Speaker 1: Brought to you by Toyota. Let's go places. Welcome to
Speaker 1: Forward Thinking, pay there, and Welcome Beforeward Thinking, the podcast
Speaker 1: that looks at the future and says people are strange
Speaker 1: when you're a stranger. I'm Jonathan Strickland, I'm La, and
Speaker 1: I'm Joe McCormick, and I've got a story for y'all. Alright,
Speaker 1: let's gather around the campfire. It's more of an anecodote. Actually,
Speaker 1: it's not even that anyway, here's what it is. You've
Speaker 1: built it up so much and now I'm already bound
Speaker 1: for disappointment. No please. So a while back I was
Speaker 1: writing a video episode for Forward Thinking about whether robots
Speaker 1: are going to take our jobs? And if you haven't
Speaker 1: doing that video, yeah you should go watch it. It's
Speaker 1: on YouTube. It's a great, great episode. It is. It is.
Speaker 1: But we have a spoiler for that video. Yeah, there
Speaker 1: is a spoiler. Actually this We say this in the
Speaker 1: video pretty early on. It's not the end. Yes, they will.
Speaker 1: Robots will take our jobs, will take your job, They'll
Speaker 1: take our jobs. They'll they'll take all the jobs. But
Speaker 1: in doing the research for the episode, I came across
Speaker 1: plenty of good reasons for thinking that some jobs are
Speaker 1: much much harder to automate than others. And one simple
Speaker 1: rubric for separating jobs into robot friendly and robot unfriendly
Speaker 1: is this is the job easily described in an explicit
Speaker 1: list of instructions that can be executed over and over. So,
Speaker 1: in other words, could it be something like pick up
Speaker 1: blue box, open blue box, put orange sphere in blue box,
Speaker 1: close blue box. That's easily explained, and it would be
Speaker 1: something that you could program as a list of actions
Speaker 1: for a robot that has very simple image recognition software.
Speaker 1: It really just needs to know what a blue box
Speaker 1: looks like and what an orange sphere looks like, and
Speaker 1: then you're pretty much good. Hard to touch those things
Speaker 1: that they don't shatter whatever, right, and it's it's just
Speaker 1: gonna do the same things over and over again. There
Speaker 1: aren't going to be a lot of changing external conditions,
Speaker 1: or if there are, they might not matter necessarily. Jobs
Speaker 1: like this are pretty easy to automate, and they they
Speaker 1: if if they have not already gone to machines or
Speaker 1: computer programs or robots, they probably will soon. So a
Speaker 1: lot of examples of this might be jobs today, and
Speaker 1: like data entry or data processing or jobs like telemarketing.
Speaker 1: A lot of people think that these kind of jobs,
Speaker 1: because they're so repetitive and you can make clear lists
Speaker 1: of instructions, can pretty easily be done by machines. Other
Speaker 1: jobs are very robot unfriendly. They're harder to automate because
Speaker 1: they require things that are harder to predict, Like you
Speaker 1: can't write a program that does unpredictable things. I mean,
Speaker 1: programs are pretty much by the definition of predicting. And
Speaker 1: we've talked about random number generators and how difficult it
Speaker 1: is to have a truly random number generator. Yeah. Yeah.
Speaker 1: If if you say to a robot, literally any person
Speaker 1: who exists in the world could walk through that door,
Speaker 1: how do you deal with that person going to go
Speaker 1: like and just shut down? Yeah? Yeah, yeah, So these
Speaker 1: jobs are the one The hard to automate jobs are
Speaker 1: the ones that require creativity, strategizing, reacting to unpredictable circumstances
Speaker 1: and stuff like that. And there are some jobs I
Speaker 1: thought it was interesting that sound like they fit into
Speaker 1: the first category, but they actually fit better into the
Speaker 1: second well. And there are also some that sound like
Speaker 1: they would fit in the second but seem to fit
Speaker 1: just fine the first like you mentioned telemarketing. Well, telemarketing
Speaker 1: involves having conversations with actual people, and you might think, oh,
Speaker 1: well a robot would have different would there be some unpredictability,
Speaker 1: But often in those cases there's a very specific script
Speaker 1: to follow, whether you're human or robot, and you have
Speaker 1: a very it's essentially kind of a it's a it's
Speaker 1: a very simple decision tree, right, You're trying to get
Speaker 1: the person on the line to say yes or or
Speaker 1: no in some cases, and if as long as it continues,
Speaker 1: it can keep going down that pathway. And we've even
Speaker 1: seen some interesting clever uses of natural language recognition to
Speaker 1: create situations where a person is not entirely sure if
Speaker 1: the if they're actually speaking to a human being or
Speaker 1: a robot telemarketer. Yeah, and that might be some cases
Speaker 1: where even if it is really a human, they're they're
Speaker 1: like trying to get the human to behave like a robot.
Speaker 1: So these kind of robo calls like that, that's prime
Speaker 1: territory for automation, especially also if it's low stakes, you know,
Speaker 1: because the people the bosses like aren't terrified about what's
Speaker 1: going to happen if the person being called has a
Speaker 1: bad experience. You know, it's just that I don't care, right, right,
Speaker 1: But let's take an example of something from our favorite movie,
Speaker 1: Back to the Future Part two. Right, So, in the
Speaker 1: opposite category is stuff that seems like it might be
Speaker 1: easy to automate, but that actually it would probably be
Speaker 1: really hard to automate, And like robot servers in a restaurant. Yeah,
Speaker 1: so a robot server in a restaurant, what would it
Speaker 1: have to do? It seems like you could basically come
Speaker 1: up with a simple list of instructions like take drink orders,
Speaker 1: bring drinks, take the food order, bring the food, check
Speaker 1: the happiness levels at the table, bring the check, uh,
Speaker 1: process payment, and then you're done. But actually being a
Speaker 1: server in a restaurant requires hundreds of constant little improvisations
Speaker 1: h plus more athletic nimbleness than any robot today is
Speaker 1: even close to capable of. I mean, can you can
Speaker 1: you imagine with how clumsy robots are now, something that
Speaker 1: could like clean tables and move quickly back and forth
Speaker 1: between a kitchen and a table without running into people.
