Embedded - 525: Some Sort of Metal

Episode Date: May 14, 2026

Dr. Tom Williams spoke with us about robots, ethics, teaching, and books. Then we talked about mines, umpires, water, and more books. Tom is the author of Degrees of Freedom: On Robotics and Social Justice (free at MIT Press: Degrees of Freedom: On Robotics and Social Justice!).  As part of the discussion, we talked about some other books and media: Nonfiction: Sex, Race, and Robots: How to Be Human in the Age of AI by Ayanna Howard (Embedded episodes 367: Data of Our Lives and 207: I Love My Robot Monkey Head) Embodied AI Safety: Reimagining safety engineering for artificial intelligence in physical systems by Philip Koopman (related Embedded episode 514: Just Turn Off All the Computers)  Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence by Kate Crawford Waki Kamino's research on robot umpires: Beyond Accuracy: Rethinking the Value of AI in Decision-Making Through Baseball's Automated Ball-Strike (ABS) System (or see the summary in the Cornell Chronicle: AI on deck: assessing impact of MLB's new ball-strike system) Fiction: A Psalm for the Wild-Built by Becky Chalmers  Platform Decay (The Murderbot Diaries Book 8) by Martha Wells (Embedded episode 432: Robot Bechdel Test)  Death of the Author by Nnedi Okorafor The Good Place TV show was mentioned a few times as an introduction to ethics for people who prefer their education crammed with amusement. Critical Role web series There was a discussion about water use in AI. Tom recommends Why is Everyone So Wrong About AI Water Use?? while Elecia unsurprisingly mispronounces synecdoche.  Tom is a computer science professor at the Colorado School of Mines where he runs the Mines Interactive Robotics Research Lab (MIRROR lab). See also Tom's page on mines.edu. The final quote is from an essay written by Karel Capek and translated to English in in The Man Who Coined the Word "Robot" Defends Himself - IEEE Spectrum.  

Welcome to Embedded. I am Elysio White alongside Christopher White. Our guest this week is Dr. Tom Williams and we're going to talk about robotics. But maybe not in the way you think or I think. I'm not sure what to expect beyond robotics. Hi, Tom. Thanks for joining us today. Thank you for having me. Could you tell us about yourself as if you were visiting the Harvey Mudd College alumni reunion? I mean, why? Yes, absolutely. Yeah, dear alumni of Harvey Mudd, thank you so much for inviting me out to California.

I'm Dr. Tom Williams. I am a social roboticist at the Colorado School of Mines. That means I study how people interact with social robots and how we can design robots to interact more effectively and ethically with humans. and my background is I'm a cognitive scientist by training. But you teach computer science? I do. I do. So my PhD is in computer science and cognitive science. So it's sort of the intersection of computer science, psychology, philosophy, linguistics. So I like to say this gives me a license to dabble. So I do teach in the computer science department. I teach computer science

and robotic students. But the courses I teach are at the intersection of those areas and psychology, design, philosophy, and sociology. I did some education in computer, or sorry, computer science and cognitive psychology. And you said cognitive science. Are those the same? Yeah. So cognitive science is sort of the blend, the or the intersection of those different areas. And so if you go to a cognitive science conference, it will be a lot of, it will be a lot of cognitive psychologists using computational methods and a lot of computation and a lot of computer scientists studying or taking insights from cognitive psychology to inspire their algorithms.

Cool. Okay. Well, I have many more questions, but first we have lightning round where we ask you short questions and we want short answers and if we're behaving ourselves, we won't ask why, how, huh? Brilliant. I think we're going to start with a short game of robot or not. Are you ready? Yes.

Is a microwave a robot? No. Self-driving car? Yes. A Roomba. Yes. Data from Star Trek. Yes.

Those little doggies from like the 80s, they would be outside mall toy stores, and they'd run into something and then turn around and then keep walking and then run into something and turn around. Not old enough. Coffee maker. No. Automatic coffee maker. No. A little drinking birds that do the thermodynamic thing, they go into the water, and then they heat up, and then they go back out of the water, and then... No.

He gave you the same look I did when you've suggested that. You can't tell. How many nerve center mugs does it take to trap a way-no? Six. Waymo. It says way-no here. Oh, I thought you meant the way-no off-brand-brand-way-mo. car. If it's a genuine waymo, then it's going to be eight.

There's an offer, I'll ask later. Complete one project or a start a dozen? Start a dozen. Would you rather read sex, race, and robots, how to be a human in the age of AI by Ianna Howard, or embodied AI safety, reimagining safety, engineering for artificial intelligence and physical systems by Philip Coopman? The first, which is to say I have read the first and I have not read the second one, and I heartily recommend the first, Ianna Howard's book.

It was good. Okay, all about these robots. What is your favorite fictional robot? Fresh cut grass from Critical Role. Okay, but meaning to start Critical Roar? I know very little about it, but can you give us a little teaser? Yeah, Fresh Cut Grass is a character from season three of Critical Role, which is a Dungeons and Dragons actual play.

he is a sort of therapist robot with a with a dark past that he's discovering and working to overcome it's not my favorite season of critical role but my favorite robot character would you rather read a psalm for the wild built by becky chalmers or platform decay the latest of the murder bot diaries by martha walth um hmm well i i just read psalm for the wild built a couple days ago, and I have not read Platform Decay. Have you read the murderbot books? I've read the first two.

