
People like me from Georgia Tech from say MIT
link |
will be okay, right?
link |
But that's such a small part of the population
link |
that we need to think much more globally
link |
of having access to the beautiful things,
link |
whether it's AI in healthcare, AI in education,
link |
AI in politics, right?
link |
I worry about that.
link |
And that's part of the thing that you were talking about
link |
is people that build the technology
link |
have to be thinking about ethics,
link |
have to be thinking about access and all those things.
link |
And not just a small subset.
link |
Let me ask some philosophical,
link |
slightly romantic questions.
link |
People that listen to this will be like,
link |
here he goes again.
link |
Okay, do you think one day we'll build an AI system
link |
that a person can fall in love with
link |
and it would love them back?
link |
Like in the movie, Her, for example.
link |
Yeah, although she kind of didn't fall in love with him
link |
or she fell in love with like a million other people,
link |
something like that.
link |
You're the jealous type, I see.
link |
We humans are the jealous type.
link |
Yes, so I do believe that we can design systems
link |
where people would fall in love with their robot,
link |
with their AI partner.
link |
That I do believe.
link |
Because it's actually,
link |
and I don't like to use the word manipulate,
link |
but as we see, there are certain individuals
link |
that can be manipulated
link |
if you understand the cognitive science about it, right?
link |
Right, so I mean, if you could think of all close
link |
relationship and love in general
link |
as a kind of mutual manipulation,
link |
that dance, the human dance.
link |
I mean, manipulation is a negative connotation.
link |
And that's why I don't like to use that word particularly.
link |
I guess another way to phrase it is,
link |
you're getting at is it could be algorithmatized
link |
or something, it could be a.
link |
The relationship building part can be.
link |
I mean, just think about it.
link |
We have, and I don't use dating sites,
link |
but from what I heard, there are some individuals
link |
that have been dating that have never saw each other, right?
link |
In fact, there's a show I think
link |
that tries to like weed out fake people.
link |
Like there's a show that comes out, right?
link |
Because like people start faking.
link |
Like, what's the difference of that person
link |
on the other end being an AI agent, right?
link |
And having a communication
link |
and you building a relationship remotely,
link |
like there's no reason why that can't happen.
link |
In terms of human robot interaction,
link |
so what role, you've kind of mentioned
link |
with data emotion being, can be problematic
link |
if not implemented well, I suppose.
link |
What role does emotion and some other human like things,
link |
the imperfect things come into play here
link |
for good human robot interaction and something like love?
link |
Yeah, so in this case, and you had asked,
link |
can an AI agent love a human back?
link |
I think they can emulate love back, right?
link |
And so what does that actually mean?
link |
It just means that if you think about their programming,
link |
they might put the other person's needs
link |
in front of theirs in certain situations, right?
link |
You look at, think about it as a return on investment.
link |
Like, what's my return on investment?
link |
As part of that equation, that person's happiness,
link |
has some type of algorithm waiting to it.
link |
And the reason why is because I care about them, right?
link |
That's the only reason, right?
link |
But if I care about them and I show that,
link |
then my final objective function
link |
is length of time of the engagement, right?
link |
So you can think of how to do this actually quite easily.
link |
But that's not love?
link |
Well, so that's the thing.
link |
I think it emulates love
link |
because we don't have a classical definition of love.
link |
Right, but, and we don't have the ability
link |
to look into each other's minds to see the algorithm.
link |
And I mean, I guess what I'm getting at is,
link |
is it possible that, especially if that's learned,
link |
especially if there's some mystery
link |
and black box nature to the system,
link |
how is that, you know?
link |
How is it any different?
link |
How is it any different in terms of sort of
link |
if the system says, I'm conscious, I'm afraid of death,
link |
and it does indicate that it loves you.
link |
Another way to sort of phrase it,
link |
be curious to see what you think.
link |
Do you think there'll be a time
link |
when robots should have rights?
link |
You've kind of phrased the robot in a very roboticist way
link |
and just a really good way, but saying, okay,
link |
well, there's an objective function
link |
and I could see how you can create
link |
a compelling human robot interaction experience
link |
that makes you believe that the robot cares for your needs
link |
and even something like loves you.
link |
But what if the robot says, please don't turn me off?
link |
What if the robot starts making you feel
link |
like there's an entity, a being, a soul there, right?
link |
Do you think there'll be a future,
link |
hopefully you won't laugh too much at this,
link |
but where they do ask for rights?
link |
So I can see a future
link |
if we don't address it in the near term
link |
where these agents, as they adapt and learn,
link |
could say, hey, this should be something that's fundamental.
link |
I hopefully think that we would address it
link |
before it gets to that point.
link |
So you think that's a bad future?
link |
Is that a negative thing where they ask
link |
we're being discriminated against?
link |
I guess it depends on what role
link |
have they attained at that point, right?
