WEBVTT 00:00.000 --> 00:09.120 Everyone, welcome to the Noob Show. Today I am joined by Matt Heunerfauth, the Dean of 00:09.120 --> 00:16.020 the Galicano College of Computing and Information Science at RIT. In this, we talk about the 00:16.020 --> 00:21.280 value of education, how AI is changing the landscape, asking alumni for money, and so 00:21.280 --> 00:31.440 much more. Joy. Two million people in the audience. No, so I've got one of these fancy 00:31.440 --> 00:36.280 mugs, right? These like Ember mugs that keeps your coffee hot. And I used to be against 00:36.280 --> 00:41.240 it because, one, it's an expensive mug and two, it's like if I'm not drinking the coffee 00:41.240 --> 00:46.400 fast enough, what's the point? But it doesn't prevent it from spilling all over my keyboard, 00:46.400 --> 00:50.840 which I just did. So it's good now. It's good now, but I definitely spilled it everywhere. 00:50.840 --> 00:56.200 You need like a sippy cup version, apparently. Yeah, I do need a sippy cup version. Actually, 00:56.200 --> 00:59.560 fun fact, I met there's a there's a product out there called the Mighty Mug, and it's 00:59.560 --> 01:04.520 one of those mugs where you can't knock it over. Have you seen that wobble? Like one 01:04.520 --> 01:09.880 of those little kids sort of? Yeah, but it like it has like this suction cup device on 01:09.880 --> 01:15.240 the bottom. And so when you hit it from like above 10 or 15% of the you can't knock it 01:15.280 --> 01:20.920 over because it like stays suction to the and I met the guy who co founded that last 01:20.920 --> 01:27.240 weekend coincidentally. But you know, doesn't help me not having one. So how's your how's 01:27.240 --> 01:32.920 your day going? Doing pretty good. Yeah. That's good. It's a snowy day here in Rochester, New 01:32.920 --> 01:40.000 York. Is it snowing? Yes. Well, slowly calming down. Yeah. Okay, I don't necessarily miss 01:40.000 --> 01:46.840 that. But have have have there been any snow days like in the past couple years, like who 01:48.480 --> 01:54.200 you know, it's probably been about four or five years. But the first winter I moved up 01:54.200 --> 02:00.960 here to Rochester, it was a pretty cold one. It was like 2014. And I think they might have 02:00.960 --> 02:08.360 called off twice. But of course, it's not day. Oh, no, no, no, back in 2014. I think, you know, 02:08.400 --> 02:12.600 it wasn't the snow. It was just it was so cold. They were worried about folks going to 02:12.600 --> 02:18.760 school and things like that outside. But no, this year, this year, nothing much. So when I was 02:18.760 --> 02:29.160 there, from, I think we had one, it was during finals, which was awesome. One final got postponed 02:29.160 --> 02:33.440 to the New Year because there was like six feet of snow that just dumped overnight or 02:33.440 --> 02:38.160 something crazy. But that was the only time ever and it was only after two o'clock and the 02:38.160 --> 02:43.360 exam was at like 215. So we got really lucky. Discrete math exam. I don't know if I was ready 02:43.360 --> 02:47.120 for it. But I don't then again, I don't know if I was ready for it after the New Year. 02:49.640 --> 02:51.680 Just got to worry about it all over Christmas. Yeah. 02:52.520 --> 02:57.240 I know that's the worst, right? That's why I like doing them before. Are then our students in 02:57.240 --> 03:03.280 exams right now? They are. Yeah, it started halfway through last week, and it finishes up on 03:03.280 --> 03:12.280 Friday. Okay, okay. So you joined RIT in 2014. I did. Okay. What, what, why the switch to RIT from 03:12.280 --> 03:19.040 from because you were in New York City before, right? Yeah, so I started my career as a faculty 03:19.040 --> 03:27.040 member at City University of New York back in 2006. And then I started everything there and in 03:27.080 --> 03:35.200 Queens College was where my laboratory was. You know, I think my my area of research has always 03:35.200 --> 03:41.640 been using AI technology to try to make useful applications for people who are deaf and hard of 03:41.640 --> 03:47.800 hearing. And so being in a big city like New York, there was lots of people. So that meant that you 03:47.800 --> 03:52.400 certainly could recruit like people who are deaf and hard of hearing to kind of test out some 03:52.440 --> 03:59.600 technology you made or do some experiments or something. And I even used to like run a summer 03:59.600 --> 04:05.040 program there for high school