Speaker 1: Keep in mind also that most robots are very very
Speaker 1: good at navigating static environments. So in other words, you
Speaker 1: program in the knowledge of what the environment is, you
Speaker 1: know how it is, and give the robot some ability
Speaker 1: to sense its environment. It can then navigate around obstacles.
Speaker 1: But in a place like a restaurant, you have a
Speaker 1: constantly shifting environment. You've got people getting up and leaving,
Speaker 1: You've got chairs that are moving. So you have a
Speaker 1: robot that has to have really good path finding technology
Speaker 1: to maneuver its way through a constantly shifting environment. That's
Speaker 1: really hard to do. Sure, but there's another factor that
Speaker 1: we haven't considered yet, which is, you know, in defensive servers,
Speaker 1: we know that you guys are not robots. Yeah, there's
Speaker 1: other stuff that you're doing than just taking the orders
Speaker 1: and bringing the stuff exactly right. And I think this
Speaker 1: might actually be the biggest problem with the idea of
Speaker 1: a robot server, which is that servers need social intelligence
Speaker 1: good ones do. Yeah, well, this might be the biggest
Speaker 1: issue of all here, because a server in a restaurant
Speaker 1: isn't just a food delivery machine. A good server makes
Speaker 1: people feel welcome, makes and feel comfortable, uses charm to
Speaker 1: like up sell drinks and specials and appetizers, can explain
Speaker 1: things about the restaurant and answer questions about the menu,
Speaker 1: explain things about the food, describe what something tastes like,
Speaker 1: and then especially can sort of like calm complaints and
Speaker 1: help people get what they want, understand what the people want,
Speaker 1: and make them feel happy. Like can you imagine, let's
Speaker 1: say you're out with your family and you know your
Speaker 1: great aunt she has a complaint about her chicken peccata.
Speaker 1: Can you imagine a robot server being able to make
Speaker 1: her feel happy and like make her feel like her
Speaker 1: complaint had been properly dealt with. I can't imagine anyone
Speaker 1: making my grain on feel happy. Well well, but especially
Speaker 1: not the same kind of software that like answers your
Speaker 1: telephone call you call the insurance company, and like that
Speaker 1: thing is what's trying to like make you fear good.
Speaker 1: Or maybe it's the chatbot that only answers answers any
Speaker 1: any message with a question I'm not happy. Why do
Speaker 1: you think you're not happy? The doctor? Yeah. So, in
Speaker 1: the context of robots taking our jobs, I think this
Speaker 1: also means that, in addition to creativity and improvisation, another
Speaker 1: type of job that will be safely human for a while,
Speaker 1: our jobs that have a strong demand for good social intelligence.
Speaker 1: So what does social intelligence mean, I mean, we we
Speaker 1: sort of gave an idea there, but how would we
Speaker 1: define it? I would say one thing is that it
Speaker 1: means something along the lines of being able to read
Speaker 1: social cues, to perceive and understand emotional states, and to
Speaker 1: intentionally manage and trigger targeted emotions in others. Right, In
Speaker 1: other words, in order that it has to be able
Speaker 1: to navigate social situations in a way that appears to
Speaker 1: be natural and does not make things worse, right, doesn't
Speaker 1: make someone feel awkward or embarrassed or ill at ease
Speaker 1: for any reason, whether because you are communicating with a
Speaker 1: and obviously artificial construct, which already for many of us,
Speaker 1: is uncomfortable. Right, Yeah, some of us We we in fact,
Speaker 1: humans are pretty flexible creatures. We can adapt fairly quickly
Speaker 1: if we're willing to, sure, sure, And and some of
Speaker 1: us I mean, I suspect many people listening to this podcast,
Speaker 1: for example, probably find it charming that the novelty of
Speaker 1: that kind of interaction, although really like like after a while,
Speaker 1: you'd be like, I just want not burned chicken cottage,
Speaker 1: And some of us might actually prefer the interaction with
Speaker 1: a robot as opposed to a human being. That's true.
Speaker 1: That's true. I have days where I'm not sure that
Speaker 1: I can do this list of things that we're talking
Speaker 1: about here that has grouped under social intenation. That's true. Well,
Speaker 1: but I mean we all have to practice our social
Speaker 1: intelligence skills all the time. Oh sure, yeah, no, this
Speaker 1: this is not something that we think. It's not something
Speaker 1: even humans are always perfect at. Right now, there are
Speaker 1: plenty of times where you might be wrapped up in
Speaker 1: something that's going on in your life and you don't
Speaker 1: pick up on social cues that otherwise you would notice
Speaker 1: right away. Um, there are plenty of times. I mean
Speaker 1: I certainly have been guilty of that because I'm I'm
Speaker 1: always wrapped up in my own mind. Uh So, you know,
Speaker 1: when we're when we're aware, and when we are capable
Speaker 1: of seeing it, then that's one thing. But machines, they
Speaker 1: don't have that innate ability at all. Right, you have
Speaker 1: to build that into machines. And now there is an
Speaker 1: entire emerging field of artificial intelligence that is dedicated to
Speaker 1: this problem, to the problem of helping machines understand human
Speaker 1: emotional states and manage them as best as possible, and
Speaker 1: sort of all the other things we think of as
Speaker 1: social intelligence, you know, impression management and and navigating complex
Speaker 1: social scenarios, not being annoying, you know, all these weird
Speaker 1: things that they don't come naturally to machine. Right. And
Speaker 1: and you know, this is important not just for robots
Speaker 1: that are specifically designed to have social interactions, but robots
Speaker 1: that are just going to be around humans. You know,
Speaker 1: they're especially consumers, right because you know, people robot industry
Speaker 1: people are kind of used to having to program a
Speaker 1: robot by typing code into a thing, you know. But
Speaker 1: but consumers, Yeah, and it kind of and it may
Speaker 1: be that the robots that you, as a consumer encounter,
Speaker 1: it may be that there's no direct interaction, but they
Speaker 1: still those robots still need to have that social intelligence
Speaker 1: to understand how to navigate through while being as unobtrusive
Speaker 1: as possible. It's it's one of the many things that
Speaker 1: we have to take into consideration as robots take an
Speaker 1: increasingly more prominent role in our lives, along with the
Speaker 1: idea that the robots have to be design in such
Speaker 1: a way that they are not likely to cause harm
Speaker 1: to people through their normal operations. I mean, this is why,
Speaker 1: like we've talked about before, with big industrial robots. Typically
Speaker 1: there are huge safety rails all around them, because these
Speaker 1: are just machines that do the same set of actions
Speaker 1: over and over again. And if you let a team
Speaker 1: full of preschoolers run around and you get a bunch
Speaker 1: of preschoolers welded to a metal wall, it's not good.