This is a hard one for me, because I wasn't a fan of either of these. I enjoyed some for the Wild Built, but it left me lacking a little. Actually, for both of these, I kind of ended up, I enjoyed them, but I wanted more. Okay, tell me what you wanted more.

Sorry, I can't do it. I know I was supposed to ask about all these The podcast talking about books. I know, yeah, this lightning, lightning. No, for a conversation about books, this is a lightning round for me. Yeah, I think that with the song for the Wild Build, it had a very, you know, cozy feeling to it. It was delightful. But it felt like there wasn't as much depth to it as I was hoping for.

In contrast, I'm currently reading, I just start immediately following. reading her two books, I started reading Death of the Author from Let me pull it up. From Nadi Okora for.

Oh, yeah, okay. Which is about an author who writes a book very, very similar to the Monkin Robot books. about these robots in this sort of post-apocalyptic society. And there's, because it is alternating between the science fiction about the robot and then

the much more human and deeply and more modern story about the author, I think there's a lot more more emotional depth to the book. So I think that the Psalm for the Wild Belt did what it accomplished, but I, I think, I was hoping for a little bit more literary depth to it. That's fair. The needy Okafora books are grittier. And Psalm for the Wild Belt was fairy tale-esque. Yes.

I actually was listening to it to go to sleep for a little while. And it was not something I was worried about waking up in the murder, in the middle of a murder scene or something. 100%. Okay. Since I've derailed this, I do have a question. about robot-themed musical theater improv? Ooh, yes.

I don't know what my question is, so let's just go with what? Okay, yeah. So you said robot-themed musical improv, and I think you are connecting together a couple of the different things I do. So outside of my work as a computer scientist, I spend 10 to 15 hours a week doing improv,

theater. This includes performing improvised musicals where we get a suggestion from the audience of a choice they've made and then perform an improvised musical about their life if they'd made a different choice. And then separately, I've been doing some robot-themed comedy nights. This includes Robot Riot, which is a monthly robot comedy show where we have comedy about robots in AI and also involving robots in AI. So, for example, we'll have improvisers performing on stage while a robot interjects and gives them rules they have to follow to sort of to showcase their talents, but also to highlight for the audience the ways that the rules we impose on robots end up being rules that we're imposing on human autonomy as well. And then I also am running an

improvised Black Mirror show where we get tech ethics students from Mines and from C.U. Boulder to write pitches for Black Mirror episodes and then we enact them on stage. Okay, I'm going to go back to what the show is supposed to be about because otherwise I'm going to get totally lost

and we can come back to that later. I mentioned the Mudd alumni thing because we recently went to our reunion and like every other person I talked to had something to say about the Colorado School of Mines. All I knew about it was that there were explosions, which very attractive.

Which was the reason I almost applied there. Right. Can you tell us a little about the Colorado School of Mines? Yeah, the Colorado School of Mines is an engineering college that's just outside Denver, Colorado. It has been around for about 150 years, I think 151 this year. and it started in the 1800s as a mining engineering school to educate the people who were coming to Colorado as part of, I guess I don't know enough about Colorado history, but not the gold rush, I don't know, whatever, whatever people were coming to Colorado to make their fortune fortune in the mining industry in the 1800s.

Some sort of metal. Some sort of metal. Yeah. And so mines as a university, it does have a very strong mining engineering department. It owns a mine out about 45 minutes from the school. It's an old silver mine. I've been down there. It's very cool.

And people run all sorts of experiments there. It's very cool. They've got a classroom that's hollowed out of the rock that they hold some classes in. Yeah. It's wild. But the university today, that's sort of a small part of what we actually do. It's in general just a STEM university. So most of the departments are focused on engineering or applied science, with the exception of the economics and business department, which is still oriented around those types of science.

and engineering programs. How big is it? It is about 7,000 students. Oh, wow. So it is small-ish, but not tiny. It is about the size of if you took the engineering school from a larger university and sort of airlifted it out and dropped it somewhere else.

So it's not huge, but that's because we don't have all of those other majors. We have within computer science and mechanical engineering, I think something like 70 faculty. So it has a pretty robust program in robotics. We've got robotics, masters, and PhD programs, for example, which are not common in the U.S. But we have no one in, we have no English majors. We have no philosophy majors. We have no psychology majors, which is interesting as a cognitive scientist.

