Ayanna Howard: Human-Robot Interaction & Ethics of Safety-Critical Systems | Lex Fridman Podcast #66
the following is a conversation with Ayane Howard she's a roboticist professor Georgia Tech and director of the human automation systems lab with research interests in human robot interaction assisted robots in the home therapy gaming apps and remote robotic exploration of extreme environments like me in her work she cares a lot about both robots and human beings and so I really enjoyed this conversation this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an Apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma a.m. I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store I personally use cash 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amazing robot you've ever met or perhaps had the biggest impact on your career I haven't met her but I grew up with her but of course Rosie so and I think it's because also who's Rosie Rosie from the Jetsons she is all things to all people right think about it like anything you wanted it was like magic it happened so people not only anthropomorphize but project whatever they wish for the robot to be onto but also I mean think about it she was socially engaging she every so often had an attitude right she kept us honest she would push back sometimes when you know George was doing some weird stuff but she cared about people especially the kids she was like the the perfect robot and you've said that people don't want their robots to be perfect can you elaborate that what do you think that is just like you said Rosie pushed back a little bit every once in a while yeah so I I think it's that so you think about robotics in general we want them because they enhance our quality of life and usually that's linked to something that's functional right even if you think of self-driving cars why is there a fascination because people really do hate to drive like there's the like Saturday driving where I can just be but then there was the I have to go to work every day and I'm in traffic for an hour I mean people really hate that and so robots are designed to basically enhance our ability to increase our quality of life and so the perfection comes from this aspect of interaction if I think about how we drive if we drove perfectly we would never get anywhere right so think about how many times you had to run past the light because you see the car behind you is about to crash into you or that little kid kind of runs into the street and so you have to cross on the other side because there's no cars right like if you think about it we are not perfect drivers some of it is because it our world and so if you have a robot that is perfect in that sense of the word they wouldn't really be able to function with us can you linger a little bit on the word perfection so from the robotics perspective what does that word mean and how is sort of the optimal behaviors you're describing different than what we think that's perfection yeah so perfection if you think about it in the more theoretical point of view it's really tied to accuracy right so if I have a function can I complete it at 100% accuracy with zero errors and so that's kind of if you think about perfection in the size of the word and in a self-driving car realm do you think from a robotics perspective we kind of think that perfection means following the rules perfectly sort of defining staying in the lane changing lanes when there's a green light you go and there's a red light you stop and that that's the and be able to perfectly see all the entities in the scene that's the limit of what we think of as perfection and I think that's where the problem comes is that when people think about perfection for robotics the ones that are the most successful are the ones that are quote unquote perfect like I said Rosie is perfect but she actually wasn't perfect in terms of accuracy but she was perfect in terms of how she interacted and how she adapted and I think that's some of the disconnect is that we really want perfection with respect to its ability to adapt to us we don't really want perfection with respect to 100% accuracy with respect to the rules that we just made up anyway right and so I think there's this disconnect sometimes between what we really want and what happens and we see this all the time like in my research right like the the optimal quote unquote optimal interactions are when the robot is adapting based on the person not 100% following what's optimal based on the roles just to linger on autonomous vehicles for a second just your thoughts maybe off the top of her head is how hard is that problem do you think based on what we just talked about you know there's a lot of folks in the automotive industry they're very confident from Elon Musk two-way mode all these companies how hard is it to solve that last piece did the gap between the perfection and the human definition of how you actually function in this world so this is a moving target so I remember when all the big companies started to heavily invest in us and there was a number of even roboticists as well as you know folks who were putting in the VCS and and corporations Elon Musk being one of them that said you know self-driving cars on the road with people you know within five years that was a little while ago and now people are saying five years ten years twenty years some are saying never right I think if you look at some of the things that are being successful is these basically fixed environments where you still have some anomalies wait you still have people walking you still have stores but you don't have other drivers right like other human drivers are is a dedicated space for the for the cars because if you think about robotics in general where has always been successful is I mean you can say manufacturing like way back in the day right it was a fixed environment humans were not part of the equation we're a lot better than that but like when we can carve out scenarios that are closer to that space then I think that it's where we are so a closed campus where you don't have self-driving cars and maybe some protection so that the students don't jet in front just because they want to see what happens like having a little bit I think that's where we're gonna see the most success in the near future and be slow-moving right not not you know 55 60 70 miles an hour but the the speed of a golf cart right so that said the most successful in the automotive industry robots operating today in the hands of real people are ones that are traveling over 55 miles an hour and in our constrains environment which is Tesla vehicles so we'll test the autopilot so I just I would love to hear of your just thoughts of two things so one I don't know if you've gotten to see you've heard about something called smart summon wait what Tesla system part Apollo system where the car drives zero occupancy no driver in the parking lot slowly sort of tries to navigate the parking lot to find itself to you and there's some incredible amounts of videos and just hilarity that happens as it awkwardly tries to navigate this environment but it's it's a beautiful nonverbal communication between machine and human that I think is a from it's like it's some of the work that you do in this kind of interesting human robot interaction space so what are your thoughts in general water so I I do have that feature new driver Tesla I do mainly because I'm a gadget freak right so I it's a gadget that happens to have some wheels and yeah I've seen some of the videos but what's your experience like I mean your your human robot interaction roboticist you're legit sort of expert in the field so what does it feel for machine to come to you it's one of these very fascinating things but also I am hyper hyper alert right like I'm hyper alert like my but my thumb is like okay I'm ready to take over even when I'm in my car or I'm doing things like automated backing into so there's like a feature where you can do this automating backing into our parking space our bring the car out of your garage or even you know pseudo autopilot on the freeway right I am hyper sensitive I can feel like as I'm navigating like yeah that's an error right there like I am very aware of it but I'm also fascinated by it and it does get better like it I look and see it's learning from all of these people who are cutting it on like every come on it's getting better right and so I think that's what's amazing about it is that this nice dance of you're still hyper-vigilant so you're still not trusting it at all yeah yeah you're using it what on the highway if I were to like what as a roboticist we'll talk about trust a little bit what how do you explain that you still use it is it the gadget freak part like where you just enjoy exploring technology or is that the right actually balance between robotics and humans is where you use it but don't trust it and somehow there's this dance that ultimately is a positive yes so I think I'm I just don't necessarily trust technology but I'm an early adopter right so when it first comes out I will use everything but I will be very very cautious of how I use it do you read about or do you explore but just try it they do like it's crudely to put a crew they do you read the manual or do you learn through exploration I'm an explorer if I have to read the manual then you know I do design then it's a bad user interface it's a failure Elon Musk is very confident that you kind of take it from where it is now to full autonomy so from this human robot interaction you don't really trust and then you try and then you catch it when it fails to it's going to incrementally improve itself into full full way you don't need to participate what's your sense of that trajectory is it feasible so the promise there is by the end of next year by the end of 2020 it's the current promise what's your sense about that journey that test is on so there's kind of three three things going on now I think in terms of will people go like as a user as a adopter will you trust going to that point I think so right like there are some users and it's because what happens is when technology at the beginning and then the technology tends to work your apprehension slow slowly goes away and as people we