Embedded - 97: Bubblesort Yourself

Episode Date: April 15, 2015

Professor Paul Fishwick joined us to talk about CS and STEM education, excellent analogies, and the crossover of art and technology.  The Linker post related to this episode managed to be reasonably topical for a change. Paul's work: UT Dallas homepage Creative Automata blog and Modeling For Everyone blog TEDx talk Aesthetic Computing, one of his books on art and CS. Online chapter.  Creative Automata course Videos   Radiolab Color Episode Forrester System Dynamics Max is a visual programming language for music and multimedia. CS Unplugged is a collection of free learning activities that teach Computer Science through engaging games and puzzles that use cards, string, crayons and lots of running around.  There are many bubblesort dance videos (mindboggling) but this is the one Elecia knew about previously. The Computer History Museum is awesome. If you are in the area, you should definitely go.  Conference and contact notes: There is a party/hack event in Pasadena May 9th and 10th, email if you want more info (and an invite). Elecia will be speaking at SOLID in SF in June, giving an intro to inertial.  She's got a coupon to share if you ask. ESC Minneapolis' call for proposals is open but closing soon. Elecia will be at ESC Silicon Valley in July, speaking on being a Maker (or not). 

Welcome to Embedded, the show for people who love gadgets. I'm Elysia White, my co-host is Christopher White, and this week we will be talking to Paul Fishwick, Professor of Computer Science. Before we start, I have a few announcements. Embedded Systems Conference Minneapolis proposals are due April 17th. That's real soon, so get those proposals in right away. It would not shock me if they extend that, but even so, gotta at least start them.

I will be going to ESC Silicon Valley in July and O'Reilly Solid Conference in San Francisco in June. In fact, at O'Reilly's I'll'll be speaking on inertial sensors, and I have 25% off coupons. I'm happy to share, but I'm not supposed to make them public, so you'll need to hit that contact link on embedded.fm. If you'll be in LA, Pasadena area, the weekend of May 9th and 10th, there will be a geeky event and party. Again, it's not quite public, but I'm happy to invite you, so hit the contact link. And that about covers it. Hi, Paul. Welcome to the show today.

Hey, I'm glad to be here. Could you tell us a bit about yourself? Yes. I guess from an academic standpoint, I was always interested in mathematics and art. And so I kind of started there. I went to work for industry for about six years at a shipbuilding company, as well as at NASA Langley Research Center in Virginia. And then for most of my career, I was at University of Florida. In the last two and a half years, I've been at the University of Texas at Dallas.

I direct a center called Creative Automata. When we started talking, it was to discuss analogies in education. That is something I find fascinating. Could you tell us a little bit about your work in modeling and simulation? Yes. What we try and do in the lab is we try and represent models using a kind of an art-based approach. And by art-based approach, I mean that our models are one-offs. I mean, a student may be inspired by a particular aesthetic or a style, and they'll use that in order to create a model of something that is either mathematical or related to computing, such as a data flow or

an equation or a part of a computer program. They'll represent it with different materials. And so that's analogous. That's kind of the use of analogy and and using different materials other than text uh to make that creative representation so back when i took an introductory engineering course in college one of the things they did uh was to teach systems and they they showed like uh pneumatic systems where you'd have air pressure, and they would compare that to an electronic system or a water system and compare that to an electronic system and make analogies between, say, voltage and water pressure and current and water current, I guess. Is that the kind of thing taken a step further? Yes. Yes, no, I think that's very much related. In fact, we take it a bit of a step further yes yes no i think that's very much related in fact um we take it a

bit of a step further i'll give you an example in the creative automata class we had students that were told to represent a time series uh with data and most of them use the weather so uh with with weather data you might have humidity and temperature, for example. And then I said, okay, you've got your time series, you've got your data. Now here's a stepper motor or here's a servo, here's an RGB LED, and here's a piezoelectric buzzer. Now represent the data with those items. So, that's not a direct answer to your question, but it's kind of an example of how one of the ways that we would explore analogy. I basically give somebody a set of objects, much like you might do as a child.

You have a bunch of Legos or you're in a sandbox and somebody says, okay, let's build the pyramid at Giza or let's build the Eiffel Tower. How are you going to do that with sand or how are you going to do that with Legos? And in our particular case, in the case of the class, it was how are you going to do it given these three electronic components? And so there was a Radiolab episode about colors where they talked about different cones and what animals could see what colors

and how the cones don't just add one color each, they are exponential and they used a chorus and so they had like two or three voices for the dog that would talk about the rainbow with a few number of voices and then when they got to humans,

there's a few more. And when they got to that weird undersea creature, the cuttlefish, they had a full vocal choral orchestra. Is it like that, that you're making that sort of analogy with time data and a small number of electronic parts? Yes. And the small number of electronic parts is just one thing. I mean, I might also, what I've done in prior years is we use Minecraft. And if you played Minecraft,

you may have seen that, you know, people make arithmetic logic units and NAND gates and flip-flops. And there's all kinds of other things you could make too. You could make finite state machines and other kinds of arcane computer science models in Minecraft. So we've used a variety of different media. So electronic components would be one medium. Minecraft might be another. Lego Mindstorms might be at another. And I think the thing you're pointing to, I think, is really good.