Speaker 1: You don't want that. So this we're we're talking about
Speaker 1: the social equivalent of that same thing. You don't You
Speaker 1: don't want the social equivalent of welding preschoolers to a wall.
Speaker 1: I'm not sure what that looks like, but I kinda
Speaker 1: I kind of want. Can someone please make us I'll
Speaker 1: take you to my next family reunion. You will be
Speaker 1: able to experience it. No here, I think here's the
Speaker 1: the real world takeaway. We're gonna have robots in our homes. Yeah,
Speaker 1: I mean, that's that's pretty clear. We aready. Yeah, we
Speaker 1: already might have some roomba or something like that. More
Speaker 1: and more we're gonna be incorporating robotics and artificial intelligence
Speaker 1: into our home life. And it actually matters that these
Speaker 1: things are not causing emotional stress and annoyance, like making
Speaker 1: our lives more unhappy by not knowing how to behave themselves. Yeah,
Speaker 1: it's a great point. And so there are entire research
Speaker 1: departments dedicated to this particular aspect of artificial intelligence, And
Speaker 1: in fact, there's one that's right down the road from it,
Speaker 1: right here at Georgia Tech. They've got a socially Intelligent
Speaker 1: Machines Lab. Yeah. We'll talk about one of the robots
Speaker 1: that they've worked on a little bit later, but I've
Speaker 1: had a chance to visit that particular lab. Yeah, it's
Speaker 1: pretty darn cool. Guess. Don't mean to brag, but it's
Speaker 1: pretty neat. Even as even as a University of Georgia graduate,
Speaker 1: I can appreciate this particular Georgia Tech lab. Uh. So
Speaker 1: let's talk a little bit about what it means for
Speaker 1: robots to actually possess social intelligence. You touched on this, Joe,
Speaker 1: you were talking about the ability to pick up on
Speaker 1: those social cues. So I would I would say that
Speaker 1: a socially intelligent machine has to be able to observe, analyze,
Speaker 1: and respond to humans accurately and within the proper context
Speaker 1: of the situation. So one example, and I've seen this
Speaker 1: as particularly examples in Japan, robots that are part of
Speaker 1: a hotel check in phase. You come in and you
Speaker 1: you need to get your room. You would want that
Speaker 1: experience to be efficient and pleasant and probably not reliant
Speaker 1: on too many assumptions because that could get socially awkward
Speaker 1: depending upon what the nature of the hotel visit could be. Right, Sure,
Speaker 1: you wouldn't want, for example, you know, yeah, sir, that
Speaker 1: you have a lovely daughter, this is my wife. That
Speaker 1: could be awk kind of thing. Yes, that's that's one
Speaker 1: of the team or examples I could get, but yes,
Speaker 1: but in context is really important. So let's say here's
Speaker 1: another example. I've actually, you know, you we've talked about.
Speaker 1: I'm not sure if we've talked about on this podcast,
Speaker 1: but there was a design for a flying drone that's
Speaker 1: meant to encourage joggers to run. It was to keep
Speaker 1: pace with joggers so that they have they feel like
Speaker 1: they have a running buddy. So you know, Now, that's
Speaker 1: a simple version of a robot. But imagine that we
Speaker 1: have a more advanced one that actually gives verbal encouragement
Speaker 1: so that you can continue to run. Now, let's imagine
Speaker 1: that said robot veers off the path and into a
Speaker 1: memorial service at a cemetery. I think saying you can
Speaker 1: do it, get on up there, keep on moving at
Speaker 1: a memorial service that, Yeah, that might might not go
Speaker 1: over so well in the social situation. That is a
Speaker 1: memorial service. So when we're talking about social intelligence, we're
Speaker 1: talking about not just responding within the situation the robot
Speaker 1: was intended for, but in broader situations. Sure. And I
Speaker 1: think also side note, this means that we need to
Speaker 1: teach all robots in the future about graveyards and funeral practices.
Speaker 1: I think why they're cool. Yeah, now I'm just seeing
Speaker 1: a bunch of robots listening to the Smiths, and the
Speaker 1: robots says, hey, baby, let's go hang out in the graveyard.