tend to swing to the other extreme right because like oh I was like hyper hyper fearful or hypersensitive and was awesome and we just tend to swing that's just human nature and so you will have I mean it is a scary notion because most people are now extremely untrusting of autobot they use it but they don't trust it and it's a scary notion that there's a certain point where you allow yourself to look at the smartphone for like 20 seconds and then there'll be this phase shift will be like 20 seconds 30 seconds 1 minute 2 minutes this is scary it's opposition but that's people right that's human that's humans I mean I think of even our use of I mean just everything on the internet right like think about how relying we are on certain apps and certain engines right 20 years ago people have been like oh yeah that's stupid like that makes no sense like of course that's false like now it's just like oh of course I've been using it it's been correct all this time of course aliens I didn't think they existed but now it says they do obvious nth earth is flat so okay but you said three things so one is okay so one is the human and I think there would be a group of individuals that will swing right I just teenagers gene it I mean it'll be clean it'll be adults there's actually an age demographic that's optimal for a technology adoption and you can actually find them and they're actually pretty easy to find just the based on their habits based on so someone like me who wouldn't wasn't no robot Isis or probably be the optimal kind of person right early adopter okay with technology very comfortable and not hyper sensitive right I'm just the hyper sensitive because I designed this stuff yeah so there is a target demographic that will swing the other one though is you still have these hue that are on the road that one is a harder harder thing to do and as long as we have people that are on the same streets that's going to be the big issue and it's just because you can't possibly know well so you can't possibly map the some of the silliness of human drivers right like as an example when you're next to that car that has that big sticker called student driver right like you are like oh either I am going to like go around like we are we know that that person is just gonna make mistakes that make no sense right how do you map that information or if I'm in a car and I look over and I see you know two fairly young looking individuals and there's no student driver bumper and I see them chit-chatting to each other I'm like oh yeah that's an issue right so how do you get that kind of information and that experience into basically an autopilot yeah and there's millions of cases like that where we take little hints to establish context I mean you said kind of beautifully poetic human things but there's probably subtle things about the environment about is about it being maybe time for commuters start going home from work and therefore you can make some kind of judgment about the group behavior of pedestrians or even cities right like if you're in Boston how people cross the street like lights are not an issue versus other places where people will will actually wait for the crosswalk or somewhere peaceful and but what I've also seen so just even in Boston that intersection the intersection is different so every intersection has a personality of its own so that certain neighborhoods of Boston are different so we kind of end the based on different timing of day at night it's all it's all there's a there's a dynamic to human behavior that would kind of figure out ourselves we're not be able to we're not able to introspect and figure it out but somehow we our brain learns it we do and so you're you're saying is there so that's the shortcut that's their shortcut though for everybody is there something that could be done you think that you know that's what we humans do it's just like bird flight right this example they give for flight do you necessarily need to build the bird that flies or can you do an airplane is there shortcut so I think the the shortcut is and I kind of I talk about it as a fixed space where so imagine that there is a neighborhood that's a new smart city or a new neighborhood that says you know what we are going to design this new city based on supporting self-driving cars and then doing things knowing that there's anomalies knowing that people are like this right and designing it based on that assumption that like we're gonna have this that would be an example of a shortcut so you still have people but you do very specific things to try to minimize the noise a little bit as an example and the people themselves become accepting of the notion that there's autonomous cars right right like they move into so right now you have like a you will have a self-selection bias right like individuals will move into this neighborhood knowing like this is part of like the real estate pitch right and so I think that's a way to do a shortcut when it allows you to deploy it allows you to collect then data with these variances and anomalies because people are still people but it's it's a safer space and it's more of an accepting space ie when something in that space might happen because things do because you already have the self selection like people would be I think a little more forgiving than other places and you said three things that would cover all of them the third is legal liability which I don't really want to touch but it's still it's it's still of concern in the mishmash with like with policy as well sort of government all that that whole that big ball of mess yeah gotcha so that's so we're out of time what do you think from robotics perspective you know if you if you're kind of honest of what cars do they they kind of kind of threaten each other's life all the time so cars are very us I mean in order to navigate intersections there's an assertiveness there's a risk-taking and if you were to reduce it to an objective function there's a probability of murder in that function meaning you killing another human being and you're using that first of all yeah it has to be low enough to be acceptable to you on an ethical level as a individual human being but it has to be high enough for people to respect you to not sort of take advantage of you completely and jaywalking front knee and so on so I mean I don't think there's a right answer here but what's how do we solve that how how do we solve that from a robotics perspective one danger and human life is at stake yeah as they say cars don't kill people people kill people people right so I think now robotic algorithms would be killing right so it will be robotics algorithms that are prone oh it will be robotic algorithms don't kill people developers of the right account or there was kill people right I mean one of the things as people are still in the loop and at least in the near and midterm I think people will still be in the loop at some point even if it's a developer like we're not necessarily at the stage where you know robots are programming autonomous robots with different behaviors quite yet not so scary notion sorry to interrupt that a developer is has some responsibility in in it in the death of a human being this uh I mean I think that's why the whole aspect of ethics in our community is so so important right like because it's true if if you think about it you can basically say I'm not going to work on weaponized AI right like people can say that's not what I'm but yet you are programming algorithms that might be used in healthcare algorithms that might decide whether this person should get this medication or not and they don't and they die you okay so that is your responsibility right and if you're not conscious and aware that you do have that power when you're coding and things like that I think that's that's that's just not a good thing like we need to think about this responsibility as we program robots and and computing devices much more than we are yes so it's not an option to not think about ethics I think it's a majority I would say of computer science sort of there it's kind of a hot topic now I think about bias and so on but it's and we'll talk about it but usually it's kind of you it's like a very particular group of people that work on that and then people who do like robotics or like well I don't have to think about that you know there's other smart people thinking about it it seems that everybody has to think about it it's not you can't escape the ethics well there is bias or just every aspect of ethics that has to do with human beings everyone so think about I'm gonna age myself but I remember when we didn't have like testers right and so what did you do as a developer you had to test your own code right like you had to go through all the cases and figure it out and you know and then they realize that you know like we probably need to have testing because we're not getting all the things and so from there what happens is like most developers they do you know a little bit of testing but is usually like okay - my compiler bug out and you look at the warnings okay is that acceptable or not right like that's how you typically think about as a developer and you'll just assume that is going to go to another process and they're gonna test it out but I think we need to go back to those early days when you know you're a developer you're developing there should be like they say you know okay let me look at the ethical outcomes of this because there isn't a second like testing ethical testers right it's you we did it back in the early coding days I think that's where we are with respect to ethics like this go back to what was good practice isn't only because we were just developing the field yeah and it's uh it's a really heavy burden I've had to feel it recently in the last few months but I think it's a good one to feel like I've gotten a message more than one from people you know I've unfortunately gotten some attention recently and I've got messages that say that I have blood on my hands because of working on semi autonomous vehicles so the idea that you have semi autonomy means people will become would lose vigilance and so on as actually be humans as we described and because of that because of this idea that we're creating