That would be, you know, let's use sound. So let's sort of explore the electromagnetic spectrum, for example, but map it to sound. I think that's very much in line. It's an issue of translating or mapping from one domain to another domain. Okay. So I think that's kind of broadly speaking what's going on and what I'm trying to promote in the class and in our research. I like this idea.

I once did the design patterns book, the game for how software patterns work. I don't remember the title, but it's shown it. And I did it with a group and we made physical models out of each design pattern because they all are objects and can be treated like physical objects. And we had Play-Doh and legos and such things and it really helped to make the ideas intuitive although it did mean that i forgot the name of all the patterns which was sort of painful but it was a way of actually getting the information in there and having it stick is that sort of what you're doing, making the things more physical? Yes. And so I seem to recall I heard a podcast where you talked about building a water computer and how that helps with, I want to say understanding integration,

but understanding isn't the right word. Making it intuitive. I guess grok is the word that science fiction uses. Yeah, Heinlein. I like that. Let's go back to a stranger in a strange world, a strange land. But yes, I agree. No, yes, we have in the lab, we have taken a mathematical model, the Lat of nonlinear differential equations that describe predator and prey like lions and gazelles or rabbits and foxes.

And how those populations, you know, basically you've got an oscillator in the phase plane where you're kind of going back and forth if you map it out in terms of phase. But we have made a water computer. Yeah, we used rates and you've got these levels, which are essentially integrators. And you tie all these things together and you create a model. And in this case, it's a model of predator prey. So we have the water computer currently consists of two tanks. It consists at the very bottom of a water reservoir with a pump. And then we have some 3D printed gears and some servos, four servos, two servos on each tank, one for the input and one for the output for each tank. And then we have an Arduino Mega, which is doing the controlling. So it's a bit, it's old school in the sense that there were people that actually did water computing, you know, a long time ago and also in the 20th century. But it's sort of new, newfangled because we've got the digital element.

We get the Arduino microcontroller doing some work for us on the servos. And so is the idea with these analogies that they demonstrate to somebody who doesn't know the concept, or is it that they are actual tools to find out what the answers are? No, they're not so much. Well, I guess they could be be both it's a really good question it's i would say there are a couple different ways of thinking about this sort of learning one is in the actual engineering or creating where if you like artistry if you think of this as the water computer is a work of art in actually designing and making it you're're learning something. And that's kind of, I think, the main point. Now, once you have done that, then you can show it to your friend and your friend may say, oh, I see.

You know, there's integration going on because the water is bubbling up and the height of the water in this tank reflects, you know, the number of gazelle or the number of foxes and so forth. So, it's another representation that may speak to people who are visual learners, but at the same time, getting back to the person who created it, it's a way of learning through creating. It's a way of learning through modeling, which is kind of, it doesn't replace text. It doesn't replace traditional mathematical notation. But I see it as augmenting it because everyone's different. Everyone learns in a different way. And so we're building different representations and we intend to assess that, which we haven't done yet, but we've got a proposal to do so. I like what you said about teaching as a way of learning. And I think that's an incredibly important thing, that we forget that teaching is such a good way to learn things. And the way you're talking about having students build ways to explain the idea to other students is great. I think information presentation is hard, and getting them to understand that and the problem is really great.

Right. I think, you know, we tend to think of teachers as, you know, in the 19th century. They're wearing a mortarboard on their head and a gown and so forth. And that's the way things were back then. But I think today, especially with all of the new, you know, the podcasts, Khan Academy, et cetera, everything going on, teachers have to, are changing. The role of the professor, the role of the lecture are changing to be more of a guide. And to get back to your point, the social connection between teacher and student is absolutely two-way. It always has been. It's never, and it shouldn't be that, you know, say I'm getting up there, I've got some PowerPoints and I'm delivering a one kind of a package that goes along a one way street to the student.

I have learned so much from all of the students that I've that I've taught or I've mentored. And so it is it's definitely two way, much like, you know, having a kids. I mean, they teach you so much it's unbelievable uh and so it's you know takes that to a sort of different level of maturity of course at college and university well i think there's two other things that could you know come out of this kind of uh representation one one is that communicating about science as science becomes more and more sophisticated i mean you're talking about a system of nonlinear differential equations, if there was a situation in the economy

or a situation that needed to be communicated for some sort of policy reason, that's kind of hard to convey. You're not going to have the New York Times or USA Today writing an understandable article for general non-technical people describing the system of non-linear differential equations but if you had something that was visual that could say well here's how this works and you see this going this way and this increasing and this

decreasing uh that seems like a a great way to communicate about science without really dumbing it down, but bringing it to a realm that it could be at least understood in some intuitive level. And I also think it's interesting from an education standpoint. I think we've already touched on it, but I was just thinking back to my own classes. And the types of things that we did for for non-linear equations were here's this bucket of tools you know here's this technique or this technique or this technique and they work on these kinds of things and these kinds of things and you know and you just throw it at it and there wasn't really an understanding of what the hell was going on with with the system so i think it's really i think it's really cool yeah and you're really cool. Yeah. And you're right. The, the,