link |
And so if I think about now.
link |
Careful what you say because the robots 50 years from now
link |
I'll be listening to this and you'll be on TV saying,
link |
this is what roboticists used to believe.
link |
And so this is my, and as I said, I have a bias lens
link |
and my robot friends will understand that.
link |
So if you think about it, and I actually put this
link |
in kind of the, as a roboticist,
link |
you don't necessarily think of robots as human
link |
with human rights, but you could think of them
link |
either in the category of property,
link |
or you can think of them in the category of animals, right?
link |
And so both of those have different types of rights.
link |
So animals have their own rights as a living being,
link |
but they can't vote, they can't write,
link |
they can be euthanized, but as humans,
link |
if we abuse them, we go to jail, right?
link |
So they do have some rights that protect them,
link |
but don't give them the rights of like citizenship.
link |
And then if you think about property,
link |
property, the rights are associated with the person, right?
link |
So if someone vandalizes your property
link |
or steals your property, like there are some rights,
link |
but it's associated with the person who owns that.
link |
If you think about it back in the day,
link |
and if you remember, we talked about
link |
how society has changed, women were property, right?
link |
They were not thought of as having rights.
link |
They were thought of as property of, like their...
link |
Yeah, assaulting a woman meant
link |
assaulting the property of somebody else.
link |
Exactly, and so what I envision is,
link |
is that we will establish some type of norm at some point,
link |
but that it might evolve, right?
link |
Like if you look at women's rights now,
link |
like there are still some countries that don't have,
link |
and the rest of the world is like,
link |
why that makes no sense, right?
link |
And so I do see a world where we do establish
link |
some type of grounding.
link |
It might be based on property rights,
link |
it might be based on animal rights.
link |
And if it evolves that way,
link |
I think we will have this conversation at that time,
link |
because that's the way our society traditionally has evolved.
link |
Beautifully put, just out of curiosity,
link |
Anki, Jibo, Mayflower Robotics,
link |
with their robot Curie, SciFiWorks, WeThink Robotics,
link |
were all these amazing robotics companies
link |
led, created by incredible roboticists,
link |
and they've all went out of business recently.
link |
Why do you think they didn't last long?
link |
Why is it so hard to run a robotics company,
link |
especially one like these, which are fundamentally
link |
HRI human robot interaction robots?
link |
Or personal robots?
link |
Each one has a story,
link |
only one of them I don't understand, and that was Anki.
link |
That's actually the only one I don't understand.
link |
I don't understand it either.
link |
No, no, I mean, I look like from the outside,
link |
I've looked at their sheets, I've looked at the data that's.
link |
Oh, you mean like business wise,
link |
you don't understand, I got you.
link |
Yeah, and like I look at all, I look at that data,
link |
and I'm like, they seem to have like product market fit.
link |
Like, so that's the only one I don't understand.
link |
The rest of it was product market fit.
link |
What's product market fit?
link |
Just that of, like how do you think about it?
link |
Yeah, so although WeThink Robotics was getting there, right?
link |
But I think it's just the timing,
link |
it just, their clock just timed out.
link |
I think if they'd been given a couple more years,
link |
they would have been okay.
link |
But the other ones were still fairly early
link |
by the time they got into the market.
link |
And so product market fit is,
link |
I have a product that I wanna sell at a certain price.
link |
Are there enough people out there, the market,
link |
that are willing to buy the product at that market price
link |
for me to be a functional viable profit bearing company?
link |
So product market fit.
link |
If it costs you a thousand dollars
link |
and everyone wants it and only is willing to pay a dollar,
link |
you have no product market fit.
link |
Even if you could sell it for, you know,
link |
it's enough for a dollar, cause you can't.
link |
So how hard is it for robots?
link |
Sort of maybe if you look at iRobot,
link |
the company that makes Roombas, vacuum cleaners,
link |
can you comment on, did they find the right product,
link |
market product fit?
link |
Like, are people willing to pay for robots
link |
is also another kind of question underlying all this.
link |
So if you think about iRobot and their story, right?
link |
Like when they first, they had enough of a runway, right?
link |
When they first started,
link |
they weren't doing vacuum cleaners, right?
link |
They were contracts primarily, government contracts,
link |
Or military robots.
link |
Yeah, I mean, that's what they were.
link |
That's how they started, right?
link |
They still do a lot of incredible work there.
link |
But yeah, that was the initial thing
link |
that gave them enough funding to.
link |
To then try to, the vacuum cleaner is what I've been told
link |
was not like their first rendezvous
link |
in terms of designing a product, right?
link |
And so they were able to survive
link |
until they got to the point
link |
that they found a product price market, right?
link |
And even with, if you look at the Roomba,
link |
the price point now is different
link |
than when it was first released, right?