automation there will be people be hurt because of it and I think that's a beautiful thing I mean it's you know it's many nights where I wasn't able to sleep because of this notion you know you really do think about people that might die because it's technology of course you can then start rationalizing saying well you know what 40,000 people die in the United States every year and we're trying to ultimately try to save us but the reality is your code you've written might kill somebody and that's an important burden to carry with you as you design the code I don't even think of it as a burden if we train this concept correctly from the beginning and I use and not to say that coding is like being a medical doctor the thing about it medical doctors if they've been in situations where their patient didn't survive right do they give up and go away no every time they come in they know that there might be a possibility that this patient might not survive and so when they approach every decision like that's in their back of their head and so why isn't that we aren't teaching and those are tools though right they're given some of the tools to address that so that they don't go crazy but we don't give those tools so that it does feel like a burden versus something of I have a great gift and I can do great awesome good but with it comes great responsibility I mean that's what we teach in terms of you think about medical schools right great gift great responsibility I think if we just changed the messaging a little great gift being a developer great responsibility and this is how you combine those but do you think and this is really interesting it's it's outside I actually have no friends or sort of surgeons or doctors I mean what does it feel like to make a mistake in a surgery and somebody to die because of that like is that something you could be taught in medical school sort of how to be accepting of that risk so because I do a lot of work with health care robotics I I have not lost a patient for example the first one's always the hardest right but they really teach the value right so they teach responsibility but they also teach the value like you're saving 40,000 mm but in order to really feel good about that when you come to a decision you have to be able to say at the end I did all that I could possibly do right versus a well I just picked the first widget and right like so every decision is actually thought through it's not a habit is not a let me just take the best algorithm that my friend gave me right it's a is this it this this the best have I done my best to do good right and so you're right and I think burden is the wrong word if it's a gift but you have to treat it extremely seriously correct so on a slightly related note yeah in a recent paper the ugly truth about ourselves and our robot creations you you discuss you highlight some biases that may affect the function in various robotics systems can you talk through if you remember examples or some there's a lot of examples I use what is bias first of all yes so bias is this and so bias which is different than prejudice so bias is that we all have these preconceived notions about particular everything from particular groups for to habits to identity right so we have these predispositions and so when we address a problem we look at a problem make a decision those preconceived notions might affect our our outputs or outcomes so they're the bias could be positive or negative and then it's prejudice the negative courage is the negative right so prejudice is that not only are you aware of your bias but you are then take it and have a negative outcome even though you are aware wait and there could be gray areas too that's the challenging aspect of all questions actually so I always like so there's there's a funny one and in fact I think it might be in the paper because I think I talked about self-driving cars but think about this we for teenagers right typically we insurance companies charge quite a bit of money if you have a teenage driver so you could say that's an age bias right but no one will click I mean parents will be grumpy but no one really says that that's not fair that's interesting we don't that's right that's right it's a everybody in human factors and safety research almost I mean it's quite ruthlessly critical of teenagers and we don't question is that okay is that okay to be ageist in this kind of way it is and it is agent right is that really there's no question about it and so so these are these this is the gray area right cuz you you know that you know teenagers are more likely to be an accident and so there's actually some data to it but then if you take that same example and you say well I'm going to make the insurance hire for an area of Boston because there's a lot of accidents and then they find out that that's correlated with socio economics well then it becomes a problem right like that is not acceptable but yet the teenager which is age it's against age is right so we figure that I was I by having conversations by the discourse let me throw out history the definition of what is ethical or not has changed and hopefully always for the better correct correct so in terms of bias or prejudice in robotic in algorithms what what examples do sometimes think about so I think about quite a bit the medical domain just because historically right the healthcare domain has had these biases typically based on gender and ethnicity primarily a little an age but not so much you know historically if you think about FDA and drug trials it's you know harder to find a woman that you know aren't childbearing and so you may not test on drugs at the same level right so there there's these things and so if you think about robotics right something as simple as I'd like to design an exoskeleton right what should the material be what should the way P which should the form factor be are you who are you going to design it around I will say that in the US you know women average height and weight is slightly different than guys so who are you gonna choose like if you're not thinking about it from the beginning as you know okay I when I design this and I look at the algorithms and I design the control system and the forces and the torques if you're not thinking about well you have different types of body structure you're gonna design to you know what you're used to oh this fits my all the folks in my lab right so think about it from the very beginning it's important what about sort of algorithms that train on data kind of thing the sadly our society already has a lot of negative bias and so if we collect a lot of data even if it's a balanced weight that's going to contain the same bias that a society contains and so yeah was is there is there things there that bother you yeah so you actually said something you ain't said how we have biases but hopefully we learn from them and we become better right and so that's where we are now right so the data that we're collecting is historic it's so it's based on these things when we knew it was bad to discriminate but that's the data we have and we're trying to fix it now but we're fixing it based on the data that was used in the first place most right and so and so the decisions and you can look at everything from the hope the whole aspect of predictive policing criminal recidivism there was a recent paper that had the healthcare algorithms which had kind of a sensational titles I'm not pro sensationalism in titles but um but you read it right so yeah make sure read it but I'm like really like what's the topic of the sensationalism I mean what's underneath it what if you could sort of educate me and what kind of bias creeps into the healthcare space yes so he's already kind of oh this one was the headline was racist AI algorithms okay like okay that's totally a clickbait title yeah oh and so you looked at it and so there was data that these researchers had collected I believe I want to say was either science or nature he just was just published but they didn't have the sensational tiger it was like the media and so they had looked at demographics I believe between black and white women right and they were showed that there was a discrepancy in in the outcomes right and so and it was tied to ethnicity tied to race the piece that the researchers did actually went through the whole analysis but of course I mean they're the journalists with AI a problematic across the board rights sake and so this is a problem right and so there's this thing about oai it has all these problems we're doing it on historical data and the outcomes aren't even based on gender or ethnicity or age but I am always saying is like yes we need to do better right we need to do better it is our duty to do better but the worst AI is still better than us like like you take the best of us and we're still worse than the worst AI at least in terms of these things and that's actually not discussed right and so I think and that's why the sensational title right and it's so it's like so then you can have individuals go like oh we don't need to use this hey I'm like oh no no no no I want the AI instead of the the doctors that provided that data cuz it's still better than that yes right I think it's really important to linger on the idea that this AI is racist it's like well compared to what sort of the we that I think we set unfortunately way too high of a bar for AI algorithms and in the ethical space where perfect is I would argue probably impossible then if we set the bar of perfection essentially if it has to be perfectly fair whatever that means is it means we're setting it up for failure but that's really important to say what you just said which is well it's still better yeah and one of the things I I think that we don't get enough credit for just in terms of as developers is that you can now poke at it right so it's harder to say you know is this hospital is the city doing something right until someone brings in a civil case right well were they I it can process through all this data and say hey yes there there's some an issue here but here it is we've identified it and then the next step is to fix it I mean that's a nice feedback loop versus like waiting for someone to sue someone else before it's fixed