not the, the differential equation stuff is, is sort of a more advanced model, but we can, you know, uh, and, and why we chose Latke Volterra, I'm not really sure, but it was, I suppose it had enough complexity that we could talk to our peers, uh, but then enough creativity and representation that we could sort of say to other people, hey, you know, this calculus stuff is not really hard. You do it, you see it every day when you turn the tap on and you, you know, you put the plug in and the water rises. So, yeah, we need to really, we need to work harder on having – I've heard a colleague that used the term multimodal communication, which means that you change the way and the sorts of props you use, the sorts of things you say, the media that you employ, depending on who you're talking to. And that's kind of what you were just saying, that if I'm going to be talking to the general public, I certainly wouldn't bring the water computer out, probably. I'd do something much

simpler, and I'd probably try and connect it to current events, because that's going to garner the most interest. I think Chris was saying if current events meant that you had to explain two differential equations working together, it would be really hard to do without a water computer or some other physical model people could look at and say, oh, because just popping up the equations on CNN won't work. Or those counterintuitive things that happen. Yeah. Especially with nonlinear things, that you just, doesn't make sense, that that shouldn't happen, and yet, oh, we put in these inputs and this incredibly bad thing happens. Well, I liked your point about it doesn't actually dumb it down. It hides some details associated with numerics, but it shows you the whole system. And how do you find analogies, Paul,

that actually cover the good stuff and don't shave off too many details? Oh, that's a great, I don't know. That's an art form. It's an art form, you know, to do that, because I think, you know, as centuries have sort of gone on and you can read about different analogies that people have used, for example, for the from a bad analogy if you've got a guide there to sort of say, hey, this is – where does this analogy break? Where does it work? Where does it break? Because in essence, all models break somewhere, right? They're all good at abstracting some things out, and they're poor at other things. But that's just the nature of modeling. I guess it was George Box who said, all models are wrong, but some are useful. And that's true, but we can't do without them. In my mind, it's modeling is just

very human. And ultimately, not to to get too philosophical ultimately everything is a model or you know our brains model everything for us and there really isn't any you know direct this is the real thing when you can take classical mechanics as a model for the real world no and then talk about relativity right or quantum mechanics quantum mechanics. And then, you know, I can't even think of an analogy for quantum mechanics. That's such a mess. Magic at that point. Yeah. And then they tunnel.

And you're like, no, that's fake. But it is an analogy. It's just a, it's not a easy to convey one. Yeah, it seems like that we just, you know, we experience the world through our senses, right? And so it's only natural, again, you know, it's only human to want to understand everything through some sort of mechanical analogy. I mean, we may finally document all of our knowledge in equation form. I mean, all of our science knowledge. But yeah, I mean, for voltage and so forth. So I think we need that because we see that every day,

and it doesn't make sense to us, literally, if we don't sense it. I have this idea, and maybe it's already something you've come across. Actually, I would like to know if there's a real name for it, about educational evolution or maybe pedagogical Darwinism. The idea that people learn new things and if they learn new things easily and well, they're more likely to teach an idea, quantum mechanics, a new analogy or a new method, then the teaching method as well as the idea gets passed along. And that's where the Darwinism in education comes from. I've been sort of, this was one of those, you know, shower of thoughts where you get hooked into and you just start thinking about and thinking about. And this has been percolating for a while.

Isn't it already a thing? Or did I invent this and I should patent it? I think you should patent it. But, you know, the dry one is, are you basically asking whether, let's say you invented something and that you would be teaching that in a particular representation in which you invented it. Is that kind of a bias or is that what you mean?

No, more the higher level idea that how you teach something is almost as important as what you teach, because how you teach it and the uptake of it is reflected in how it gets passed along. I mean, if you read Newton's Principia, which I haven't, but I have heard that if you read it, it is really tough because the way acceleration and momentum are presented is just sort of baffling, very confusing throughout it. And now we teach these things. I mean, some middle schools can even explain momentum and acceleration and the difference in why they're important because we've gotten better at teaching, not because the concepts have changed.

I agree with that. But I also say we need to get better at learning. And what I mean by that is because of this landscape has changed with regard to learning. I mean, I don't want to sort of name drop all the different, you know, advertised for all these different places. But I mean, of course, you've got your podcast, there's all these other podcasts, there's books, there's the e-readers, there's the academ there that are completely outside of academia, and that's an extremely healthy phenomenon. So I guess what I'm leading to is that instead of teaching, we have to sort of – one of my goals is to try and get the student to teach themselves because we do more of this with, you know, you go to say, you know, Google search or Google image searches is actually, I'm more partial to the image search than I am to the regular search. And you look for something and you, you kind of, or have a thirst, a thirst for knowledge. And so I think part of teaching is, is just trying to, how to encourage that thirst and how to encourage that level of

getting the student to go out and encourage them to browse. And then in the classroom, you do more project-based learning and less of this, you know, testing and just regurgitation, which really I think is dead now. I mean, that kind of approach to teaching is, I don't think it's very effective. It sounds a lot like the inverted classroom, which has become a big thing. Yes. Which is to do most of the rote teaching elsewhere, on video or whatever,

and then have actual interactive, do the homework in the class. I think I've got that right, sort of. But do the actual projects and the practice work in class rather than lecture. Because the lectures are usually the same each time, so why keep giving them? Right. Right. That sounds cool.