But, okay, so it's a graduate school as well. You award PhDs. Yep. Okay. And when I think about robotics, it's about the complex electrical and mechanical systems. Because you're an implementer. Because I am an engineer and I develop these things. And if you show me a BLE goldfish monitor, I'm going to say,

know that's not a robot, but having worked on an autonomous water sampling system with motors and sensors and enough intelligence to let it live in the wild for months on end, I'm like, yeah, that's pretty much a robot, even though it doesn't walk around and say anything to people. Would that be a robot to you? I think I would need to see it, but it's complicated because there isn't a clear definition of a robot. There are engineering definitions that people have created. For example, saying that a robot is an embodied artifact that can sense its environment, make decisions and take actions in the world. But that definition does apply to a lot of the things you talked about in the lightning round. It applies to the coffee maker,

the coffee maker, to thermostats, to elevators, to dishwashers. And part of the reason why this is complicated is because robots are a science fiction concept. The word robot comes from science fiction. The word robotics comes from science fiction. And so to a large extent, the definition of a robot that in terms of the most sort of accurate and I think compelling definition of a robot is just, if you saw it in a movie, would your parents describe it as a robot? And then this is slightly complicated because things like autonomous cars now don't fit that mold of how we typically think about robots, but they're sort of on the border and people do, I think, understand them or think of them

as robots or more as robots than they would their dishwasher, because they're autonomously moving or semi-autonomously moving through the environment. But then there are all sorts of other things that people in robotics work on, or they use the tools and techniques from robotics to work on, that the general public would look at and be like, well, that's not a robot. And so to the roboticist to sort of claim that what they're doing is robotics, is it a robot? Yes. But in the larger cultural sense, does our society consider it a robot? No.

There's also a great, there was a great paper that came out at the Human Robot Interaction Conference two months ago from Waki Camino from Cornell University on the robot umpires in baseball right right they've started using automation to detect balls and strikes right exactly they're these automated ball and strike cameras and i think uh she raised in her paper that that that the major league baseball really tried to emphasize that like you know it's not a robot um but the public very much uh picked up on this like robot framing for it and it has very consistently been referring to it as a robot. And she points out in her paper the ways that the definition of robot is really fluid.

And it depends on what it is doing and who it is made by and where it's deployed, but in ways that are really hard to pin down. And so it's a fluid technology that doesn't really have a very firm definition where you can clearly and easily draw a line in the sand between robots and not robots. As a professor, if a student comes to you, sophomore junior, says, I want to be a roboticist. I want to work on robots. What classes do you recommend they take? So there, it does sort of break down into the classic robotics definition. So if we think about robots again as things that perceive the world, make decisions, take actions, then the students need some type of classes on perception like computer vision or mapping.

They need some type of classes on cognition, whether that's machine learning or AI or other types of more specific planning methodologies. is they need some, they need some training on the action side of how to actually take actions in the world. And that tends to be the more mechanical engineering classes like mechatronics or robot control. And then from my perspective, students also need to understand something about robots and society and robots and people. It isn't helpful to be able to know about the mechanical and software construction of the robot. If you don't know anything about how to talk to people and figure out what their needs are, if you have no idea about what the implications of that robot are going to be in society once it's deployed. And so because of this, I've gotten it

so that all of our robotic students at Mines have to take either my human robot interaction class, which is sort of the intersection between robots and psychology and design, or they need to take my robot ethics class, which is the intersection between robotics and philosophy and sociology and history. And you wrote a book, was it for one of these classes? The book, Degrees of Freedom, is not for one of these classes, but it is tightly interconnected with the classes. So the book is very much on the history,

philosophy and sociology of robotics. And so in that sense, it's very tightly connected with my robotics class. But it also makes recommendations for how we can move forward as a field, what types of methods we might take for designing robots in ways that are more responsible. And in that way, it connects with the human robot interaction class because the focus is not just on what are the problems, but how can we use concrete design processes to do better? I remember, I think it was in your introduction, and when we talked to Ianna Howard on the show, she mentioned having this study where she had a robot, and the robot was supposed to lead people around, and the robot in a quasi-fake emergency situation led people in an entirely

incorrect place, and people still followed it. Even after the robot had done things that indicated it was in a bad state, people trust robots. And I wonder about, you just mentioned this umpire thing. I wonder if they like, if folks who watch baseball like the idea of a robotic umpire because it's super fair, even though I can think of many ways to make it not fair. So I think that's really interesting. So, yeah, and with the study that Ianna was talking about, It wasn't just that like they had seen the robot performing poorly,

is that they'd seen the robot performing poorly, and then the building begins to fill with smoke, and the robot just drives off and says, follow me, right? And so it's in this setting where it's like, well, there might actually be an emergency here, and every single participant follows the robot instead of leaving the building and following the exit signs. Instead of following the lit exit signs.