right and so I think that power we need to capitalize on a little bit more right instead of having the sensational titles have the okay this is a problem and this is how we're fixing it and people are putting money to fix it because we can make it better now you look at like facial recognition how joy she basically called out the companies and said hey and most of them were like Oh embarrassment and the next time it had been fixed right it had been fixed better right and then I was like oh here's some more issues and I think that conversation then moves that needle to having much more fair and unbiased and ethical aspects as long as both sides the developers are willing to say okay I hear you yes we are going to improve and you have other developers are like you know hey AI it's wrong but I love it right yes so speaking of this really nice notion that AI is maybe flawed but better than humans so just made me think of it one example of flawed humans is our political system do you think or you said judicial as well do you have a hope for AI sort of being elected for president or running our Congress or being able to be a powerful representative of the people so I mentioned and I truly believe that this whole world of AI is in partnerships with people and so what does that mean I I don't believe or and maybe I just don't I don't believe that we should have an AI for president but I do believe that a president should use AI as an adviser right like if you think about it every president has a cabinet of individuals that have different expertise that they should listen to right like that's kind of what we do and you put smart people with smart expertise around certain issues and you listen I don't see why a I can't function as one of those smart individuals giving input so maybe there's an AI on health care maybe there's an AI on education and right like all these things that a human is processing right because at the end of the day there's people that are human that are going to be at the end of the decision and I don't think as a world as a culture as xiety that we would totally be and this is us like this is some fallacy about us but we need to see that leader that person as human and most people don't realize that like leaders have a whole lot of advice right like when they say something is not that they woke up well usually they don't wake up in the morning and be like I have a brilliant idea right it's usually a ok let me listen I have a brilliant idea but let me get a little bit of feedback on this like ok and then it's saying yeah that was an awesome idea or it's like yeah let me go back already talked to a bunch of them but are there some possible solutions to the biases presence in our algorithms beyond what we just talked about so I think there's two paths one is to figure out how to systematically do the feedback in corrections so right now it's ad hoc right it's a researcher identify some outcomes that are not don't seem to be fair right they publish it they write about it and the either the developer or the companies that have adopted the algorithms may try to fix it right and so it's really ad hoc and it's not systematic there's it's just it's kind of like I'm a researcher that seems like an interesting problem which means that there's a whole lot out there that's not being looked at right because it's kind of researcher driven I and I don't necessarily have a solution but that process I think could be done a little bit better one way is I'm going to poke a little bit at some of the corporations right like maybe the corporations when they think about a product they should instead of in addition to hiring these you know bug they give these oh yeah yeah yeah wait you think Awards when you find a bug yeah yes Joey bug yeah you know let's let's put it like we will give the whatever the award is that we give for the people who finally secure holls find an ethics hole right like find an unfairness hole and we will pay you X for each one you find I mean why can't they do that one is a win-win they show that they're concerned about it that this is important and they don't have to necessarily dedicate it their own like internal resources and it also means that everyone who has like their own bias lens like I'm interested in age and so I'll find the ones based on age and I'm interested in gender and right which means that you get like all of these different perspectives but you think of it in a data-driven way so like go see sort of if we look at a company like Twitter it gets it's under a lot of fire for discriminating against certain political beliefs correct and sort of there's a lot of people this is the sad thing because I know how hard the problem is and I know the Twitter folks are working with a heart at it even Facebook that everyone seems to hate I worked in really hard of this it you know the kind of evidence that people bring is basically anecdotal evidence well me or my friend all we said is X and for that we got banned and and that's kind of a discussion of saying well look that's usually first of all the whole thing is taken out of context so they're they present sort of anecdotal evidence and how are you supposed to as a company in a healthy way have a discourse about what is and isn't ethical what how do we make algorithms ethical when people are just blowing everything like they're outraged about a particular and a godel evident piece of evidence that's very difficult to sort of contextualize in the big data-driven way do you have a hope for companies like Twitter and yeah so I think there's a couple of things going on right first off the remember this whole aspect of we are becoming reliant on technology we're also becoming reliant on a lot of these the the apps and the resources that are provided right so some of it is kind of anger like I need you right and you're not working for me but I think and so some of it and I and I wish that there was a little bit of change and rethinking so some of it is like oh we'll fix it in house no that's like okay I'm a fox and I am going to watch these hens because I think it's a problem that foxes eat hens No right like use like be good citizens and say look we have a problem and we are willing to open ourselves up for others to come in and look at it and not try to fix it in house because if you fix it in house there's conflict of interests if I find something I'm probably going to want to fix it and hopefully the media won't pick it up right and that then caused this distrust because someone inside is going to be mad at you and go out and talk about how yeah they can the resume survey because it's rightly the best people like just say look we have this issue community help us fix it and we will give you like you know the bug finder fee if you do did you have a hope that the community us as a human civilization on the whole is good and can be trusted to guide the future of our civilization into positive direction I think so so I'm an optimist right and you know we there were some dark times in history always I think now we're in one of those dark times I truly do and which aspect the polarization and it's not just us right so if it was just us I'd be like yeah say us thing but we're seeing it like worldwide this polarization and so I worry about that but I do fundamentally believe that at the end of the day people are good right and why do I say that because any time there's a scenario where people are in danger and I would use I saw Atlanta we had Snowmageddon and people can laugh about that people at the time so the city closed for you know little snow but it was ice and the city closed down but you had people opening up their homes and saying hey you have nowhere to go come to my house right hotels were just saying like sleep on the floor like places like you know the grocery stores were like hey here's food there was no like oh how much are you gonna pay me it was like this such a community and like people who didn't know each other strangers were just like can I give you a ride home and that was a point I was like you know I like that that there reveals that the deeper thing is is there's a compassion or love that we all have within us it's just that when all that is taken care of and get bored we love drama and that's I think almost like the division is the sign of the time is being good is that it's just entertaining under some unpleasant mammalian level to watch to disagree with others and Twitter and Facebook are actually taking advantage of that in the sense because it brings you back to the platform and their advertisers are driven so they make a lot of money love doesn't sell quite as well in terms of advertisement so you've started your career NASA Jet Propulsion Laboratory but before I'd ask a few questions there have you happen to have ever seen Space Odyssey 2001 Space Odyssey yes okay do you think Hal 9000 so we're talking about ethics do you think how did the right thing by taking the priority of the mission over the lives of the astronauts do you think Cal is good or evil easy questions yeah Hal was misguided you're one of the people that would be in charge of an algorithm like Hal yes so how would you do better if you think about what happened was there was no failsafe right so we perfection right like what is that I'm gonna make something that I think is perfect but if my assumptions are wrong it'll be perfect based on the wrong assumptions all right that's something that you don't know until you deploy and like oh yeah messed up but what that means is that when we design software such as in Space Odyssey when we put things out that there has to be a failsafe there has to be the ability that once it's out there you know we can grade it as an F and it fails and it doesn't continue right if there's some way that it can be brought in and and removed and that's aspect because that's what happened with what how it was like assumptions were wrong it was perfectly correct based on those assumptions and there was no way to change change it change the assumptions at all and the change the fallback would be to humans so you ultimately think like humans should be you know it's not Turtles or AI all the way down it's at some point there's a human that actually don't think that and again because