So your creative automata class, you were talking about that time series and piezo and RGB LED and motor. What are people doing? What's been neat? Well, I have them in years gone by. And I like your project, Alicia, where you mentioned about the things you did in software engineering, the patterns. I've been, when I was at Florida, I taught a class called Aesthetic Computing for about 12 years before I came here to Dallas. And in that class, we had art exhibits with software patterns. We had art exhibits with automata, with pieces of programs where people have marbles running around. It very much looked like a Rube Goldberg way of looking at computing. And in the class that I have now, I mean, they started using electronic components,

but now they're making a sorter. I'm saying, go ahead and make a sorting machine and do that by, first of all, looking around and finding sorting in the real world. So this is another something we haven't really talked about, you know, so far in the podcast, but I'm sort of a proponent of finding this information flow outside of engineering, you know, but through observation. So you might see something as information and you see the flow of that thing and you say, well, that's information flow. And then you may see conditional branching. And all of this is outside of the traditional text-based programming. So I try and encourage that in the class as well. You know, for sorting, sorting is a great, you know, is really a nice subject.

There are lots of companies that make fruit sorters and sorters of candy and sorters of, and if you, you know, think about sorting as a sort of general ordering mechanism, creating order out of chaos or order at where there was some randomness. I mean, sorting is absolutely everywhere. We don't have to build anything. We just have to sort of train ourselves to see it. I don't know if that, I may have maybe have gone off into a bit of a tangent, but. I'm there with you. I visited a small company and they showed me a recyclable sorter that they'd been working on for, I don't know, some trash company.

And basically it was to separate the glass from the plastic from the paper. And it was really cool. And I could see sorting fruit. Yes, that makes a lot of sense. Christopher, do you think that we could make a bubble sorter that was actually sorting bubbles? Because that would be really cool to have little bubbles over here and big bubbles over there, and we'd call it a bubble sorter. Yeah, he's giving me the same look he gave when I interviewed the cat. Yeah, yeah.

Okay. Yeah, yeah. We have to think on that, right? Yeah. It's a good idea. I mean, you probably, I think you had mentioned earlier something about, you know, if you look online, you can see people doing a dance. Again, that's artificial. That's creating, you know, humans basically doing actions that result in a sorted sequence.

Wait a minute. You and I talked about that, but I haven't said it on the show. So let me make sure. You can find on the internet someone doing a musical dance in which they bubble sort themselves by height i'll find a link and put it in the notes but yes that was a that was incredibly amusing yeah i mean that's fantastic and there's a i think there's a fellow that does there's a group that does um there's a group that does CS Unplugged, Computer Science Unplugged, and they're kind of all about that. So, I mean, if that interests you, the Hungarian dance sort or using people to demonstrate computing concepts, CS Unplugged is quite amazing. I have nothing to do with it, you know i i find it an interesting resource oh neat i'll have to look at that i was unfamiliar with it and um so okay the sort

it makes sense what else are your have your students done in the past with the automata class well we had um i teach different modeling types. So we do finite state machines, for example. And I will say, okay, here's a state machine. It's got these number of states and these transitions between states. And I'll say, okay, build a state machine. And there's different ways you can do that. You could take the, instead of circles and arrows on a whiteboard, you could say, okay, I'm going to represent the circles as rooms, and I'm going to represent the arrows as doors. And so going from- And then I'm going to put it in Zork and make it a game.

No, if you do that, I want a copy. No, I love Zork. Okay, you're bringing back old memories. So text-based adventures were fantastic. And I totally agree. I think something like a Zork-type adventure, but with finite state machines, what an interesting way of getting people who are more oriented towards the humanities in understanding state machines, you know, what an interesting way of getting people who are more oriented towards the humanities in understanding state machines. I feel like I'm going into Tron.

Oh, no, you mentioned another of my favorites. Tron is, Tron was my, I'm serious. Tron was my, one of my major inspirations for getting involved in aesthetic computing. So I'm definitely all about pop culture. I mean, when I saw Tron was one of my major inspirations for getting involved in aesthetic computing. So I'm definitely all about pop culture. I mean, when I saw Tron, and I saw the first version, which I think came out in, was it 82? Right around then, yeah. I mean, I was absolutely enamored with this thing. And, you know, because, you know, there's the MCU.