Speaker 1: I'm feeling better and better about the lyric I picked
Speaker 1: for the beginning of this episode. Okay, So, in addition
Speaker 1: to understanding context, I think another crucial part of social
Speaker 1: intelligence is the ability to incorporate new information right because
Speaker 1: to right, Like, when we interact with people, we don't
Speaker 1: treat everybody the same way. I mean because they not
Speaker 1: everybody wants to be treated the same way you treat
Speaker 1: everybody else. You learn different ways to interact with different
Speaker 1: people based on what your relationship with them is, and
Speaker 1: what their preferences are. Some people like very jokey interactions,
Speaker 1: some people are a little more business like. Yeah, there's
Speaker 1: entire fields dedicated to this as well. And it's interesting
Speaker 1: because the law of the earning behaviors I've seen have
Speaker 1: concentrated first on something a little simpler, because when we
Speaker 1: start getting into social interactions, that's a really complex and
Speaker 1: and chaotic field. So, I mean, if you feel stress
Speaker 1: in social situations like social anxiety, a lot of the
Speaker 1: stress you're probably feeling is it has to do with
Speaker 1: the complexity of the social interactions that we have. In
Speaker 1: your fear that you're not meeting expectations, writing, unsure that
Speaker 1: the choices that you're making are are good choices. Right, yeah, now,
Speaker 1: and that's a great point. Now, obviously the robots aren't
Speaker 1: going to be experiencing social anxiety, but they could end
Speaker 1: up that we know of, but they could certainly encourage
Speaker 1: it in other people if they the robots are not
Speaker 1: behaving in a way that the people were expecting. If
Speaker 1: they have said something and the robots seems to behave
Speaker 1: in a in a completely counterintuitive way, that could really
Speaker 1: cause some issue. Oh yeah, well, I was just trying
Speaker 1: to communicate the complexity like, Yeah, us humans who are
Speaker 1: pretty good at social interaction have enough trouble with it
Speaker 1: that sometimes we can get anxiety about it. How So,
Speaker 1: a lot of the learning I've seen has been oriented
Speaker 1: to teaching a robot to perform a series of tasks
Speaker 1: by performing them for the robot. Actually the one that
Speaker 1: there's one in Georgia Tech that does this where you
Speaker 1: could have a robot and it goes into observation mode
Speaker 1: and watches what you do, so you could pick up
Speaker 1: let's say that you've got, you know, kind of going
Speaker 1: back to that example of the sphere in the box.
Speaker 1: Let's say you've got a sphere on a desk in
Speaker 1: a box in the desk, and you open up the box,
Speaker 1: you pick up the sphere, you put the sphere in
Speaker 1: the box, you close the box. The robot will observe
Speaker 1: this and then be able to repeat those steps. And
Speaker 1: even if if you've designed the robot properly, it might
Speaker 1: be able to ask questions like does it matter what
Speaker 1: how I pick up the this thing? Does that matter?
Speaker 1: Does it matter how I close the box doesn't? If
Speaker 1: it's four flaps, does it matter? Or which flaps are
Speaker 1: closed first? Is there a sequence? Right, if it were
Speaker 1: a cube that you were putting inside the box instead
Speaker 1: of his sphere, doesn't matter which side of the cube
Speaker 1: is facing up perfect exactly right. So that's that's a
Speaker 1: building block, not to make it a weird, stupid pun,
Speaker 1: but that's a building block for the kinds of interactions
Speaker 1: where a robot starting to get into more complex situations,
Speaker 1: such as, this person is exhibiting behaviors that indicate that
Speaker 1: they are in a happy mood. So what is the
Speaker 1: appropriate response for this particular person when they are in
Speaker 1: a happy mood. Maybe it's playing that person's favorite upbeat
Speaker 1: song because it's going to enhance that happy mood. And
Speaker 1: then that's what the robot ends up doing. Uh, these
Speaker 1: are you know, it's going to take these these basic
Speaker 1: steps before you get into something so complex. Is all right,
Speaker 1: Now we've got two people, two people the robot has
Speaker 1: to interact with. If we're talking about a home robot,
Speaker 1: it might have profiles for each member of the family,
Speaker 1: for example, but it knows that person number two is
Speaker 1: not really into music, so playing songs aren't going to
Speaker 1: have that same emotional effect as for the first person,
Speaker 1: So it may have to build an entirely different set
Speaker 1: of interactions, just as we humans would kind of intuitively
Speaker 1: know from our interactions, like what you know works and
Speaker 1: doesn't work with the people in our lives. And you
Speaker 1: start to realize, Wow, this is this is tough. This
Speaker 1: is a non trivial challenge in artificial intelligence. Absolutely. Let's
Speaker 1: talk about some of the teams and some of the
Speaker 1: robots that are that are taking these challenges head on. Sure. Yeah,
Speaker 1: so we've got a collection of different robots. These are
Speaker 1: These are mainly robots designed specifically to have social interactions
Speaker 1: with humans, and lots of we should say that lots
Speaker 1: of computer programs and robots have some elements of this. Yeah. Um,
Speaker 1: I mean typically you're not going to be interacting with
Speaker 1: a robot that's just designed to be social, because what's
Speaker 1: the point other than a novelty. I mean, typically social
Speaker 1: intelligence is a feature of a robot that intended to
Speaker 1: do something else. Yeah, except for I guess therapy, but yeah,
Speaker 1: that's true. Therapy, butts would be a great example. Yeah.
Speaker 1: I started to think that in some of these, some
Speaker 1: of these cases, we're heading toward a future like in
Speaker 1: future rama, where we have robots built to be hoboes
Speaker 1: or gamblers or whatever, and you think, why would anyone
Speaker 1: ever build a robot, But we are doing that. Yeah.
Speaker 1: So one robot that I actually watched this adorable video
Speaker 1: earlier today was this robot called Gibo. Had you heard
Speaker 1: about this one before? I have? I had seen pictures.
Speaker 1: I had not seen the video or read about Gibo,
Speaker 1: but I had seen photos of Gibo before. Okay, so
Speaker 1: this is nothing super complex. Gibo is just supposed to
Speaker 1: be a social robot that's really designed as a kind
Speaker 1: of around the house helper. So imagine kind of an
Speaker 1: embodied serie in a way. It can track faces and
Speaker 1: recognize individual household members, take pictures, record voice reminders, um
Speaker 1: and do a lot of the stuff you might have
Speaker 1: like apps on your smartphone. It can even do things
Speaker 1: like um like sort of like a similar feature as FaceTime,
Speaker 1: where you are in one place, one of your family
Speaker 1: members is somewhere else they are using their smartphone, and
Speaker 1: then Gibo just projects their face onto its face. So
Speaker 1: you have a a direction to look in and it's
Speaker 1: an actual physical thing. It's not something you're holding in
Speaker 1: your hand. You're looking down at Gibos quote unquote face,
Speaker 1: which is really kind of a round screen. Yeah, it's
Speaker 1: this like it's this kind of friendly. I yeah. And
Speaker 1: it has a camera in it so it can it
Speaker 1: can quote unquote see that allows it to do the tracking.