Yes, yes. Wrong. Yes, it's crazy, right? And so people have a tendency to dramatically over-trust robots. I think in the case with the baseball umpire, it's very interesting where one of the things that Wachie talks about in her paper is about the importance of theatricality, where the purpose of the baseball umpire is not just to call the balls and strike successfully, but, But it needs to do so in a way that doesn't violate the sort of theatrical spirit of baseball. And it needs to do so in a way that allows the drama and tension of baseball to be maintained. To the extent that baseball has drama intention, I mean, I enjoy baseball, but, you know, it's a slow sport. But they pointed out that, like, they have to make sure that the amount of time it takes to challenge the robot umpire, or to, to challenge a human umpire and get a call from the automated system is not so long that it diffuses the tension. And also, they wanted it to be accurate, but to have a level of accuracy where the challenges

would go with equal likelihood towards the players or towards the umpires so that it wasn't that every time the challenge was made, the automated system was just siding with the um, and instead, if it's like a 50-50 chance of siding with the ump versus the player who made the challenge, then there's more drama because you really don't know how it's going to turn out. And so that's interesting, right, where it's not just about being accurate. It's even in that setting where it seems like it's really clean, right? It's like, well, is it a ball or is it a strike? The human factors and the cultural and societal factors are really, really important for quantifying whether or not you consider it to be successful or not.

It should just be a math problem. I mean, it's got inputs. It's a bounding box. That's what a strike zone is. It should just be a number. Right. Well, but if you want to do that, you should just put the game into a simulation. I mean, it's a game, right?

It's a human event. So you're trying to put technology into something that's traditionally done by humans. You'd be very careful. Well, and it's also, I think this is a good point where it's not just about the internal operations of the system. It's also about how it's deployed, right? Where it's not just how does the system make a decision. It's also what is the larger sort of choice architecture that leads to it being triggered? How many challenges do you allow to players during the game?

game? What is the procedure for making a challenge? Is this something that automatically happens or you need to make a challenge? Right? And those types of decisions about how the robot is deployed are going to also shape these, you know, these questions around the drama and narrative of the game. Why wouldn't you do it automatically? Okay, sorry. There have been umpires for 150 years, 200 years, and people, you know, are used to it. You can't just get rid of them. And it's kind of fun to get out of them.

Uh-huh. Well, it's also interesting in the paper, and I know we're going on and on about this specific paper, but like it's a really, it was a really cool paper. But they also point out the ways that this isn't completely new. And they have a picture from, I don't know, like in the 1940s or something of an automated,

not license plate, sorry, an automated ball strike reader camera being used or prototyped at a game. And obviously it didn't catch on because the tech wasn't there yet. But this is something that people have been trying to do in Major League Baseball for like 80 years. Yeah. Let's go back to your book. It looks from the table of contents, like either it has a lot of really great puns or it's about robotics.

I mean, there's control systems, there's end effectors, there's bounding boxes. But these don't, you don't have a chapter called. kinematics. Uh-huh. Or the math you wish you remembered from school or any of the chapters I need in my books these days. Well, so there's no chapter on the math you needed from school because there's no math in the book.

And the titles... Which seemed like a win when I started it. Uh-huh. But then it made me think too much. Oh, no. Not bad. Oh, no. I'm sorry I made you think.

Um, the, yeah, so the names of the chapters are, very much puns that I have to explain in footnotes. So for bounding box, for example, the chapter is talking about computer vision systems and robotics. And when we talk about a bounding box, typically in computer vision, we're talking about the sort of rectangle that's drawn over the image at the area where something is detected. But in the chapter, I'm talking about it in terms of the ways that algorithms are used to sort people into categories of race and gender in ways that then go on to reinforce and legitimize those specific ways of reasoning about the world. And so it is about computer vision, but the bounding box is about the sort of sociological

category that people are being forced into. What about control system? The control system chapter is talking about the ways that robots' moral reasoning algorithms, serve to control people. And so this goes back to what we were talking about with the comedy show and some of the things I try to highlight in that particular act in the robot riot show. We have this tendency in robotics to think about moral decision making by robots as a matter of compliance with ethical rules. And I think this comes from two different places. One is it comes from Isaac Asimov, from his laws of robotics. And the second is it comes from the sort of dominant philosophical theory that ethicists have drawn on in robotics, which is deontology.

And both of these are kind of messed up if you get down to them. For Asimov, Asimov's laws of robotics, Asimov actually credits to his editor, John Campbell, which if you know anything about the history of science fiction, they had to rename the John Campbell Award because John Campbell was an apologist for slavery. And this sort of helps to explain why Asimov in his stories, his characters refer to his laws of robotics as giving the robots good, healthy slave complexes. So they're really these slave codes for keeping these autonomous slaves in line. And then deontology also has this sort of similar worrying history where the philosopher Charles Mills points out that at the same time that Emmanuel Kant was creating his moral and political philosophies, he was also creating his race hierarchy. And it was one of the first race scientists. So the folks for whom Kant is saying, well, we all agree that these are the rules that need to be imposed are the people at the top of his.

hierarchy of race and gender, and the people on whom the rules tend to be imposed are everyone else. And so this isn't to say that we need to completely throw out rules or throw out Kant completely, but I think it does suggest that maybe we should be aware of this history and think about other types of perspectives we might use to approach what it means for a robot to behave ethically. So glad I paid attention during the good place. You talk about roboticists enforcing white supremacy, capitalism, heteropatriarchy, through their design choices. When you say roboticists there, do you mean the companies, the software engineers, mechanical engineers, industrial designers, product design, the funders? Who is responsible here?