And he didn't have a story, you know, the evil MCU and so on, or MPU, I forget. And then they would show, you know, information going from one place to another with people flying. I think we need in computer science, we need to sort of expand out like this. And that's what I'm trying to encourage for the non, you know, the non-computer engineer, the non-computer science major. If we're trying to get our point across to how important engineering is and how important information processing is, we have to connect to pop culture. So, oh, yeah, Tron, don't go there because we'll probably be we'll probably be talking for another an hour i started to ask you what were some of your best projects and then i totally interrupted do you want to go back to that do you have things you want to particularly highlight well we have in terms of best projects one of the projects i remember i thought was interesting is i i said okay take take an equation or take something mathematical and use wood and plastic and so i think there was one one one student who created the taylor

taylor series expansion and it was the most fantastic thing I'd ever seen. And we would rent out or otherwise obtain space that generally was reserved for art exhibits. And students would have an exhibit. We'd have Coke and soda and water and some appetizers and some desserts. And we'd invite the general public to come around and look at these crazy things that we created. And I guess it was part play, part artwork, but also a way to kind of for the public, for people who otherwise wouldn't dare look at a statement machine, a PetriNet, a data flow diagram. You know, I'd have the students would basically be trying to be explaining these things to everyone. So it's maybe it's a new type of art, you know, and I kind of look at the better student projects as art, art that is a kind of an information computing art that goes beneath the surface of, you know, here's some and here's a display, but we're going to hide everything in between those two things as a black box. So I definitely want to get,

I want to take, remove the black box, get inside of it. And, you know, a bit like Tron, I suppose, uh, creatively explore it. I love the idea of tricking the public into looking at CS and math models because they're beautiful. Absolutely. It's not a trick. I completely agree with that. It's not a trick. Yes, they are.

They are. Oh, no, I agree they are. But if you said, come look at my Lucky Vogue Terra system, people would be like, huh? And if you say, come look at my neat water thing with pretty lights and bubbly liquid, they might do it. No, it's true. Yeah.

And you're very into art and technology and the intersection. Yes. I've always been uh interested in that i almost did a dual degree undergrad in art and mathematics and i went with mathematics i guess because i could get a better job that way uh but i've always right yeah it it's important um but i've always been very, you know, I've done my own. I've done sketches. I used to do acrylics and oils. I never did sculpture, but I'm actually intrigued to do some sculpture with all the 3D printing and laser cutting.

We do own a laser cutter, and we have three 3D printers in the lab. So I'm becoming sort of reinvigorated with the whole idea of three-dimensionality. But yeah, always very interested in the intersection of art, science, and mathematics. I completely understand. I minored in art, so I totally understand. Although I don't get to apply much of the art during technology, while I do technology. And I think that that's fascinating.

Right. And that's partly, you know, I mean, that's the kind of reason why I went to UT Dallas is that they had this new building, you know, a 65,000 square foot building, which we reside in, and it's arts and technology. So it's a fairly substantial commitment to that intersection within a university. Why? I mean, that's an investment. It's a big chunk of change that could be used for anything. Why do they see it as important that people cross art and tech?

Yeah, that's great. So I would say, you know, like anything, it depends who you ask. But there are a couple, if you take a look at some of the things like game design, or you look at animation, or you look at sound design, those things naturally connect technology, science, engineering, and the arts, right? I mean, if you go work at an animation studio like Pixar, they're going to need teams of artists working with designers, working with sound people, working with story people, working with engineers. So it sort of combines, so things like gaming and animation are sort of natural seats for that intersection. And, you know, there's a lot of money to be made in that.

And I think there's also a lot of philosophical interest in that connection between art and technology. It seems like it's a great way to bring people in. I mean, we talked about tricking them into seeing equations they would never agree to otherwise. But it is a great way to get people interested in undergrad so that they want to do computer science. They want to do math and they don't want to... They recognize that these things do bring in more money for most people

and getting an art degree can lead to difficulty finding employment. Where are you headed with that? I really was headed somewhere and I have no idea. Can I just take it all back? Mostly that I am glad I stumbled into engineering, but I fear if I had stumbled into photography before engineering, I'm not sure I would have taken this path. Well, yeah.

Oh, go ahead. Sorry. and so yeah oh go ahead sorry and so the idea of having water clocks and and physical manifestations of algorithms as art it's just so much more fun to think about it that way well i think of it this way that you don't have to give up doing art just because you're in a technical field. You don't have to be a mechanical robot. You can apply technology to your art and vice versa. And I think that would dispel some of the stigma, not stigma, but the feeling that technology is boring for nerds. Lacks creativity, which it certainly does not. I think it's a good point.

A couple of notes on that. I guess one is that sometimes, I mean, one of my jobs, I feel, is to sort of say, they may look at me or what I teach or what I do, and they see naturally that I'm a technologist. But there's a problem with that, that if they don't, if they're not familiar with engineering, or science, or mathematics, those are areas that under they're within the shell of technology. If they just see me essentially, or people like me as a, as a computer screen with knobs, you know, as in, you know, that's sort of the end product, which is consumer oriented, then they're not seeing the deep connections that go underneath technology. You know, for those of us who are doing engineering, science, math, and so on in STEM areas, we take that for granted. We know that we do those and we know they're creative and they're really fascinating.