Speaker 1: Now it doesn't like walk around the house or anything.
Speaker 1: It's sort of on a stationary base. But you could
Speaker 1: pick it up and move it around with you a
Speaker 1: little more than five pounds, I think. And the thing
Speaker 1: about this is nothing about this robot is like crazy
Speaker 1: mind blowing, you know. It's not like doing anything all
Speaker 1: that weird. It's sort of a cuddly smartphone or cuddly
Speaker 1: series kind of thing. It you can talk to it,
Speaker 1: it'll talk back to you. It tries to, uh to
Speaker 1: be friendly and fit in around the house. Right. So
Speaker 1: it's supposed to kind of provide a lot of those
Speaker 1: features that you would find in a smartphone, but in
Speaker 1: a way that is more socially interactive. Sure. Sure that's
Speaker 1: and that's a little bit more relatable because your smartphone.
Speaker 1: Although I think that we all have certain attributes that
Speaker 1: we give it, we don't really you know, name them.
Speaker 1: And and no, I'll never name that phone. It did
Speaker 1: phone phone. Uh so the next one we wanted to
Speaker 1: talk about is Pepper Okay, So Pepper is According to
Speaker 1: the company that makes it, Aldebron is the first humanoid
Speaker 1: robot designed to live with humans. And it's a conversational robot,
Speaker 1: and it's supposed to detect and react to emotions, kind
Speaker 1: of like what we're talking about earlier. It can move
Speaker 1: about in its own and that's about all I can
Speaker 1: do is have conversations move around autonomously, so you don't
Speaker 1: have to direct it. Um and uh. It watches your
Speaker 1: facial expressions and your body language for social cues to
Speaker 1: your emotional state, and it pays attention to your word
Speaker 1: choice to try and get a handle on what kind
Speaker 1: of mood you might be in. But so I guess
Speaker 1: essentially builds an index of words that you are more
Speaker 1: likely to use when you are angry, perhaps of the
Speaker 1: four letter variety. Huh yeah. But it is meant to
Speaker 1: have these social interactions and responses so that it has
Speaker 1: these these appropriate responses for whatever mood you happen to
Speaker 1: be in. You know, I hate to sounds cynical, but
Speaker 1: I wonder to what extent, especially early versions of these
Speaker 1: kinds of robots are going to be again, like Sirie,
Speaker 1: not in what they do, but in how people treat them,
Speaker 1: because I can't remember the figure, Like some significant percentage
Speaker 1: of what people say to Siri is just profanity, Like
Speaker 1: they're just they think it's funny, you know, like what
Speaker 1: will series say if I tell her to do this
Speaker 1: rude thing? You know? My favorite was serie where can
Speaker 1: I Hide a body? And the response was the nearest
Speaker 1: quarry is three? Like that is amazing. Yeah, well, you know,
Speaker 1: it's that novelty factor before you get really used to
Speaker 1: something and before something works extremely well. I think that
Speaker 1: we're gonna be treating these robots like like robots, and
Speaker 1: and you know, it's like playing a text based adventure
Speaker 1: and just like typing in weird things just to see
Speaker 1: if the programmers thought, yeah, to put inside. And then
Speaker 1: we reach we'll reach the point where we'll get more
Speaker 1: and more movies and this is already the case, but
Speaker 1: we'll get more and more movies that give us an
Speaker 1: emotional attachment to robots. So we'll see that more and
Speaker 1: more in the pop culture, and then gradually the technology
Speaker 1: will also reach that same level where we will start
Speaker 1: to have emotional attachments to these robots beyond the what
Speaker 1: you might call superficial ones that we have now, Like
Speaker 1: there are people who if they're if their roomba were
Speaker 1: to get damaged, would feel genuine emotional stress about that,
Speaker 1: not not just related to I need to replace my room, Bob,
Speaker 1: but more like a member of the family has been
Speaker 1: hurt kind of thing. Yeah. Yeah, absolutely, And uh, I
Speaker 1: think that Jarvis from the Iron Man movies is a
Speaker 1: is a really good example of that. And there is
Speaker 1: a robot called Emo Spark that was kind of reminding
Speaker 1: us in the research of of that sort of Jarvis character. Yeah,
Speaker 1: so this isn't really a robot. Yeah, this is more
Speaker 1: like an artificial intelligence that lives inside a cube. So
Speaker 1: because the cube is a cube, you could set it
Speaker 1: on a shelf and but it's a cube, open it
Speaker 1: up and let the cinambytes out. Cinnabonn have a little
Speaker 1: home or Simpson moment. Uh. But no, it is like
Speaker 1: Jarvison that it feels almost like it's a disembodied artificial
Speaker 1: intelligence that can inhabit a space within your home. So,
Speaker 1: so imagine you've got this cube. The cube is what
Speaker 1: contains the you know, it's the hardware that contains the
Speaker 1: software that runs this Emo Spark robot. Uh. The Emo
Speaker 1: Spark robot can sense and interact with its environment through
Speaker 1: things like Bluetooth and WiFi. It also uses webcams and
Speaker 1: microphones and a connection to your smartphone. So this is
Speaker 1: what gives it that that window to the world, and
Speaker 1: it can recognize people. It can look at facial cues
Speaker 1: again to determine moods. It actually maps your face against
Speaker 1: eighty different points and tries to figure out your mood
Speaker 1: based upon your expression. So, um, yeah, this is kind
Speaker 1: of an interesting design. If you want to take a
Speaker 1: look at the Emo Sparks, it does look like this
Speaker 1: kind of you know, uh, Cino byte meets tron cube thing,
Speaker 1: and uh yet you know, it's it's one of those
Speaker 1: that could potentially have this sort of natural interaction. You know.