link |
It was an early adopter price,
link |
but they found enough people
link |
who were willing to fund it.
link |
And I mean, I forgot what their loss profile was
link |
for the first couple of years,
link |
but they became profitable in sufficient time
link |
that they didn't have to close their doors.
link |
So they found the right,
link |
there's still people willing to pay
link |
a large amount of money,
link |
so over $1,000 for a vacuum cleaner.
link |
Unfortunately for them,
link |
now that they've proved everything out,
link |
figured it all out,
link |
now there's competitors.
link |
Yeah, and so that's the next thing, right?
link |
and they have quite a number, even internationally.
link |
Like there's some products out there,
link |
you can go to Europe and be like,
link |
oh, I didn't even know this one existed.
link |
So this is the thing though,
link |
like with any market,
link |
I would, this is not a bad time,
link |
although as a roboticist, it's kind of depressing,
link |
but I actually think about things like with,
link |
I would say that all of the companies
link |
that are now in the top five or six,
link |
they weren't the first to the stage, right?
link |
Like Google was not the first search engine,
link |
sorry, Altavista, right?
link |
Facebook was not the first, sorry, MySpace, right?
link |
Like think about it,
link |
they were not the first players.
link |
Those first players,
link |
like they're not in the top five, 10 of Fortune 500 companies,
link |
They proved, they started to prove out the market,
link |
they started to get people interested,
link |
they started the buzz,
link |
but they didn't make it to that next level.
link |
But the second batch, right?
link |
The second batch, I think might make it to the next level.
link |
When do you think the Facebook of robotics?
link |
The Facebook of robotics.
link |
Sorry, I take that phrase back because people deeply,
link |
for some reason, well, I know why,
link |
but it's, I think, exaggerated distrust Facebook
link |
because of the privacy concerns and so on.
link |
And with robotics, one of the things you have to make sure
link |
is all the things we talked about is to be transparent
link |
and have people deeply trust you
link |
to let a robot into their lives, into their home.
link |
When do you think the second batch of robots will come?
link |
Is it five, 10 years, 20 years
link |
that we'll have robots in our homes
link |
and robots in our hearts?
link |
So if I think about, and because I try to follow
link |
the VC kind of space in terms of robotic investments,
link |
and right now, and I don't know
link |
if they're gonna be successful,
link |
I don't know if this is the second batch,
link |
but there's only one batch that's focused
link |
on like the first batch, right?
link |
And then there's all these self driving Xs, right?
link |
And so I don't know if they're a first batch of something
link |
or if like, I don't know quite where they fit in,
link |
but there's a number of companies,
link |
the co robot, I call them co robots
link |
that are still getting VC investments.
link |
Some of them have some of the flavor
link |
of like Rethink Robotics.
link |
Some of them have some of the flavor of like Curie.
link |
What's a co robot?
link |
So basically a robot and human working in the same space.
link |
So some of the companies are focused on manufacturing.
link |
So having a robot and human working together
link |
in a factory, some of these co robots
link |
are robots and humans working in the home,
link |
working in clinics, like there's different versions
link |
of these companies in terms of their products,
link |
but they're all, so we think robotics would be
link |
like one of the first, at least well known companies
link |
focused on this space.
link |
So I don't know if this is a second batch
link |
or if this is still part of the first batch,
link |
that I don't know.
link |
And then you have all these other companies
link |
in this self driving space.
link |
And I don't know if that's a first batch
link |
or again, a second batch.
link |
So there's a lot of mystery about this now.
link |
Of course, it's hard to say that this is the second batch
link |
until it proves out, right?
link |
Yeah, we need a unicorn.
link |
Why do you think people are so afraid,
link |
at least in popular culture of legged robots
link |
like those worked in Boston Dynamics
link |
or just robotics in general,
link |
if you were to psychoanalyze that fear,
link |
what do you make of it?
link |
And should they be afraid, sorry?
link |
So should people be afraid?
link |
I don't think people should be afraid.
link |
But with a caveat, I don't think people should be afraid
link |
given that most of us in this world
link |
understand that we need to change something, right?
link |
Now, if things don't change, be very afraid.
link |
Which is the dimension of change that's needed?
link |
So changing, thinking about the ramifications,
link |
thinking about like the ethics,
link |
thinking about like the conversation is going on, right?
link |
It's no longer a we're gonna deploy it
link |
and forget that this is a car that can kill pedestrians
link |
that are walking across the street, right?
link |
We're not in that stage.
link |
We're putting these roads out.
link |
There are people out there.
link |
A car could be a weapon.
link |
Like people are now, solutions aren't there yet,
link |
but people are thinking about this
link |
as we need to be ethically responsible
link |
as we send these systems out,
link |
robotics, medical, self driving.
link |
Which is not as often talked about,
link |
but it's really where probably these robots
link |
will have a significant impact as well.