But a lot of people on the outside of that will just see what we do as technology. They'll just see the end product. And so one of my tasks, I think, is to break that stereotype and say, no, technology, we all use technology, right? But let me tell you about what cool things are going on inside the technology shell, that envelope. And so you said STEM, and I have heard this acronym STEAM a few times. How do you feel about that, where the A stands for art? Yeah, I'm a big advocate of STEAM bandwagon. And I've read a bunch of articles and so forth, I guess, like everyone. And I think it's a really, I think it's an important thing. We probably need more of a sort of arts-based appreciation within STEM. But likewise,

as we've talked about, we need the artists and the humanists to better understand that there's deep creativity and thought that goes behind the technology within science and mathematics. So it goes both ways. It's really important to kind of build the two-way street and include the, you know, arts and humanities as part of that. I agree. I mean, that was part of why I went to Harvey Mudd is it's a very humanities-based engineering college. And I wonder, actually thinking about them and how their computer science departments are really doing well with women, do you think having art as part of the curriculum, making it part of what they do, does it mean the students become more involved with their degree?

I guess I sort of mean, if you give them a task that's already been accomplished by everyone else, the Towers of Hanoi as a text-based program or whatever, but instead you say, but now you can do it in LEDs and you get a whole bunch of personal expression instead of just a simple task. Does that make it better for them? Even though it might be more work, it makes it more fun so they learn more? I think so. I would call that a personalized education, a personalized approach rather than one size fits all. And I am 100% behind that sort of approach, which is allowing people in the classroom, it would be allowing students to creatively explore their own representations and understandings of these things. I think that's absolutely critical. So, yeah, I think that's kind of behind – it was behind aesthetic computing and it's certainly behind the creative automata in what I'm doing in the university. So I think that's essential to allow people personal expression using different

media, which the arts are very good at, right? In computer science, you know, when I taught computer science only, you know, media is kind of a sort of an, you know, something you talk about in HCI, right? Or, you human-computer interaction, or perhaps in a multimedia class. But in fact, media should be part of every class. I mean, it should be just an integral part of learning mathematics and computer science. But it's, you know, you go to humanities and the arts, and they've got entire departments and labs and sections devoted to different media. So it's just, we've got these interesting cultural mismatches and miscommunications. And I think, you know, one of the goals of A-Tech, of arts and technology,

is to try and smooth those out, you know, kind of cross over the cultures, blend the cultures, understand one another better. So when you say media as part of the classes, blend the cultures, understand one another better. So when you say media as part of the classes, what do you mean exactly? Well, you could take photography or you could take video. Let's say, for example, I'll just give an example. Let's take an equation. Let's say I take Newton's second law. I say, okay, we've got Newton's second law.

We know that we can write it out. We know we can use LaTeX or we can actually write out the equation in notational symbols. But I could also say, okay, don't use symbols, use video. So video would be considered an art form or a type of media. And that's what I mean by media. Or I may say, symbols, use video. So video would be considered an art form or a type of media. And that's what I mean by media. Or I may say, okay, use the camera on your cell phone. Here's Newton's second law, but you don't get a pencil. You don't get any writing instruments.

You get a video camera or you get sculptor's tools. And all of these things are different media. They're different ways of representing things. I think probably in mathematics and computing, we grow up with the medium of typography, right? It's so natural to us, we don't often even think about it. That, oh, of course that's the way you represent it, with these funny-looking symbols. And so now we get back to Tron. Maybe if we need to kind of break out of that mold a little bit, think about different media.

When I say sculpture, know, sculpture, video, photography, sound, sound is a medium. Perhaps the medium of story, narrative, that could even be thought about as a medium, a medium for communication. Okay. That makes a lot of sense. So what you're saying is that someday I really should write a book that describes a computer algorithm, but with characters that have emotional impulses. I absolutely think so. Because you're just really good at that look today. Yeah, that's right. This is kind of strange stuff because, you know, when I teach students, I've been teaching them, what I do is I get half.

Half the class is from A-Tech or arts and technology. The other half is for computer science. So talk about strange looks. I mean, I'm combining both students in one class and I get them to work with each other. I think it works out really well, but it is a bit of a culture shock because the cultures are very different. It almost seems to me some sort of formalized synesthesia where, you know, you smell red or you taste five. I've always wanted to taste a five. I've never – but yeah, I know what you mean. Yeah, with synesthesia.

Yeah, I always read about that and say, gosh, I wish I could do that. And I wouldn't have to buy anything at the grocery store. But it is a twisting of what we expect and looking at things from a different perspective. And I think it's really useful. I mean, I'm just sitting here listening and thinking. And you were talking about Newton's second law by way of a video camera. And I was saying, okay, well, how would I do that? That's F equals MA for those of you who didn't look it up like I just did. You know, and okay, so I could push on a rock and I could push on a smaller rock and, you know, see the... Go watch people play pool. Okay. Or do the mousetrap with the marble coming down the slide?

But just thinking about it, I got a better intuitive sense of what that equation means. Yeah. Yeah, and I think it kind of brings us back to modeling as a sort of a general methodology, is that it's constrained creativity. Because I've said, all right, we're going to consider Newton's second law, but you've got to use it using this medium. So I'm constraining the situation, but by doing so, creating a disturbance, creating a friction. And so that's kind of what I'm after. I'm after sort of exploring that friction because, you know, on the hope that it may get people more interested in STEM. I have so many more questions to ask you, and I'm looking me wasn't spies, but I don't know if I believe you.