Speaker 1: We we are seeing this kind of stuff in the
Speaker 1: homes already with things like like the Xbox and PlayStation
Speaker 1: controllers that allow for voice control. So this is kind
Speaker 1: of the next step when where it goes beyond a
Speaker 1: passive system that's trying to recognize voice commands and then
Speaker 1: respond to them and have one that can actually have
Speaker 1: some form of communication back to the person who is
Speaker 1: issuing the commands. In the first place, so it becomes
Speaker 1: not just a list of commands and then responses, but
Speaker 1: in actual communication, a conversation that leads to whatever the
Speaker 1: outcome the person hoped for, you know, was in mind. Yeah, uh,
Speaker 1: And I wanted to talk for a second going back
Speaker 1: to the stuff that they're working on at Georgia Tech
Speaker 1: in their Socially Intelligent Machines Lab, because they're they're kind
Speaker 1: of working on more the the building blocks of a
Speaker 1: more practical household robot and how people are going to
Speaker 1: be interacting with that, because part of creating and ease
Speaker 1: of interaction between consumers and robots is going to be
Speaker 1: making robots that can learn new tasks with a minimal
Speaker 1: effort on behalf of the owner, right, right, So you
Speaker 1: don't have to sit at a terminal and type lines
Speaker 1: of code so it can open up a can of
Speaker 1: cat food. Yeah. Yeah, And kind of the first half
Speaker 1: of that was what we were talking about earlier with
Speaker 1: with that unsupervised learning, wherein the robot is watching a
Speaker 1: human completed task, and you know, so even if it
Speaker 1: doesn't have any idea what the objects in this task are,
Speaker 1: you know, it doesn't know what if it needs to
Speaker 1: set a table. It doesn't know what cups and plates
Speaker 1: and food are, but it can be taught to know
Speaker 1: what those things look like where to place them in
Speaker 1: a table setting. Um right, that that plates come first,
Speaker 1: food comes later. Otherwise people are unhappy, right right, Sure,
Speaker 1: exactly that kind of stuff. And when you break it
Speaker 1: down into those kind of steps, it becomes a relatively
Speaker 1: easy thing for robot to learn how to do. But
Speaker 1: that's really only half of the equation, because the second
Speaker 1: half of of how humans naturally learn how to do
Speaker 1: stuff is being able to ask questions of their teacher
Speaker 1: and so and that that's what they're calling active learning
Speaker 1: in robot circles, and it's it's letting the robot ask
Speaker 1: questions of the human teacher while it's being presented with
Speaker 1: this new task that it's watching. But that's a trickier
Speaker 1: question you might expect, like having a robot know how
Speaker 1: to ask the question to figure out what it needs
Speaker 1: to figure out. Right, it comes naturally to us, but
Speaker 1: it doesn't necessarily come naturally to machine. Right, So sure
Speaker 1: you have to you have to teach a robot when
Speaker 1: it's actually permissible to ask a question. And and furthermore,
Speaker 1: how to ask a good question, what does the question mean?
Speaker 1: And then what does the answer mean? Like to to
Speaker 1: ask a good question, you have to understand what relevant
Speaker 1: information is to know that you need it right. Yeah,
Speaker 1: and and in fact, the examples the robot were specifically
Speaker 1: talking about is called Simon, the robot um But yeah,
Speaker 1: and I got to see Simon. That Simon was the
Speaker 1: one I was talking about. Specifically, I got to see Simon.
Speaker 1: Uh didn't get to see Simon really in in full
Speaker 1: um in full robot mode. But I had a great
Speaker 1: conversation with Henrik Christensen, who is the head of robotics
Speaker 1: over a Georgia Tech and he was telling me all
Speaker 1: about this approach. And it's so interesting the idea that
Speaker 1: the robot can start to build this kind of of database,
Speaker 1: this index of information of the various things in its environment,
Speaker 1: the relationships between those things. Uh we which ones are
Speaker 1: meant to be used in certain ways. It's it's learning
Speaker 1: in a similar way to the way humans learn, but
Speaker 1: it's but it's already got a huge step up and
Speaker 1: that it's got a basic grammar syntax vocabulary that it
Speaker 1: can follow. It doesn't have to learn the language. It
Speaker 1: just has to learn, you know, and has to be
Speaker 1: able to learn how to interact with its environment. And granted,
Speaker 1: even that is going to be limited based upon what
Speaker 1: the programmers anticipate. Right there may be and in fact,
Speaker 1: there will be situations that are unique to every home
Speaker 1: that a programmer could not anticipate. And in in some cases,
Speaker 1: I'm sure there will be times where it will be
Speaker 1: very difficult to explain to the robot what something is for,
Speaker 1: or how it's used, or why it's there. It will
Speaker 1: be tricky and um, you know. The the question then
Speaker 1: is how do you address those those outliers, things that
Speaker 1: are outside the normal experience. How do you explain into
Speaker 1: the robot how to use your furby? Why are you
Speaker 1: explaining that to your robot? I mean, other than the
Speaker 1: fact that that would be adorable. I just okay, I
Speaker 1: just answered my own question. No, now I'm thinking about it,
Speaker 1: and I totally want a robot. The robot in Ferbie
Speaker 1: are plotting against you. They're having conversations deep into the night.
Speaker 1: But but so yeah, this this lab at Georgia Tech
Speaker 1: is laying some of this really cool groundwork, um for
Speaker 1: for you know, it sounds like a lot of these
Speaker 1: other robots are are kind of fun, but aside from
Speaker 1: the interesting fact that they existed there there may be
Speaker 1: moving towards something like being a therapy bot or being
Speaker 1: able to interact with the human uh, doing household chores
Speaker 1: and stuff like that. But I mean, yeah, yeah, yeah,
Speaker 1: I mean all the pieces are kind of out there. Yeah,
Speaker 1: I think all these are are sort of making steps
Speaker 1: in the right direction. Though at the same time, as
Speaker 1: impressive as all this is, we recognize how big the
Speaker 1: gap is between this and like Rosie from the Jetsons. Yeah, yeah,
Speaker 1: the best socially intelligent robots today are nothing like a human.