All of the above? which is complicated, right? And when we talk about this in my robot ethics class, we talk about how difficult this is, right? Because if you're talking about responsibility, everyone is responsible, right? It's not just that there's a single agent which is responsible, which makes it difficult then to assign accountability when things go wrong.

Well, ultimately, everyone is responsible. and in different ways. In the book, though, I'm mostly talking to roboticists, right? It's a slightly generalist book, right? And the intended use is in tech ethics classes. So I'm not expecting that people who are reading the book have robotics knowledge. But I am sort of talking to the next generation of robotics students and sort of robotics adjacent students. and sort of robotics adjacent students.

And so in that sense, I'm talking to them as potential designers, potential engineers. But yes, of course, the entire history of robotics has been shaped by and determined by choices made by science fiction authors. And of course, it's the companies at a higher level that are steering robot design more fundamentally today, as opposed to the specific decisions of an individual engineer. I think this is also somewhere where we have a collaborator and friend of the lab, Katie Winkle, who is a roboticist currently in Sweden, who has this awesome paper on feminist human-robot interaction, where she points out that the field of human-robot interaction

is often pretty narrowly focused on the human-robot interaction. itself, whereas we do need to consider this broader network of other people who are interacting with the robots or are bystanders and otherwise affected by the robots, the places where the robots are deployed, the institutions, the funding agencies, if those still exist, the researchers themselves, their participants, and all the power relations between all these different groups of stakeholders that go on to shape robot design. It's hard. I mean, I spend a lot of my time working on control systems and trying to make the robots smart enough to do the things they need to do in order to get whatever my goal is.

And for like the water robot, I mean, you have examples where robots look like, have a wasp shape so that they are more feminized. It was a box. I mean, it was a clear box in spots, but mostly it was a box. And to me, it was very robotic because there were so many. moving parts and the electromechanical was so hard. But that was not really something that interacted with humans. You put it on the bottom of a river and it interacted with fish.

And other creatures. Now I know about the ring-tailed thingies. Those were very cute. It interacted with people in a limited way. It didn't interact with the public. It interacted only with scientists. But even that, it was a lot of control. systems. There was a lot of state machines. It was a lot of planning and thinking about how things

are going to be used. But it was never, I mean, there was the ethics hurdle of, is this a good project? But as soon as it was like, okay, environmental DNA in the middle of wilds, I'm like, that sounds like fun. I didn't think about this. Yeah, I think it's complicated where on the one hand, I would say that in the book, I'm pretty focused as a social roboticist. on interactive and humanoid robots. So robots that look like people and or that are interacting with people. But I think that even in the types of cases you're talking about,

while the issues of how a robot is going to be gendered are maybe less salient, I think you still need to be thinking about the broader ways that that technology, is part of a human sociotechnical system, right? Yes, maybe it's only interacting directly with the scientist, but the existence of that robot may change the ways that certain industries operate. It may serve to legitimize certain forms of science or certain ways of knowing.

it could lead to, you know, greater funding in one area at the expense of another. And all these sort of like broader systemic issues, which are, you know, maybe much harder to reason about or are less immediately visible. And so it is interacting with human society and it is going to have real impact on people. But yes, some of the issues around like race and gender, probably less salient. But when we talk about self-driving cars, which I think we did agree our robots, those issues do come up again sometimes. Yeah, and I think with self-driving cars, it's really interesting. I think that's actually a great example for two reasons.

The first is that we can think about the broader transportation systems and who they serve. this is something where when I was doing my PhD in Boston, I loved having a public transit system to take around. And I used the subway and the buses. And I was a much bigger fan of the subway system because I was like, I know where it is. I know how to get there. I can conceptualize it easier in my head. But other, I can't remember the scholar's name, but I know that people have written about the ways that there's gender differences between uses of subways versus buses, for example,

where the subways tend to be used to get from external places in the city into the middle of the city to do work in offices and then to leave, for example. Whereas buses have higher ridership among women who might need to be making multiple stops across the city in different parts the city over the course of the day in ways that are more easily navigated through those bus lines, which is something I'd never thought about before. And I'm guessing that there would be similar patterns of gendered use with autonomous vehicles. And so that's maybe something interesting to think about. But then the second point is that we talk about autonomous cars as, well, it's right there in the name, autonomous, right? But these autonomous vehicles are rarely actually

fully autonomous. There's pretty much always somebody behind the scenes who is either directly driving that robot or more commonly, it's when the robot encounters a problem, the human is able to hop in and take control. I was just at an event in Washington, D.C. yesterday where Missy Cummings, who is a professor at George Mason and one of the first female fighter pilots,

gave a talk all about this. And she pointed out some of the problems here where because these robots are controlled from the Philippines, there is sufficiently high latency that, at least from her perspective, they're really not safe at over 10 miles an hour, which says something when you've got Waymo's driving, you know, 60 miles an hour on the highway or what have you.