I have no idea where to go next. Which of those do you want to do, Chris? That was a really long list. I know. We could do another podcast later. We might have to. Yeah. No, I mean, I'm grateful for the opportunity.

Which of those would you most like to talk about? Well, of the things you talked about, gosh, it's hard to say. I suppose we could talk about Babbage's engine, only in that I recently saw the second model of that when I was in Mountain View. This was, I guess, about three weeks ago at the Computer History Museum. And boy, that place needs to be plugged because that's, uh, that, that was, I regarded as Mecca. Uh, I mean, it was just a fantastic place to be. And they had the, they, once a day they have a difference, the second difference equation being hand cranked. And that was just – that was brilliant. So, I mean, I just look at the – the things that Babbage did were just amazing.

And, in fact, I'm going to London in June, and this is for a conference in modeling and simulation. It's a society that I chair called SigSim. And there's going to be, there's a person there I'm meeting who's an expert on a diagrammatic data flow mechanism that Babbage created, but has not been published yet. So no one really knows about this except this guy and his PhD student. And so I can't, I mean, I can't wait to talk to him. And actually, there's, of course, a difference equation at the Kensington Museum in London, which I don't think, I'm not sure why they don't operate it. I think the fellow in Mountain View was saying that, you know, they've got the one in London, but nobody works it. But it's...

I've heard it's pretty fussy to work. And you say difference equation, but I think you mean difference engine. Sorry. Yeah, you're right. Why am I saying difference equation? It is difference. You're absolutely correct. It's difference engine.

So what you were saying about the diagrammatic language, and so it may be that Babbage created LabVIEW long before National Instruments. Oh, God. See, I was going to bring created LabVIEW long before National Instruments. Oh, God. See, I was going to bring up LabVIEW. Amazing. I was going to bring up LabVIEW as a pathological example of where this could go. Where analogies go wrong. Yes.

Because – Well, you know what's – Sorry, go ahead. Yeah. Oh, no, no. I was just going to say, speaking of LabVIEW, there's something, there's another package which I teach, which I've just started using to teach the arts and humanities students LabVIEW-ish kinds of stuff. And that is the Max MSP, which is a data flow and control flow language, but it's a data flow and control flow language for musicians, video jockeys, and video and artists. So that's a kind of, that's become interesting.

That's kind of, I've sort of moved away from things like LabVIEW and Simulink, at least, because, you know, you take a look at something like Max and it turns out to be an absolutely brilliant language in order to teach systems concepts, feedback, state, event, everything that we do in engineering. You can do all of that stuff there, but you get the added advantage of video and sound and synthesizer sounds and all kinds of super cool things.

Don't you think there are limits to that sort of language, though? I found with LabVIEW, especially on trying to do large, real projects with an industry, that once you got beyond a certain level of complexity, it was so much more difficult to work with than a traditional programming language. And so I worry that we can take this a little too far and neglect sort of the benefits of traditional representations. I agree. Okay.

And just so we kind of reel ourselves back, which we should do, and I'll just, since I was on talking about Max, and just so we kind of reel ourselves back, which we should do. And I'll just, since I was on talking about Macs, it's fully compatible and it's built on C, you know, and so I write C code in the objects and then some of the objects, if you build your own objects, it's all C. And so a lot of these things that we're talking about are don't, they don't replace programming and coding in the way that we understand it. They augment it.

And so I completely agree. But then the question is, where do you draw the line? In some cases, okay, you could make everything all text, and that's okay. Or you could make everything all visual, but presumably there's a, you know, we don't want to strike a balance somewhere, but as to how to define that balance, I don't, I don't know. There's no single answer to that. Yeah. I think there's definitely a place for both. It's just right. Like you said, finding the right, the right balance. Well, this goes all the way back to analogies.

That sometimes there are really good analogies, and sometimes there are analogies that are good for a part of the problem, but have some serious difficulties for the whole thing. And sometimes there are analogies we fall into using that actually aren't very good, and they confuse students because they leave out the details that make the thing, the thing. And instead we, we compare apples and oranges and they keep wondering why we want them to make orange juice out of an apple. And they're like, I don't know. So yeah. How do you find good analogies? It's gotta be, I mean, that that's a lifetime's worth of work, I think. I think it is. And if we just talk about analogies, there are, there are people who have been writing

about analogy, I mean, you know, academic kind of textbooks for 40 to 50 years. So, it's, I mean, it's a really interesting area that is analogy and metaphor. And so they've written about the same things. They've said historically, here are some analogies that people have used. I think as Chris has pointed out, the water analogy is something that's somewhat popular in describing inductance, capacitance, resistance, voltage, current, and so forth.

But Alicia, as you point out, with any analogy or with any model, there are going to be parts that don't work. And as far as how do you come up with them, I would still have to go back to it's a bit of an art. It's really an art form. There's no formula. There's no algorithm that I know of coming up with them. It's something that, which is kind of good, I suppose, that we can automate that anyway.