I do human robot interaction I still think the human needs to be part of the equation at some point so what just looking back what are some fascinating things in robotic space that NASA was working at the time or just in general what what have you gotten to play with and what are your memories from working at NASA yes so one of my first memories was they were working on a surgical robot system that could do eye surgery right and this was back in oh my gosh it must have been Oh maybe 92 93 94 so it's like almost like a remote operation oh yeah it was it was a remote operation in fact that you can even find some old tech reports on it so think of it you know like now we have da Vinci right like think of it but these are like the late 90s right and I remember going into the lab one day and I was like what's that right and of course it wasn't pretty right because the technology but it was like functional and you had as this individual that could use version of haptics to actually do the surgery and they had this mock-up of a human face and like the eyeballs you can see this little drill and I was like oh that one I vividly remember because it was so outside of my like possible thoughts of what could be done the kind of precision and uh hey what what's the most amazing of a thing like that I think it was the precision it was the kind of first time that I had physically seen this robot machine human interface right versus because manufacturing have been you saw those kind of big robots right but this was like oh this is in a person there's a person in a robot like in the same space the meeting them in person I like for me it was a magical moment that I can't as a life-transforming that I recently met spot mini from Boston Dynamics Elysee I don't know why but on the human robot interaction for some reason I realized how easy it is to anthropomorphize and it was I don't know it was uh it was almost like falling in love this feeling of meeting and I've obviously seen these or was a lot on video and so on but meeting in person just having that one-on-one time it's different so do you have you had a robot like that in your life that was made you maybe fall in love with robotics sort of odds like meeting in person I mean I mean I I loved robotics yeah that was a 12 year old like I would be a roboticist actually was I called it cybernetics but so my my motivation was Bionic Woman I don't know if you know that is um and so I mean that was like a seminal moment but I didn't me like that was TV right like it wasn't like I was in the same space and I meant I was like oh my gosh you're like real just linking I'm Bionic Woman which by the way because I've read that about you I watched a bit bits of it and it's just so no offence terrible I've seen a couple of reruns lately it's uh but of course at the time is probably disgusted the imagination especially when you're younger just catch you but which aspect did you think of it you mentioned cybernetics did you think of it as robotics or did you think of it as almost constructing artificial beings like is it the intelligent part that that captured your fascination or was it the whole thing like even just the limbs and just so for me it would have in another world I probably would have been more of a biomedical engineer because what fascinated me was the by on it was the parts like the Bionic parts the limbs those aspects of it are you especially drawn to humanoid or human-like robots I would say human-like not humanoid right and when I say human-like I think it's this aspect of that interaction whether it's social and it's like a dog right like that's human-like because it's understand us it interacts with us at that very social level - you know humanoids are part of that but only if they interact with us as if we are human but just to linger on NASA for a little bit what do you think maybe if you have other memories but also what do you think is the future of robots in space will mention how but there's incredible robots and NASA's working on in general thinking about in art as we venture out human civilization ventures out into space what do you think the future of robots is there yes so I mean there's the near term for example they just announced the the rover that's going to the moon which you know that's kind of exciting but that's like near-term you know my favorite favorite favorite series is Star Trek right you know I really hope and even Star Trek like if I calculate the years I wouldn't be alive but I would really really love to be in that world like even if it's just at the beginning like you know like voyage like adventure one so basically living in space yeah with what what robots would a robots do data were roll the data would have to be even though that wasn't you know that was like later but so data is a robot that has human-like qualities right without the emotion ship yeah you don't like emotion well they know what the emotion ship was kind of a mess right it took a while for for that thing to adapt but and and so why was that an issue the issue is is that emotions make us irrational agents that's the problem and yet he could think through things even if it was based on an emotional scenario right based on pros and cons but as soon as you made him emotional one of the metrics he used for evaluation was his own emotions not people around him right like and so we do that as children right so we're very egocentric we're very egocentric and so isn't that just an early version of the emotion ship then I haven't watched much Star Trek I have also met adults right and so that is that is a developmental process and I'm sure there's a bunch of psychologists that can go through like you can have a six-year-old dolt who has the emotional maturity of a ten-year-old right and so there's various phases that people should go through in order to evolve and sometimes you don't so how much psychology do you think a topic that's rarely mentioned in robotics but how much the psychology come to play when you're talking about HRI human robot interaction when you have to have robots that actually interact with you tons so we like my group as well as I read a lot in the cognitive science literature as well as the psychology literature because they understand a lot about human human relations and developmental milestones things like that and so we tend to look to see what what's been done out there sometimes what we'll do is we'll try to match that to see is that human human relationship the same as human robot sometimes it is and sometimes is different and then when it's different we have to we try to figure out okay why is it different in this scenario but it's the same in the other scenario right and so we try to do that quite a bit would you say that's if we're looking at the future of human robot interaction would you say the psychology piece is the hardest like if it's I mean it's a funny notion for you as I don't know if you consider yeah I mean one way to ask it do you consider yourself for roboticist or psychologists oh I consider myself a robot is's that plays the act of a psychologist but if you were look at yourself sort of you know 20 30 years from now do you see yourself more and more wearing the psychology hat another way to put it is are the hard problems in human robot interactions fundamentally psychology or is it still robotics the perception of manipulation planning all that kind of stuff it's actually neither the hardest part is the adaptation in the interaction so learning it's the interface it's the learning and so if I think of like I've become much more of a roboticist /ai person then when I like originally again I was about the bionics I was looking I was electrical engineer I was control theory right like and then I started realizing that my algorithms needed like human data right and so that I was like okay what is this human thing but how do I incorporate human data and then I realized that human perception had there was a lot in terms of how we perceived the world it's so trying to figure out how do i model human perception for my and so I became a HRI person human robot interaction person from being a control theory and realizing that humans actually offered quite a bit and then when you do that you become one more of artificial intelligence AI and so I see myself evolving more in this AI world under the lens of robotics having Hardware interacting with people so you're a world-class expert researcher in robotics and yet others you know there's a few it's a small but fierce community of people but most of them don't take the journey into the h of HR I into the human so why did you brave into the interaction with humans it seems like a really hard problem it's a hard problem and it's very risky as an academic yes and I knew that when I started down that journey that it was very risky as an academic in this world that was nuanced it was just developing we didn't have a conference right at the time because it was the interesting problems that was what drove me it was the fact that I looked at what interests me in terms of the application space and the problems and that pushed me into trying to figure out what people were and what humans were and how to adapt to them if those problems weren't so interesting I'd probably still be sending Rovers to glaciers right but the problems were interesting and the other thing was that they were hard right so it's I like having to go into a room and being like I don't know and then going back and saying okay I'm gonna figure this out I do not I'm not driven when I go in like oh there are no surprises like I don't find that satisfying if that was the case I go someplace and make a lot more money right I think I stay in academic because and choose to do this because I can go into a room like that's hard yeah I think just for my perspective maybe you can correct me on it but if I just look at the field of AI broadly it seems that human robot interaction has the most one of the most number of open problems people especially relative to how many people are willing to acknowledge that there are this because most people are just afraid of the human so they don't even acknowledge how many open problems are but it's a in terms of difficult problems to solve exciting spaces it