students who were deaf and hard of hearing, so that they could kind of 04:05.040 --> 04:09.120 get like a little research experience over the summer, get them kind of excited about computing 04:09.120 --> 04:15.400 and things. The trouble was, I mean, you know, I think during the summertime when I ran that 04:15.400 --> 04:21.880 program, like the language of my laboratory became sign language, and I would sign and we could 04:21.880 --> 04:27.640 recruit a lot of folks. But then during the rest of the academic year, it wasn't like that, like 04:27.640 --> 04:35.040 there weren't deaf students of any significant numbers at the university. And although I could 04:35.040 --> 04:40.120 get really good computing students to work at the lab, and I could get some great deaf students to 04:40.120 --> 04:47.160 also work at the lab at other times to like recruit folks, I couldn't quite crack the thing to figure 04:47.160 --> 04:54.480 out how to get like a great deaf computing student to be working at my lab. So, you know, back in 04:54.480 --> 05:03.800 2014, a job advertisement was forwarded my way for an opening at RIT. And of course, I knew what 05:03.800 --> 05:09.920 RIT was, I mean, working in, you know, deaf technology, everybody knows about NTID and a 05:09.920 --> 05:15.720 thousand deaf students on the RIT campus because of the National Technical Institute for the deaf 05:15.760 --> 05:23.560 there. And I had visited before. And like the job ad, I read it, and it sounded like somebody wrote 05:23.560 --> 05:30.480 it for me. Like it was, Oh, we're looking for a mid career faculty member to come and join RIT and do 05:30.480 --> 05:38.240 research on accessibility technology for people with disabilities. And I was like, Okay, I have to 05:38.240 --> 05:42.920 apply to this. I was happy in New York City. I wasn't planning to move in. But when I when I saw 05:42.960 --> 05:52.000 that, it just got exciting. Yeah. And I think the big two differences when I moved to RIT, the first 05:52.000 --> 05:59.120 one was because there's all of these really skilled sign language interpreters and a lot of support 05:59.120 --> 06:05.960 services and things like that on the campus. It was really possible to recruit deaf and hard of 06:05.960 --> 06:12.200 hearing master students and then PhD students and have them be successful at actually doing a PhD 06:12.240 --> 06:20.880 here. It's also a place where you can go put up a poster, hang it up on a wall and say, Hey, we need 06:20.880 --> 06:26.840 35 people to like do an experiment, we need 35 deaf and hard of hearing people to do an experiment to 06:26.840 --> 06:33.520 try out some pieces of software we need. And you could have a list signed up in a day. And after all 06:33.520 --> 06:38.840 of the logistical things we used to go through, even in New York City to try to recruit people to test 06:38.840 --> 06:45.120 things out. That was just amazing. And that really like accelerated stuff. So yeah, that that was the 06:45.120 --> 06:48.240 big reason for the leap. Because of the research field I did. 06:49.280 --> 06:59.640 Yeah, that's great. I think it's fascinating. And so but the person who sent you the job posting, did 06:59.640 --> 07:02.120 they read through your 45 pages of resume? 07:02.880 --> 07:13.920 Perhaps. So yes, we have a 45 page resume. Well, in my defense, it's it's 07:13.920 --> 07:17.000 here we go. This is the academic in a club. 07:18.920 --> 07:27.240 It's a thesis review, right? So and grad students that that work in computing or are studying, we 07:27.240 --> 07:32.720 teach them how to create a curriculum vitae, basically a really long resume, that absolutely 07:32.720 --> 07:38.160 everything you have ever done as an academic gets in there every paper, every every little thing. 07:39.560 --> 07:44.400 And yep, mine is a exciting page turner of 45 pages. 07:45.960 --> 07:51.000 Do you feel like a badass? Like you go to like kinkos, you print out 45 pages, and then you just slam it 07:51.000 --> 07:53.360 down during the interview, you're like, right? 07:53.920 --> 07:58.520 I haven't tried that one yet. Because mine, mine's like a mine's like a feather. 