And that we, it's just part of the creative act. Well, and then I get to go back to my Darwinism in pedagogy that if we make good ones, they will outlast us. And if we make bad ones, they will die because people won't have any idea what we're talking about. Okay. And that actually, that describes it better for me. Now I kind of understand a little bit more where you're coming from. And yeah, I would say that's true. Good ideas tend to propagate as in species in evolutionary biology. And so, yeah, I think that absolutely makes sense. But I suppose now and then, even bad analogies somehow, maybe that's the platypus or something, you know. I don't know what it would be, you know, pick your, you know, the least favorite species. But, right, I would think most of the time, the good things, just like good knowledge, it tends to be propagated and repropagated and put

in textbooks and re-communicated and the poor things just end up going away or they get put into the dustbin of history as something bizarre that somebody thought of 200 years ago. Oh, string theory is definitely the platypus of physics. Yeah. No. It's fine. Okay, so the Computer History Museum. I totally agree.

I used to work not too far from it, and the admission then was free, so I would go over for lunch whenever I wanted to visit the really great computers. If you are in Silicon Valley, you should check out the Computer History Museum in Mountain View. And if you are going to be here for the 30th anniversary of the Amiga on Saturday, July 25th, the Computer History is having just a huge shindig, and there's a Kickstarter to fund the party. So check that out. I'll put the link in the show notes.

And then I think we're almost out of time. Wait, wait. I had a question. Oh, good. What do you have? So this is all extremely interesting, and I'm actually charged up to learn more. How does somebody who is not in academia and can't take a class and has been doing technical things for a long time. How can we learn more about these ideas? Is there stuff to read or good places to go?

Yeah, there's some things to read. Yeah, there's, well, I could provide, first of all, I can provide some links to you guys if you think that would help. Oh, please. And I can do that after the show. Also, there's a book I edited in 2006 called Aesthetic Computing. It's MIT Press. And that has some ideas from various artists and mathematicians.

And I've got a chapter in there. So I think there's a lot of interesting ideas about what we've been talking about there. And so collect, I think, the links that I provide and maybe that book, and perhaps going to, you know, I have a blog called creative-automata.com. And, you know, there's some of these, some of these ideas are sort of in there in some of the blog entries. And so, you know, plus we're trying to do more videos and stuff.

Oh, I do have a, and again, this isn't meant to be self-promotion. I do have a TEDx talk that I did last year. But that talk was more about seeing information rather than this sort of engineering art side of the synthesis side of creating something. But still, people might be interested in that. It's I think if you and I can I can give you guys the link for that if you're interested. But it's TEDx and then my last name, you know,, you should be able to find it. Cool. Very cool. And you do a lot of public outreach, including this podcast. Why? I do it because I feel that we all need, faculty at universities need to do public outreach for a couple different reasons. One is that

we do research, but the question is, once we do our research, how do we get it to other people? One way is to write papers, but academic papers may reach 10 people because we have small clusters of people that we consider our peers. But I think it's critical that we also talk to each other within the university and also talk to the public. I mean, there are others, of course, there's the taxpayer reason too. I mean, if you're in a public university, taxpayers are paying part of your salary. So I think it behooves us to give back and say, here's what we're doing in a way that's understandable. So I guess in a general way, I'm trying to democratize knowledge, just as you're trying to do with a podcast and Khan Academy

is doing and so forth. I think it's extremely important. And it shouldn't, knowledge shouldn't be something that's just limited to 10 people on the planet. So that's why I'm doing it. Excellent. Thank you very much. Do you have any last thoughts you'd like to leave us with? Yeah, I was thinking about that, because I know you do that every podcast. So I've got, I'm sitting here thinking about Alice in Wonderland and the phrase where the queen says, why sometimes I believed as many as six impossible things before breakfast. And so that's what I would advise to listeners is that before breakfast tomorrow morning, I want you to think of six impossible things. I like that a lot.

All right. Thank you so much for being on the show. My guest has been Dr. Paul Fishwick, Distinguished University Chair of Arts and Technology and Professor of Computer Science at the University of Texas at Dallas. Thank you also to Christopher White for co-hosting and producing. And we're going to be at 100 episodes soon, which is sort of odd since we started out with the idea of doing six. I want to put together a list of five good starter episodes for people new to the

show. What do you think I should include? Definitely Jack Gansels on being a grown-up and Chris and mine on the imposter syndrome because those are two of my favorites. But what else? So email or hit the contact link on embedded.fm to let me know. Also, if you'd like the solid coupon or the party invite for LA on May 9th or 10th, hit that contact link or email embedded at, no, wait, wait a minute. Email something. Show at embedded.fm. That's it. Email show at embedded.fm. And now a final thought I have too, because I came up with one during the show and I can't really stop myself. The first one is from Dykstra.

Computer science is no more about computers than astronomy is about telescopes. And the other one, which seems really appropriate for a show about analogies and metaphors. Tarmac and Jalad at Tanegra. Yeah, you can email and tell me that that's terrible.