But also pointing out that when San Francisco experienced the blackout in December and all of their Waymos were stranded and couldn't move anymore, the ways that this emphasized the importance of the humans behind the scenes, where without those humans behind the scenes, the robots couldn't operate anymore. And that is something that is, of course, also going to be gendered and racialized in particular ways. I'll also just briefly point at a sort of a parallel. We're talking about these being controlled by people in the Philippines. there is a case I talk about in the book of this robot Anki, which is a South Korean English language learning teaching robot.

And so the kids in the English class are told it's autonomous, and it's a robot with like this white woman's animated face on it. But the robot isn't autonomous. It's teleoperated and primarily teleoperated by Filipino women, whose facial expressions are mapped onto this white woman's face in a way that erases their labor and erases their identity. And this happens in this very specific, racialized, and gendered ways due to the history of American imperialism in the Philippines and in South Korea, which dictated who was in a

position to be performing that labor cheaply and who was stereotypically the sort of correct instructor for English. And so we don't have those exact types of racial. and gender issues with the autonomous cars, but I think we should still be thinking about who is performing the labor and why and from where, and how does that tie into these global systems of race and gender and capitalism and imperialism. How do we balance this consideration of ethics and philosophy in our jobs when we need to have jobs?

I think that's complicated, right? I think there's some, there is a part of me that would say, well, yes, we need to have jobs, but you don't need to work in a domain where you are causing harm. And I think that I would be more willing to apply that that type of sort of hardline logic when it comes to companies like Palantir, right? where it's like, yes, you need a job. You do not need to have a job where you are working at Palantir, right? I think that for other types of robotics companies, it's a little, it can be hazier, right?

Or even you can think of academia, right? For me, as an academic, in some ways, the system of academia serves to reinforce power boundaries along race and gender and class. But what I am doing in the classroom where I'm asking students to think about these issues is hopefully subverting that in some way. So I think it is complicated. And so I don't think I would ask students,

I don't think I would tell students, don't go into robotics because there is too high of a chance that you're going to encounter ethical issues. Instead, I would say, do think about where you are choosing to take a job and what type of work that company is specifically doing and what the impacts of the technology are going to be on the communities around you. But then once you are at that company, wherever you choose to work, try to keep these issues in mind. And I'm not under any disillusion. I'm not, you know, under the illusion that I have the ability to control what students do once they go out into the workforce. But I'm hoping that if they've, you know, been forced to think and write about these issues at least once in their life, then maybe it will lead to them making some more ethical choices once they get to these companies.

In your book, you prioritize the ethics of white supremacy above others. But for me, for technology, environmental impact is a harder thing to watch. I mean, I made children's toys. They were made of plastic. I'm proud. They taught kids to read. I think it was worth it. And yet I still look at the plastic and think, wow, I wish that wasn't.

there. How do you, how do you prioritize ethics? Yeah, I think, well, so in the book, I had to take a particular frame. I had to choose a particular scope, right? And so I emphasize in the book that while I'm talking primarily about issues of race and gender, because those issues, especially race, have been overlooked, I think, within the robotics community. Of course, there are broader issues of capitalism that tie through all of the above. And similarly, you're right, issues of environmental impact are really important. I think that it is complicated in two ways. The first is that if we think about water use, one of the big environmental topics people talk about around AI is water use. But I think that some of these concerns around water use are either overblown or not

talked about in the right way, where some of the statistics that are used by people to talk about the amount of water that AI is using are incorrect. It's due to a misreading of the paper that they're coming from. And then also, the notion of what it means to use water is complicated. Hank Green, famous YouTuber, has a great video he made, I think, like, two months ago on this, where he talks about the complications around what it means to use water and AI for like an hour, and how there's different types of water, and there's different types of water, and there's different types of of data centers that are using water in different ways. And then even if you are using water in a way where it's evaporating out into the atmosphere,

even in those situations, the water, it's not like it's going away, right? It's just going back into the water system. The problem is more about where it's being used, right? And if you are drawing on all of this, if you are drawing a lot of water use, in places that don't have a lot of water to spare and in ways where and in places where that water isn't just going to go back into the reservoirs

and direct back in a usable form into the water system in a reasonable amount of time then it's like in those very spatially contextualized ways that we need to be concerned about water use So I do think that water use with data centers is a big problem, but in ways that are maybe more nuanced than people talk about. I totally agree. I've thought of water use as a cynic dokey, as something that represents the whole problem. Yeah. that water use is inextricably related to power use.

And so, but it's easier to see a bottle of water than it is to see a unit of power. And so in many ways they are convertible, although it's not something that's easy to think about. So I get that water, yes, we say water use is bad, water use AI uses lots of water, but we're also saying AI uses lots of power with no obvious results. Okay, I have a larger question for you, Tom, about this. And first, let me preface this by saying, I mean, there's lots of farming that uses water that absolutely dwarfs AI. I'm not a fan of AI to start with, but let's start with that.

He is such not a fan of AI. But I think the water use argument is a, leads me to a larger question about criticism. And my concern with water use, as you say, is it's perhaps overblown to six or misread. It's dwarfed by other industries that nobody's talking about, all these kinds of things. But I also feel like it's something that the rug can be pulled out from under the critics, right?