08:00.200 --> 08:00.880 What was that? 08:03.920 --> 08:08.800 And I mean, you know, something that I often like talk about with students when we're trying to like, 08:08.840 --> 08:13.640 you know, write a paper on something, it's a lot easier to write something that's too long than it 08:13.640 --> 08:18.520 is to actually write something that's short. So actually, the challenge of compressing something 08:18.520 --> 08:24.760 down into just a couple pages, that's really tough. I don't, I don't know. If I ever wasn't doing 08:24.760 --> 08:30.920 academia, and I had to have like a normal resume, compress that thing down to two pages, I don't 08:30.920 --> 08:40.040 know. Well, I mean, that's a great segue into our friends in the AI world would using AI to do 08:40.040 --> 08:42.800 that. That sounds like something that's very common and likely. 08:43.240 --> 08:51.320 It is indeed. I mean, that. So, you know, I feel like during my career, I've gotten to see a couple 08:51.320 --> 08:59.960 different interesting leaps in what computers can do. Certainly, I started studying computing well 08:59.960 --> 09:06.920 before, you know, smartphones and having a computer in your pocket was a thing. And as someone who 09:06.960 --> 09:13.840 studies how people use tech and evaluates whether anything's a good idea and you tested out with 09:13.840 --> 09:18.480 people, the idea that you have another platform like that to do things is really exciting. It opens 09:18.480 --> 09:25.760 up new applications. But then after I started doing work in creating technology and software for 09:25.760 --> 09:30.640 people who are deaf and hard of hearing, a lot of it was about speech and language tech. So some of 09:30.640 --> 09:38.240 it was on tools to make sign language animations or things that tools that could allow for automatic 09:38.240 --> 09:43.840 creating of captions with speech. Yes. And so the second big leap was really maybe about a decade 09:43.840 --> 09:52.120 or so ago, when there was a lot of new neural network based approaches in artificial intelligence. 09:52.400 --> 09:59.040 And there was another just huge leap in performance. And I think suddenly technology like 09:59.040 --> 10:05.200 automatic speech recognition that had always been a little bit niche, like, you know, you could get 10:05.200 --> 10:11.000 like drag and naturally speaking, you could go train it for a long time and use it to your own 10:11.000 --> 10:19.240 voice. Suddenly, about 10 years ago, it started to really become seriously powerful and accurate 10:19.240 --> 10:26.360 enough that I got really excited and started to shift a little more my focus at our laboratory 10:26.360 --> 10:33.280 towards automatic captioning tools. So could you have a meeting like this and auto automatically 10:33.280 --> 10:38.680 have the captions appear, or have somebody go to a lecture and do it? And you know, 10 years ago, 10:38.680 --> 10:44.200 that sounded a little bit iffy, because everybody was was thinking about speech recognition from the 10:44.200 --> 10:49.560 way it had been before this. And so the kind of work we were doing was, okay, this is probably 10:49.560 --> 10:54.080 going to be awful, but how could we make it better for people, right? Could we could we indicate in 10:54.080 --> 10:59.040 the captions, when the tool isn't quite confident of the word it heard, and then maybe that would be 10:59.040 --> 11:05.520 useful for the user and stuff like this, it got better, the tech got better. And suddenly we could 11:05.520 --> 11:12.280 do all these powerful things with those neural based AI techniques. I feel like this is now like the 11:12.280 --> 11:20.760 third leap is all of this generative AI stuff. The I mean, some of it we folks that do, you know, 11:20.800 --> 11:26.080 technology and speech and language had seen large language models for a long time. And we had kind 11:26.080 --> 11:31.000 of known like, these things can look a little bit magical when you interact with them. But the idea 11:31.000 --> 11:36.320 that suddenly it's actually like out there and people are experimenting with it and trying to use 11:36.320 --> 11:42.720 it in all sorts of different ways. That's I think the exciting thing. So similar to that first leap I 11:42.720 --> 11:48.280 mentioned of the smartphone in your pocket, suddenly everybody was trying it out, using it in a new 11:48.320 --> 11:53.640 way, figuring out in their day to day life what they might do with it. It made this ecosystem of 11:53.640 --> 11:59.640 people making apps for these devices, because it would fill these different needs. I think that's 11:59.640 --> 12:05.880 kind of what we've just seen with the generative AI. And so as you said, could I could you get a 45 12:05.880 --> 12:10.680 page resume down to two pages? I haven't tried