seems to be an incredible for that it is it is exciting you mentioned trust before what role does trust from interacting with autopilot to in the medical context what role distress playing the human robot trap so some of the things I study in this domain is not just trust but it really is over trust how do you think about over traffic what is for so what is what is trust and what is overdressed basically the way I look at it is trust is not what you click on a survey just this is about your behavior so if you interact with the technology based on the decision are the actions of the technology as if you trust that decision then you're trusting right and I mean even in my group we've done surveys that you know on the thing do my you trust robots of course not would you follow this robot in a burning building of course not right and then you look at their actions and you're like clearly your behavior does not match what you think right or which you think you would like to think right and so I'm really concerned about the behavior because that's really at the end of the day when you're in the world that's what will impact others around you it's not whether before you went onto the street you you clicked on like I don't trust self-driving cars you know that from an outsider perspective it's always frustrating to me well I read a lot so I'm Insider in a certain philosophical sense the it's frustrating to me how often Trust is used in surveys and how people say make claims that have any kind of finding they make about somebody clicking on answer you just trust is uh yet behavior just you said it beautiful I mean the action your own behavior as is what Trust is I mean that everything else is not even close it's almost like a absurd comedic poetry that you weave around your actual behavior so some people can say they're they their trust you know I trough trust my wife husband or not whatever but the actions is what speaks volumes but their car probably don't I trust them I'm just making sure no no that's yeah it's like even if you think about cars I think it's a beautiful case I came here at some point I'm sure on either Oberer lift right I remember when it first came out I I bet if they had had a survey would you get in the car with a stranger and pay them yes how many people do you would think would have said like really you know wait even worse would you get in the car with a stranger at 1:00 a.m. in the morning to have them drop you home as a single female yeah like how many people would say that's stupid yeah and now look at where we are I mean people put kids like great links oh yeah my child has to go to school and I yeah I'm gonna put my kid in this car with a stranger yeah I mean it's just a fascinating how like what we think we think is not necessarily matching our behavior and certainly with robots for the tallest vehicles and and all all the kinds of robots you work with that's it's yeah it's the way you answer it especially if you've never interacted with that robot before if you haven't had the experience you're being able to respond correctly I know surveys is impossible but what do you what role does trust play in the interaction do you think like is it good - is it good to trust a robot what is over trust mean what is it it's good to kind of how you feel about autopilot currently which is like for a roboticist perspective is like is so very cautious yeah so this is still an open area of research but basically what I would like in a perfect world is that people trust the technology when is working a hundred percent and people will be hypersensitive and identify when it's not but of course we're not there that's that's the ideal world and but we find is that people swing right they tend to swing which means that if my first and like we have some papers like first impressions in everything is everything right if my first instance with technology with robotics is positive it mitigates any risk in it correlates with like best outcomes it means that I'm more likely to either not see it when it makes a mistakes or faults or I'm more likely to forgive it and so this is a problem because technology is not 100 percent accurate right it's not as if it's inaccurate although it may be perfect how do you get that first moment right do you think there's also an education about the capabilities and limitations of the system do you have a sense of how do you educate people correctly in that first interaction again this is this is an open-ended problem so one of the study that actually has given me some hope that I were trying to figure out how to put in robotics so there was a research study that had showed for medical AI systems giving information to radiologists about you know here you need to look at these areas on the x-ray what they found was that when the system provided one choice there was this aspect of either no trust or over trust right like I'm not going I don't believe it at all or a yes yes yes yes and they was miss things right instead when the system gave them multiple choices like here are the three even if it knew like you know it had estimated that the top area you need to look at was he you know someplace on the x-ray if it gave like one plus others the trust was maintained and the accuracy of the entire population increased right so basically it was a you're still trusting the system but you're also putting in a little bit of like your human expertise like you're a human decision processing into the equation so it helps to mitigate that over trust risk yeah so there's a fascinating balance tough to strike I haven't figured out again exciting open area research exactly so what are some exciting applications of human robot interaction you started a company maybe you can talk about the the exciting efforts there but in general also what other space can robots interact with humans and help yeah so besides healthcare cuz you know that's my bias lens my other bias lens is education I think that well one we definitely we in the u.s. you know we're doing okay with teachers but there's a lot of school districts that don't have enough teachers if you think about the teacher-student ratio for at least public education um in some districts it's crazy it's like how can you have learning in that classroom right because you just don't have the human capital and so if you think about robotics bringing that in to classrooms as well as the after-school space where they offset some of this lack of resources and certain communities I think that's a good place and then turning on the other end is using the system's then for workforce retraining and dealing with some of the things that are going to come out later on of job loss like thinking about robots and Nai systems for retraining and Workforce Development I think that's exciting areas that can be pushed even more and it would have a huge huge impact what would you say some of the open problems were in education so it's a exciting so young kids and the older folks or just folks of all ages who need to be retrained we need to sort of open themselves up to a whole nother area of work what what are the problems to be solved there how do you think robots can help we we have the engagement aspect right so we can figure out the engagement that's not a what do you mean by engagement so identifying whether a person is focused is like that we can figure out what we can figure out and and there's some positive results in this is that personalized adaptation based on any con sense right so imagine I think about I have an agent and I'm working with a kid learning I don't know algebra - in that same agent then switch and teach some type of new coding skill to a displacement Anik like what does that actually look like right like hardware might be the same content is different to different target demographics of engagement like how do you do that how important do you think personalization is in human robot interaction and not just mechanic or student but like literally to the individual human being I think personalization is really important but a caveat is that I think we'd be ok if we can personalize to the group right and so if I can label you as along some certain dimensions then even though it may not be you specifically I can put you in this group so the sample size this is how they best learn this is how they best engage even at that level it's really important and it's because I mean it's one of the reasons why educating in large classrooms is so hard right you teach too you know the median but there's these you know individuals that are you know struggling and then you have highly intelligent individuals and those are the ones that are usually you know kind of left out so highly intelligent individuals may be disruptive and those who are struggling might be you disruptive because they're both bored yeah and if you narrow this the definition of the group or in the size of the group enough you'll be able to address their individual yeah it's not individual needs but really gross needs a group most important group needs right right and that's kind of what a lot of successful recommender systems do is Spotify and so on say sad to believe but I'm as a music listener probably in some sort of large group it's very sadly predictable been labeled yeah I've been labeled and and successfully so because they're able to recommend stuff that I yeah but applying that to education right there's no reason why it can't be done do you have a hope for our education system I have more hope for workforce development and that's because I'm seeing investments even if you look at VC investments in education the majority of it has lately been going to workforce retraining right and so I think that government investments is increasing there's like a claim and some of it's based on fear right like AI is gonna come and take over all these jobs so what are we gonna do with all these non paying taxes that aren't coming to us by our citizens and so I think I'm more hopeful for that not so hopeful for early education because it's this it's still a who's gonna pay for it and you won't see the results for like 16 to 18 years it's hard for people to wrap their heads around that but on the retraining part what are your thoughts there's a candidate andrew