Oh, we've solved the water problem by changing cooling methods. Or we've made an advance and now we don't need data centers anymore. But all the other stuff that has been, that AI makes AI problematic still exists. And people aren't talking about that because they're spending all the time talking about water, which I agree is a very easy thing. thing to talk about. Tom's talking about the white supremacy and race and gender. I'm not talking about Tom.

I'm not talking about the discourse. I see a lot of discourse about these kinds of easy number things. Yep. Where it's like, oh, power, oh, water, oh, data center, expend, all of these things. When I see less about psychological impacts or the impact on employment, these kinds. I mean, those come up. But I feel like the question I have is, Is this a common thing in criticism for industries and discourse where people pick an easy target and the target can be pulled out from under them?

And then it's harder. It's easy for evangelists to discredit the critics by saying, oh, see, that wasn't really an issue. And therefore, everything else you're complaining about is also not an issue. Yeah, 100%. And I think this goes back to what we're talking about of the network of who is responsible. responsible, right, being just enormous and hard to grapple with. And it's just hard for people to think about systems, right? There is a fantastic book, Atlas of AI, where Kate Crawford talks about some of these environmental impacts in terms of these larger systems.

And she's got this great graphic that goes along with it that shows how all these different things. fit together in terms of all these different disparate impacts, how they intersect with the history, how they, and the larger systems they fit into. Unfortunately, the graphic is so large that if you tried to print it out, you would need a quite long hallway in order to display it. And in fact, I think she had an exhibit on it at the, I think the Met in New York City, where they had, they had indeed, a huge room to put this graphic up. And that's part of the problem, right, that all these impacts and the ways that they fit into these systems

are so vast and interconnected that you can shine the spotlight on one area. and in doing so, you're necessarily excluding the other areas, but I think it's sort of an intractable problem. It's just a limit of human psychology. Right, right. Yeah, and we end up to bring up the good place again. I fear sometimes we end up like Chee-D with his almond milk and his coffee, losing the bigger picture.

It's like, oh, this is what's damned me is my almond milk in my coffee? No, it's that you've paralyzed yourself. Yeah. Yes, the good place I show that when I first saw the trailer for it, I was like, this looks awful. And then I started watching it for some reason. And I was like, this is amazing. But it's easy for me to say that as a professor of ethics. Yes, right.

Okay. To that point, don't the students, the computer science students, the robotic students, who are learning control theory and robotics and slam localization algorithms and dealing with cameras and I could design a whole major. Do they really need to spend time learning the history, philosophy, and ethics of everything they might possibly do? Or can't they just go back to... Look, if Mudd made me take a class on Kant, then everyone else should have to.

You chose that. I took the history of science. Yeah, no, I think absolutely that they do. I think that asking students to take, you know, a semester is really sort of the bare minimum of the amount of time that students should be spending on this. And really, I think what we also need is what people refer to as ethics across the curriculum, where students encounter this type of ethical deliberation and societal context in every class they take, even if it's just for a little bit. Otherwise, what happens, and I've seen this at Mines, is that students, their first year, get exposure to some of these issues.

they then don't encounter having to think about people at all for several years, and then it's their senior year when it comes back to senior design or when they're taking an elective like one of my classes, that they're asked to think about it again. But in the meantime, the sense that they are given is, well, maybe it doesn't matter that much because we're going to put that on hold and not talk about that at all this semester. And I think this is particularly important today with computer science because of the rate at which computer science is able to move, right?

So you've got these students who are graduating, and especially in the age of AI where they're able to vibe code a product in 20 minutes, right? We've given students enough knowledge to be dangerous, to be extremely dangerous, right, in order to very, very quickly. create a product that has the ability to potentially immediately impact millions of people. And so in the same way that like professional engineers have licensing requirements, right, and have to have to have knowledge of the safety of how they're building their bridges, right? And know that they are responsible or, you know, liable if something goes wrong, if their bridge collapses. we need to be instilling that same sense of responsibility and awareness into our computer science students in ways that currently we just don't do it all. I agree, although it is a little difficult to have that awareness of responsibility without the feeling of power to change or authority.

It gives a powerlessness to it. Yeah, I think this is something where, for this reason, even in my robot ethics class, I make sure that we spend a week talking about design so that it isn't just all doom and gloom. And it's also, well, here's just, here are specific paradigms and tools you could actually use that might mitigate your risk of falling into these traps. I think that this is also somewhere where when people talk about like tech ethics, there's, tends to be an over-focusing on moral philosophy and not as much on not only on these broader system-level issues, but also specifically on design. The philosopher Peter Paul Verbeek talks in his writing about the ways that design is a way of doing ethics by other means. And I think that if we move towards more practical hands-on ways of thinking about ethics,

then that might help to counter some of this doom and gloom and depression that you otherwise get in an ethics class. Is that like thinking about the accessibility features as you're doing the design of your system? Or what do you have for that section? What are the design features that would make this not terrible? Yeah, so we really hammer home on methods like participatory design where you work with communities directly to build the systems that meet their needs. We talk about design justice, which is a framework where you say instead of sort of design, this technology paternalistically for this community, we will give them the tools that they need so that they can design it for themselves. So instead of us saying, well, these are the rules that the robot needs to follow, maybe you give the communities an interface that they can use to instill their systems values or norms or role ethics or what have you into the system on their own.