Speaker 1: And another question is do we want them to be? Yes?
Speaker 1: Like if we so you say yes, yes, I don't know.
Speaker 1: I I think the question might be, um, should socially
Speaker 1: intelligent robots be like well mannered humans or should they
Speaker 1: be a different kind of entity? No? No, I I personally, Uh, well,
Speaker 1: I don't think I would not define what a socially
Speaker 1: intelligent robot should or should not really be like as
Speaker 1: much as I joke about it. But well, no, I
Speaker 1: mean I know we're not like setting the rules. I
Speaker 1: guess what I'm asking is what do people what? What
Speaker 1: do most people really want. Yeah, yeah, I mean I
Speaker 1: think that I would be creeped out by something trying
Speaker 1: to interact with me as a human or as it
Speaker 1: thinks or was programmed to think that a human would
Speaker 1: would interact. You know. I think that it may be
Speaker 1: that we define like a subset of behaviors that we
Speaker 1: expect from and are comfortable with as far as a
Speaker 1: robotic entity is concerned. So things that you know, these
Speaker 1: are the kind of interactions that I think will be fine.
Speaker 1: They're very straightforward. Uh, you know, outside of things like
Speaker 1: the robots that are meant for therapy or of of
Speaker 1: one nature or another, those obviously you need to have
Speaker 1: more of a kind of comforting approach. But for robots
Speaker 1: that we're having interactions with on a daily basis, Like
Speaker 1: if it's a robot that, for example, Uber has famously
Speaker 1: invested a lot of money in autonomous cars, you would
Speaker 1: want that interaction to be pretty smooth and probably pretty quiet.
Speaker 1: If I know most people who have complained about Uber,
Speaker 1: it's that. Listen, when I get a when I get
Speaker 1: a newber car, I don't want you talking to me.
Speaker 1: I just want you to take me to the place
Speaker 1: where I wanted to go, and then I want to
Speaker 1: get out of the car, and then I want to
Speaker 1: be on my married little way. Um, don't remind you
Speaker 1: that you're a human. See, I don't have that particular interaction.
Speaker 1: I'll talk if they want to talk, but I don't
Speaker 1: want to initiate conversation because I figure this is someone
Speaker 1: who interacts. I can hardly believe that about you, Jonathan.
Speaker 1: It's once in a while I'm able to be considerate
Speaker 1: of other human beings. But all right, but but this
Speaker 1: is a point, right that where where in this particular
Speaker 1: context where Uber would have a Thomas Cars, which are
Speaker 1: technically robots. I mean, that's essentially a robot. How do
Speaker 1: how what kind of social intelligence do those robots need
Speaker 1: in order to be able to uh do their their
Speaker 1: job and do so in a way that is the
Speaker 1: most satisfying experience to the customer. Well, I've got an
Speaker 1: analogy for household robots and whether or not we should
Speaker 1: expect their social intelligence to be like that of humans
Speaker 1: or to be a different kind of thing. How about dogs?
Speaker 1: I mean, we love dogs, but you don't. There's the
Speaker 1: difference between a well behaved dog and an ill manner
Speaker 1: badly behaved dog. But a well mannered dog doesn't act
Speaker 1: like a human. It's just a different kind of vinity.
Speaker 1: And I wonder if well mannered robots we would expect
Speaker 1: to be just a different kind of thing than humans.
Speaker 1: I think. I think it will also depend on the
Speaker 1: form factor, Like, if the robot is a humanoid robot,
Speaker 1: would we expect it to have more human like traits?
Speaker 1: Oh yeah? Oh man, a humanoid robot that acted more
Speaker 1: dog like, well not necessarily dog catlike would be pretty awful.
Speaker 1: But well, well, but no, no. I I was thinking
Speaker 1: about that too, and I'm I'm not sure. I'm not
Speaker 1: sure how comfortable I would be giving a robot any
Speaker 1: orders in my house, Like I I don't know, It's
Speaker 1: it's a very basic thing that I'm not sure if
Speaker 1: I could, in good conscience say, hey, robot, go make
Speaker 1: me some toast. I've got this really important Facebook articles. Well,
Speaker 1: when you put bread in a toaster, do you ask
Speaker 1: the sister nicely to toast your bread or do you
Speaker 1: just push the button and walk away through that that
Speaker 1: toaster is just a slave to your demands. I'm just saying, like,
Speaker 1: but I can see what you're saying in terms of
Speaker 1: of the emotional situation, like if it were too human one,
Speaker 1: I certainly wouldn't want a robot to do my bidding
Speaker 1: that was indistinguishable from a human, because I would feel
Speaker 1: like I was ordering a human around, which I mean
Speaker 1: that would be creepy. Uh. To be more serious though,
Speaker 1: going down this this pathway of of you know, let's
Speaker 1: let's get a little philosophical, it's also possible that we
Speaker 1: could have these very socially interactive robots that people would
Speaker 1: feel comfortable talking to and confiding in in ways that
Speaker 1: they might not with another person. Particularly if there's like
Speaker 1: a problem that's weighing on their mind that they want
Speaker 1: to express, but they don't feel comfortable talking about it
Speaker 1: to anybody in their circle. They're they're support group, they
Speaker 1: might want to talk to a robot. Which if that happens,
Speaker 1: and I assume it will happen, the next logical thing
Speaker 1: that will happen is people will design robots specifically to
Speaker 1: get information from folks. Uh sure, sort of like a
Speaker 1: monitor your children, Barbie, yeah, or or you know uh,
Speaker 1: or spy upon your employees to find out who's actually
Speaker 1: leaking corporate secrets to your So you plant a robot
Speaker 1: employee among them that sits at the lunch table. Know,
Speaker 1: all you have to do is you work at a
Speaker 1: big company, and and everyone at that company is told, Hey,
Speaker 1: guess what, we're making this awesome robot that's gonna help
Speaker 1: people at home, and everyone who works here gets a
Speaker 1: free one. Tell us what you really think about the boss.