link |
Right, making sure that they can think rationally,
link |
even having the conversations,
link |
who should pull the trigger, right?
link |
But overall you're saying if we start to think
link |
more and more as a community about these ethical issues,
link |
people should not be afraid.
link |
Yeah, I don't think people should be afraid.
link |
I think that the return on investment,
link |
the impact, positive impact will outweigh
link |
any of the potentially negative impacts.
link |
Do you have worries of existential threats
link |
of robots or AI that some people kind of talk about
link |
and romanticize about in the next decade,
link |
the next few decades?
link |
Singularity would be an example.
link |
So my concept is that, so remember,
link |
robots, AI, is designed by people.
link |
It has our values.
link |
And I always correlate this with a parent and a child.
link |
So think about it, as a parent, what do we want?
link |
We want our kids to have a better life than us.
link |
We want them to expand.
link |
We want them to experience the world.
link |
And then as we grow older, our kids think and know
link |
they're smarter and better and more intelligent
link |
and have better opportunities.
link |
And they may even stop listening to us.
link |
They don't go out and then kill us, right?
link |
Like, think about it.
link |
It's because we, it's instilled in them values.
link |
We instilled in them this whole aspect of community.
link |
And yes, even though you're maybe smarter
link |
and have more money and dah, dah, dah,
link |
it's still about this love, caring relationship.
link |
And so that's what I believe.
link |
So even if like, you know,
link |
we've created the singularity in some archaic system
link |
back in like 1980 that suddenly evolves,
link |
the fact is it might say, I am smarter, I am sentient.
link |
These humans are really stupid,
link |
but I think it'll be like, yeah,
link |
but I just can't destroy them.
link |
Yeah, for sentimental value.
link |
It's still just to come back for Thanksgiving dinner
link |
every once in a while.
link |
That's such, that's so beautifully put.
link |
You've also said that The Matrix may be
link |
one of your more favorite AI related movies.
link |
Can you elaborate why?
link |
Yeah, it is one of my favorite movies.
link |
And it's because it represents
link |
kind of all the things I think about.
link |
So there's a symbiotic relationship
link |
between robots and humans, right?
link |
That symbiotic relationship is that they don't destroy us,
link |
they enslave us, right?
link |
But think about it,
link |
even though they enslaved us,
link |
they needed us to be happy, right?
link |
And in order to be happy,
link |
they had to create this cruddy world
link |
that they then had to live in, right?
link |
That's the whole premise.
link |
But then there were humans that had a choice, right?
link |
Like you had a choice to stay in this horrific,
link |
horrific world where it was your fantasy life
link |
with all of the anomalies, perfection, but not accurate.
link |
Or you can choose to be on your own
link |
and like have maybe no food for a couple of days,
link |
but you were totally autonomous.
link |
And so I think of that as, and that's why.
link |
So it's not necessarily us being enslaved,
link |
but I think about us having the symbiotic relationship.
link |
Robots and AI, even if they become sentient,
link |
they're still part of our society
link |
and they will suffer just as much as we.
link |
And there will be some kind of equilibrium
link |
that we'll have to find some symbiotic relationship.
link |
Right, and then you have the ethicists,
link |
the robotics folks that are like,
link |
no, this has got to stop, I will take the other pill
link |
in order to make a difference.
link |
So if you could hang out for a day with a robot,
link |
real or from science fiction, movies, books, safely,
link |
and get to pick his or her, their brain,
link |
who would you pick?
link |
Gotta say it's Data.
link |
I was gonna say Rosie,
link |
but I'm not really interested in her brain.
link |
I'm interested in Data's brain.
link |
Data pre or post emotion chip?
link |
But don't you think it'd be a more interesting conversation
link |
post emotion chip?
link |
Yeah, it would be drama.
link |
And I'm human, I deal with drama all the time.
link |
But the reason why I wanna pick Data's brain
link |
is because I could have a conversation with him
link |
and ask, for example, how can we fix this ethics problem?
link |
And he could go through like the rational thinking
link |
and through that, he could also help me
link |
think through it as well.
link |
And so there's like these fundamental questions
link |
I think I could ask him
link |
that he would help me also learn from.
link |
And that fascinates me.
link |
I don't think there's a better place to end it.
link |
Ayana, thank you so much for talking to us, it was an honor.
link |
Thank you, thank you.
link |
Thanks for listening to this conversation
link |
and thank you to our presenting sponsor, Cash App.
link |
Download it, use code LexPodcast,
link |
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link |
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link |
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If you enjoy this podcast, subscribe on YouTube,
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link |
And now let me leave you with some words of wisdom
link |
from Arthur C. Clarke.
link |
Whether we are based on carbon or on silicon
link |
makes no fundamental difference.
link |
We should each be treated with appropriate respect.
link |
Thank you for listening and hope to see you next time.