Now, I will also say that this is complicated as well because I think the further you go towards empowering communities, the more you potentially abdicate your own moral responsibilities, right? If you say, well, we'll just let the community, you know, a community to decide for themselves how they're going to use this technology. Then you're sort of just avoiding making any ethical decisions yourselves and just hoping that your users, you know, choose for the best. And so this has been a problem with like Apple, for example, they got some pushback on how like the, you know, the Siri voice is, you know, this white woman's voice. And they started creating more voices for Siri. And I think they ultimately made it so that the user has to choose.

So that there isn't a default voice. And I can't remember if this is Apple or Amazon. but for one of these companies where there isn't a default voice and the user has to choose, right? And to some extent, that does decrease the likelihood of the system by default reinforcing these associations between femininity and these types of like administrative labor. But on the other hand, it sort of just pushes the decision to the users, right? And you can expect that if those stereotypes are the reasons why the system was designed that way, then users are probably most likely going to choose the voice that plays into those stereotypes for the same reasons.

So it's... Yeah, why would we assume that the user community is a separate domain of humanity from... Right. And so it really depends, right? I think if you're working with, like my lab does work with on house survivors of domestic abuse, for example. and that is a space in which we want to make sure that we are listening to that group and working with them to design the technology. And this is something where things come back to improv where we've been developing new improvisational role play-based design methods that allow the community members to participate in robot interaction design in different ways, either by sharing stories of, ways things have gone wrong in the past that actors then act out to give a sense of what a design might look like or the community members giving feedback and sort of directing those role play

activities or them sort of jumping in and role playing in these sort of roleplayed interactions between a hypothetical user and a robot product. And so this is somewhere where we do want to have tight connection with those communities and where I think we would feel more confidence in giving more agency over to those specific community members. But obviously in other domains, like I don't know if you were, and you know, I've written a lot and there's a whole chapter in the book about robots and policing. And I don't think we should be developing robots for the police. But if you were to design, you know, a police robotic system and say, well, we'll just give it over to the police and allow them to decide for themselves, you know,

know, you know, when and how the robot should be surveilling people, then, you know, for obvious reasons, that might not turn out the way the roboticist would hope. I mentioned Philip Coopman's embodied AI safety book, which is more technical, less ethical, more directive, implementation, directive. Prescriptive? Yeah. Yeah. And one of the things, one of the ideas that he brought to me was moral crumple zones.

the idea that, sure, I'm not responsible. I told you not to run it into a wall. Or I told you not to use the AI. It's on page 50 of the manual. It's on page. Yes. And I really like that as a idea, at least for myself, that there are, you can tell people, you set people up for failure.

And that's not, that's not okay either. Yeah, and I think that this ties in to these things we've been talking about, about who to hold responsible, right? Some of the types of moral crumple zones that we see in other places are with, like, pilots and airlines, right? Where when there's a plane crash, people tend to blame the pilot, even in cases where it's really not their fault. And the airlines might sometimes design things in ways where it makes it easier cognitively, to blame the pilot, right, in ways that avoid liability them for themselves.

And for robot design, I think that it depends on the type of robot, who is likely to fall into that crumple zone. If it's the person who's using the robot, if it's the person in the Philippines who is remotely controlling it, et cetera. I think in all of these cases, again, yeah, we need to be figuring out ways that we can reasonably hold the companies responsible, but we also need to be identifying ways that we can inform the general public of this broader network of stakeholders that are involved and of how the technology really works so that they're not just by default putting people into the crosshairs that don't deserve it. Tom, it's been wonderful to talk to you. Do you have any thoughts you'd like to leave us with? Yeah, I think that as a closing thought, the high-level point I would make is that we can't afford to think about robots purely as technical devices. And whether we're talking about a android or a cute, fuzzy, home robot pet, or if we're talking about a glass box that is, is exploring the bottom of a river.

We always need to be thinking about the humans that are involved. Our guest has been Dr. Tom Williams, Professor of Computer Science at the Colorado School of Minds, and author of Degrees of Freedom on Robotics and Social Justice. Thanks, Tom. Thank you. Thank you to Christopher for producing and co-hosting. Thank you to David Goldberg for the introduction,

and thank you for listening. You can always contact us at show at Embedded.fm or hit the contact link on Embedded FM. Now a quote to leave you with. With outright horror, he refuses any responsibility for the thought that machines could take the place of people or that anything like life,

love, or rebellion could ever awaken in their cogwheels. He would regard this somber vision as an unforgivable over-evaluation of mechanics or as a severe insult to life. That's the inventor of the word robot Karel Chappick in an explanation of how everyone got his idea of robots wrong. It's an I-Trippoli spectrum as a translation, and I will link that in the show notes.