Speaker 1: I'm just saying, like free robots, Like if if if
Speaker 1: we were offered a free robot, I'd likely be one
Speaker 1: of the people saying, I will take that free robot.
Speaker 1: Can this free robot carry me the way home? Because
Speaker 1: I don't know that I can carry the robot home,
Speaker 1: and one of us is going to be doing a
Speaker 1: lot of the work, so I wanted to be the
Speaker 1: robot in this case, you could call an uber. But
Speaker 1: at anyway, Yeah, get that autonomous car come up and
Speaker 1: let me my robot buddy, and then I'm outnumbered. I've
Speaker 1: got two. But yeah, the point being that that, I
Speaker 1: mean there are actual people who have have brought this up,
Speaker 1: who have written papers on this subject. The idea that
Speaker 1: if we get to a point with socially intelligent robots
Speaker 1: where we feel comfortable enough to confide in them in
Speaker 1: order to receive comfort. Then there is already the incentive
Speaker 1: to build robots specifically to gather information that might you
Speaker 1: might want to remain private. So, in other words, if
Speaker 1: people do this behavior, and if there's a way to
Speaker 1: to profit from that behavior, someone is going to act
Speaker 1: upon that. That is perfectly logical in the way our
Speaker 1: world works. It's not the bright, beautiful future that I
Speaker 1: want where you know, you can have these interactions then
Speaker 1: be be assured that they're between you and you're the
Speaker 1: robot that you're talking to. Um, well, yeah, yeah, I
Speaker 1: mean eventually you've just got you've just got do android
Speaker 1: stream of electric sheet of scenario where you've got probably
Speaker 1: a robot interrogating probably another robot. Right. That was this
Speaker 1: turtle that I came across on my way here. I
Speaker 1: just left it there in the middle of the belt line.
Speaker 1: Well no, first you've turned it over on its back. Yeah.
Speaker 1: It was odd too, because you would have thought it
Speaker 1: would have been a tortoise, not a turtle. But it
Speaker 1: was definitely a turtle. That was kind of strange. There's
Speaker 1: pawns along the belt line, there are there are all right, So, uh,
Speaker 1: socially intelligent robots is going to continue to be a thing.
Speaker 1: I am curious. Do you guys have any guests like, like,
Speaker 1: I know this is putting you on the spot, but
Speaker 1: like a prediction of when we will get to a
Speaker 1: point where a robot will be socially intelligent enough to
Speaker 1: interact in a a typical social setting. Let's say I
Speaker 1: don't know a cotillion, oh for years, let's play it.
Speaker 1: Uh no, Um, I'm not sure. I think I honestly, Oh,
Speaker 1: technology is changing so fast these days. Well, I'm tempted
Speaker 1: to say some huge number, like like fifty to a
Speaker 1: hundred years. I think my answer would play on the
Speaker 1: same thing I was just talking about a few minutes ago.
Speaker 1: It would be the difference between something that's very convincingly
Speaker 1: human versus something that's just very socially pleasant and acceptable
Speaker 1: but not necessarily human. It's its own paradigm, it's its
Speaker 1: own thing. I think the latter is going to happen
Speaker 1: much sooner. In fact, might argue that the latter already
Speaker 1: exists and it's just going to be refined. Yeah, I'm
Speaker 1: going with fifteen years. That's when we're gonna see robots
Speaker 1: capable of interacting in social situations as well as your
Speaker 1: typical human wow, I believe that it could happen. I mean,
Speaker 1: I'm I'm dubious. It seems like a lot of I mean,
Speaker 1: we're we're coming a long way in terms of natural
Speaker 1: language processing and all of that, but it's it's so much.
Speaker 1: Mostly I'm confident that by no one's going to listen
Speaker 1: to this episode in fact check me. So I'll be
Speaker 1: all right. I feel pretty confident about that. That's a
Speaker 1: good way to play the game. It's a fairly it's
Speaker 1: a fairly arbitrary number, not prices, right, You're just like,
Speaker 1: as long as you don't yeah, I think, um, I
Speaker 1: think yeah, I think that. Uh. I think that we
Speaker 1: are making advances in the field of artificial intelligence at
Speaker 1: an incredible rate, and that I think that rate is
Speaker 1: likely to stay steady. Now, we should point out that
Speaker 1: these advances aren't on a path like Moore's law, right
Speaker 1: they are, they are far below the path of Moore's law.
Speaker 1: But I do think that advances in various fields are
Speaker 1: pointing the way to incredible achievements in artificial intelligence. And
Speaker 1: I think that by having a robot capable of having
Speaker 1: a social interaction that would be more or less indistinguishable
Speaker 1: from a typical person. It's ambitious, but I think achievable. Uh.
Speaker 1: And if rolls around and it turns out that we
Speaker 1: had hit some obstacles we could not have anticipated. Demand
Speaker 1: money I want. I wanted my socially my socially acceptable robot,
Speaker 1: but I will accept money. It's place that's almost always
Speaker 1: going to be the case, actually, Joe, I I like,
Speaker 1: I like our range of of optimism. Yeah. Yeah, And
Speaker 1: you know again, I think it's always important you always
Speaker 1: have to acknowledge the fact that there are challenges. If
Speaker 1: you ignore that there are challenges, you're pretty much guaranteed
Speaker 1: to fail. You need to acknowledge the challenges so that
Speaker 1: you can figure out ways to overcome them on your
Speaker 1: quest to whatever your goal happens to be, in this case,
Speaker 1: creating a socially intelligent robot. Joe, you came up with
Speaker 1: the idea for this podcast. I think it was a
Speaker 1: lot of fun. It was. It was entertaining and fun
Speaker 1: to research the various types of robots that are in
Speaker 1: this field. So thank you, Thank you guys. Now we
Speaker 1: all start getting tons of great suggestions from you listeners
Speaker 1: out there. We want those to keep coming in because
Speaker 1: we really love the fact that you're guiding the conversation.
Speaker 1: You're you're part of the conversation. Keep up the great works.
Speaker 1: Send us your suggestions for future episodes or even comments
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