yang running for president and saying that sort of AI automation robots universal basic income universal basic income in order to support us as we kind of automation takes people's jobs and to explore and find other means like you have a concern of society transforming effects of automation and robots and so on I do I do know that AI robotics will displace workers like we do know that but there'll be other workers that will be defined new jobs what I worry about is that's not what I worry about like we'll all the jobs go away what I worry about is the type of jobs that will come out right like people who graduate from Georgia Tech will be okay right we give them the skills they will adopt even if their current job goes away I do worry about those that don't have that quality of an education right will they have the ability the background to adapt to those new jobs that I don't know that I worry about which will convey even more polarization in in our society internationally and everywhere I worry about that I also worry about not having equal access to all these wonderful things that AI can do and robotics can do I worry about that you know people like people like me from Georgia Tech from say MIT will be okay right but that's such a small part of the population that we need to think much more globally of having access to the beautiful things whether it's AI and healthcare AI and education may ion and politics right I worry about and that's part of the thing that you were talking about is people that build a technology had to be thinking about ethics have to be thinking about access yeah and all those things and not not just a small small subset let me ask some philosophical slightly romantic questions all right but they listen to this will be like here he goes again okay do you think do you think one day we'll build an AI system that we a person can fall in love with and it would love them back like in a movie her for exam yeah although she she kind of didn't fall in love with him uh she fell in love with like a million other people something like that so you're the jealous type I see we humans at the judge yes so I do believe that we can design systems where people would fall in love with their robot with their AI partner that I do believe because it's actually and I won't I don't like to use the word manipulate but as we see there are certain individuals that can be manipulated if you understand the cognitive science about it right alright so I mean if you could think of all close relationship and love in general as a kind of mutual manipulation that dance the human dance I mean many patients a negative connotation and I don't like to use that word particularly I guess another way to phrase is you're getting as it could be algorithmic eyes or something it could be the relationship building part can yeah yeah I mean just think about it there we have and I don't use dating sites but from what I heard there are some individuals that have been dating that have never saw each other right in fact there's a show I think that tries to I weed out fake people like there's a show that comes out right because like people start faking like what's the difference of that person on the other end being an AI agent right and having a communication are you building a relationship remotely like there there's no reason why that can't happen in terms of human robot interaction was a what role you've kind of mentioned what data emotion being can be problematic if not implemented well I suppose what role does emotion some other human-like things the imperfect things come into play here for a good human robot interaction and something like love yes so in this case and you had asked can i AI agent love a human back I think they can emulate love back right and so what does that actually mean it just means that if you think about their programming they might put the other person's needs in front of theirs and certain situations right you look at think about it as a return on investment like was my return on investment as part of that equation that person's happiness you know has some type of you know algorithm waiting to it and the reason why is because I care about them right that's the only reason right but if I care about them and I show that then my final objective function is length of time of the engagement right so you can think of how to do this actually quite easily and so but that's not love well so that's the thing it I think it emulates love because we don't have a classical definition of love right but and we don't have the ability to look into each other's minds to see the algorithm and yeah I guess what I'm getting at is is it possible that especially if that's learned especially if there's some mystery and black box nature to the system how is that you know how is it any different I was any different and in terms of sort of if the system says I'm cautious I'm afraid of death and it does indicate that it loves you another way to sort of phrase I be curious to see what you think do you think there'll be a time when robots should have rights you've kind of phrased the robot in a very roboticist way it's just a really good way but saying okay well there's an objective function and I can see how you can create a compelling human robot interaction experience that makes you believe that the robot cares for your needs and even something like loves you but what if the robot says please don't turn me off what if the robot starts making you feel like there's an entity of being a soul there all right do you think there'll be a future hopefully you won't laugh too much of this but there were there's they do ask for rights so I can see a future if we don't address it in the near term where these agents as they adapt and learn could say hey this should be something that's fundamental I hopefully think that we would address it before it gets to that point you think so that you think that's a bad future is like what is that a negative thing where they ask or being discriminated against I guess it depends on what role have they attained at that point right and so if I think about now careful what you say because the robots fifty years from when I'll be listening to this and you'll be on TV is saying this is what roboticists used to believe and so this is my and as I said I have a bias lens and my robot friends will understand that yes but so if you think about it and I actually put this in kind of fee as a robot assists you don't necessarily think of robots as human with human rights but you could think of them either in the category of property or you can think of them in the category of animals right and so both of those have different types of rights so animals have their own rights as as a living being but you know they can't vote they can't write they can be euthanized but as humans if we abuse them we go to jail like right so they do have some rights that protect them but don't give them the rights of like citizenship and then if you think about property property the rights are associated with the person right so if someone vandalizes your property or steals your property like there are some rights but it's associated with the person who owns that if you think about it back in the day and if you remember we talked about you know how society has changed women were property right they were not thought of as having rights they were thought of as property of like their yeah salting a woman meant assaulting the property of somebody else's butt exactly and so what I envision is is that we will establish some type of norm at some point but that it might evolve right like if you look at women's rights now like there are some countries that don't have and the rest of the world is like why that makes no sense right and so I do see a world where we do establish some type of grounding it might be based on property rights it might be based on animal rights and if it evolves that way I think we will have this conversation at that time because that's the way our society traditionally has evolved beautifully puts just out of curiosity at Anki geebo main field robotics within robot curious eye how it works we think robotics were all these amazing robotics companies led created by incredible roboticists and they've all went out of business recently why do you think they didn't last long why is this so hard to run a robotics company especially one like these which are fundamentally HR are HRI human robot interaction robots yeah one has a story only one of them I don't understand and that was on key that's actually the only one I don't understand I don't understand either it's you know I mean I looked like from the outside you know I've looked at their sheets I've looked like the data that's oh you mean like business-wise yeah yeah and like I look at all I look at that data and I'm like they seem to have like product market fit like so that's the only one I don't understand the rest of it was product market fit what's product market feel if it just just that how do you think about it yes so although we rethink robotics was getting there right but I think it's just the timing it just they're the clock just timed out I think if they had been given a couple more years if they would have been okay but the other ones were still fairly early by the time they got into the market and so product market fit is I have a product that I want to sell at a certain price are there enough people out there the market that are willing to buy the product at that market price for me to be a functional viable profit bearing company right so product market fit if it costs you a thousand dollars and everyone wants it and only is willing to pay a dollar you have no product market fit even if you could sell it for you know it's enough for a dollar because you can't you so hard is it for robots sort of maybe if you look at iRobot the company that makes Roomba vacuum cleaners can you comment on did they find the right product market product fit or like are people willing to pay for robots is also another kind of question about iRobot in their story right like when they first they had enough of a runway right when they first started they weren't doing vacuum cleaners right they were a military contracts primarily government contracts designing robots yeah I mean that's what they were that's how they started right and they still do a lot of incredible work there but yeah that was the initial thing that gave him enough funding to then try to the vacuum cleaner is what I've been told was not like their first rendezvous in terms of designing a product right and so they they were able to survive until they got to the point that they found a a product price market right and even with if you look at the the Roomba the price point now is different than when it was first released right it was an early adopter price but they found enough people who were willing to defend it and I mean though you know I forgot what their loss profile was for the first couple of you know years but they became profitable in sufficient time that they didn't have to close the doors so they found the right there's still there's still people willing to pay a large amount of money so or a thousand dollars for for vacuum cleaner unfortunately for them now that they've proved everything out figured it all out the other side yeah and so that's that's the next thing right the competition and they have quite a number even like there's some some products out there you can go to you know you're up and be like oh I didn't even know this one existed so so this is the thing though like with any market I I would this is not a bad time although you know as a roboticist its kind of depressing but I actually think about things like with the I would say that all of the companies that are now in the top five or six they weren't the first to the stage right like Google was not the first search engine sorry Alta Vista right Facebook was not the first sorry myspace right like think about it they were not the first players those first players like they're not in the top five ten no fortune 500 companies right they proved they started to prove out the market they started to get people interested they started the buzz but they didn't make it to that next level but the second match right the second batch I think might make it to the next level do you when do you think the the Facebook of Roja the Facebook of Robotics sorry take that phrase back because people deeply for some reason I know why but it's I think exaggerated distrust Facebook because of the privacy concerns and so on and with robotics one of the things you have to make sure all the things we've talked about is to be transparent and have people deeply trust you to let it well robot into their lives into their home what do you think the second batch of robots local is it five ten years twenty years that will have robots in our homes and robots in our hearts so if I think about and because I try to follow the the VC kind of space in terms of robotic investments and right now I don't know if they're gonna be successful I don't know if this is the second batch but there's only one batch that's focused on like the first batch right and then there's all these self-driving X's right and so I don't know if they're a first batch of something or if I like I don't know quite where they fit in but there's a number of companies the co robot I'll call them Co robots that are still getting VC investments they some of them have some of the flavor of like rethink robotics some of them have some of the flavor like hurry what's a col robot of course so basically a robot in human working in the same space so some of the companies are focused on manufacturing so having a robot and human working together in a factory some of these Co robots are robots and humans working in the home working in clinics like there's different versions of these companies in terms of their products but they're all so rethink robotics would be like one of the first at least well known companies focus on this space so I don't know if this second if this is a second batch or if this is still part of the first batch that I don't know and then you have all these other companies in this self-driving you know space and I don't know if that's a first batch or again a second batch yeah so there's a lot of mystery about this now of course it's hard to say that this is the second batch until it you know approves outright correct exactly yeah we need a unicorn yeah exactly the why do you think people are so afraid at least in popular culture of legged robots like those work than Boston Dynamics or just robotics in general if you were to psychoanalyze that fear what do you make of it and should they be afraid sorry so should people be afraid I don't think people should be afraid but with a caveat I don't think people should be afraid given that most of us in this world understand that we need to change something right so given that now things don't change be very afraid what which is the dimension of change that's needed so changing of thinking about the ramifications thinking about like the ethics thinking about like the conversation is going on right it's not it's no longer a we're gonna deploy it and forget that you know this is a car that can kill pedestrians that are walking across the street right it's we're not in that stage where a we're putting these roads out there are people out there yes a car could be a weapon like people are now solutions aren't there yet but people are thinking about this as we need to be ethically responsible as we send these systems out robotics medical self-driving and military - and Miller and military just not as often talked about but it's really we're probably these robots will have a significant impact as well correct correct right making sure that they can think rationally even having the conversations who should pull the trigger right but overall you're saying if we start to think more and more as a community about these ethical issues people should not be afraid yeah I don't think people should be afraid I think that the return on investment the impact positive impact will outweigh any of the potentially negative impacts do you have worries of existential threats of robots or AI that some people kind of talk about and romanticize about and then you know in those decade in the next few decades no I don't singularity will be an example so my concept is is that so remember robots AI is designed by people yes it has our values and I always correlate this with a parent and a child all right so think about it as a parent would we want we want our kids to have a better life than us we want them to expand we want them to experience the world and then as we grow older our kids think and know they're smarter and better and more intelligent and have better opportunities and they may even stop listening to us they don't go out and then kill us right like think about it it's because we it's instilled in them values we instilled in them this whole aspect of community and yes even though you're maybe smarter and more have more money and data it's still about this love caring relationship and so that's what I believe so even like you know we've created the singularity and some archaic system back in like 1980 that suddenly evolves the fact is it might say I am smarter I am sentient these humans are really stupid but I think it'll be like yeah but I just can't destroy that yeah for sentimental value it's still just for to come back for Thanksgiving dinner every once in a while exactly this so beautifully put you've you've also said that the matrix may be one of your more favorite AI related movies can you elaborate why yeah it is one of my favorite movies and it's because it represents kind of all the things I think about so there's a symbiotic relationship between robots and humans right that symbiotic relationship is that they don't destroy us they enslave us right but think about it even though they enslaved us they needed us to be happy right and in order to be happy they had to create this Kruti world that they then had to live in right that's the whole but then there were humans that had a choice wait like you had a choice to stay in this horrific horrific world where it was your fantasy and life with all of the anomalies perfection but not accurate or you can choose to be on your own and like have maybe no food for a couple of days but you were totally autonomous and so I think of that as and that's why so it's not necessarily us being enslaved but I think about us having this symbiotic relationship robots and AI even if they become sentient they're still part of our society and they will suffer just as much as us and there there will be some kind of equilibrium that we'll have to find some somebody out of relationship and then you have the ethicist the robotics folks that like no this has got to stop I will take the other peel yeah in order to make a difference so if you could hang out for a day with a robot real from fiction movies books safely and get to pick his or her there brain who would you pick gotta say it's data data I was gonna say Rosie but I don't I'm not really interested in her brain hmm I'm interested in data's brain data pre or post emotion ship pre but don't you think it'd be a more interesting conversation post emotion ship yeah it would be drama and I you know I'm human I deal with drama all the time yeah but the reason why I went to pick data's brain is because I I could have a conversation with him and ask for example how can we fix this ethics problem right and he could go through like the rational thinking and through that he'd also help me think through it as well and so that's there's like these questions fundamental questions I think I can ask him that he would help me also learn from and that fascinates me I don't think there's a better place to end it thank you so much for talking I was an honor thank you thank you this was fun thanks for listening to this conversation and thank you to our presenting sponsor cash app downloaded use code Lex podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators if you enjoy this podcast subscribe my youtube give it five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter and now let me leave you with some words of wisdom from arthur c clarke whether we are based on carbon quan silicon makes no fundamental difference which should each be treated with appropriate respect thank you for listening and hope to see you next time you