it yet. But yeah, I'll give it a whirl after this. 12:10.680 --> 12:18.960 Yeah, buffer overflow. Yeah. And I also think, you know, we've a lot of during my career, we've been 12:18.960 --> 12:24.680 studying like how to make like custom AI tools for people with disabilities to do different things 12:24.680 --> 12:31.120 like, I don't know, like, simplify text, if you have trouble reading text, for example, well, the idea 12:31.120 --> 12:37.400 that there's now almost this like utility knife of an AI tool that can do all these things like 12:37.400 --> 12:44.360 summarize things, simplify things, reorganize things, that's going to be really interesting in 12:44.360 --> 12:50.280 many applications, but also in tech for people with disabilities. Because now it's something that's 12:50.280 --> 12:56.920 in every web browser, or you could add chat GPT or whatever else to anybody's phone. And you don't 12:56.920 --> 13:03.640 need a custom specialty app or whatever, you can use the same thing everybody else is using, but 13:03.720 --> 13:11.320 there's all these interesting ways to use it. Yeah, totally. So that, you know, actually, I use whisper, 13:11.320 --> 13:16.120 which was one of the open AI products to transcribe all the audio for this podcast. And then I upload 13:16.120 --> 13:24.040 those and I try to timestamp them to so you can say, at two minutes and 47 seconds, you know, well, 13:24.040 --> 13:27.960 Matt was talking, it's easy in this situation, because it could be half wrong, which Matt, but 13:28.920 --> 13:34.520 and then you can like go to that, or you can just see the text and it works for a number of reasons. 13:34.520 --> 13:39.880 It's not just for, I know the accessibility is huge, but for SEO, for example, if you're searching 13:39.880 --> 13:45.720 on a particular topic, and you can see, oh, we're talking about accessibility or talking about AI, 13:45.720 --> 13:49.480 you can go right to it, and then you can listen in or you can read where it was. So I think it's 13:49.480 --> 13:59.160 pretty cool. Speaking of AI, how is school, how's RIT? I mean, you're the big boss now. How is RIT 13:59.160 --> 14:05.560 embraced AI? Like, you know, I'm sure there's tons of things to think about. There's potential, 14:07.000 --> 14:12.360 you know, everything from cheating to AI pulling in, you know, if you're helping it with a paper 14:12.360 --> 14:17.800 or with code, you know, using source code that may not be open source or licensed properly, like, 14:17.800 --> 14:22.200 but also it's such a great tool. So I'm really, really curious to know, like, how is RIT embracing AI 14:22.200 --> 14:27.080 and what do you, how is education doing that? Well, you call me the big boss. What I'll say is 14:27.080 --> 14:32.760 about two years ago, I crossed more into the academic leadership side of things. I became the 14:32.760 --> 14:38.440 Dean of our Golisano College of Computing and Information Sciences, of which I know you're an 14:38.440 --> 14:46.920 alum. And so asking about sort of, you know, what has RIT been doing in AI? I think actually, 14:46.920 --> 14:51.880 the story is a little bit longer than just kind of the excitement about the generative AI very 14:51.880 --> 14:59.400 recently. So, you know, when I think about sort of the portfolio of all the different areas of 14:59.400 --> 15:05.720 research that the faculty in our college do, really the trend over the past 15 years has just 15:05.720 --> 15:13.160 been a bigger piece of the pie being AI. Or folks that were doing work in some other area of computing, 15:13.880 --> 15:19.240 suddenly there's an AI methodology to what they're doing as well. So they might be working in 15:19.240 --> 15:26.840 cybersecurity, software engineering, some other area, but just about everything has like an AI 15:27.400 --> 15:32.760 twist to what you can do. And that's kind of some of the exciting frontier in many ways. 15:32.760 --> 15:41.240 So there's that progression. In the curriculum side of the house, students clamor for AI courses, 15:41.240 --> 15:45.720 right? So those AI courses, the machine learning courses, they fill up real fast, right? 15:45.720 --> 15:48.680 Yeah. Everybody's on the course registration system trying to get into those. 15:48.680 --> 15:52.280 Back in my day, the classes that fill up quickly were like wines and beers of the world. 15:53.640 --> 15:59.240 Well, that one too, but you know, I think it's neck and neck with an AI class nowadays, if that 15:59.240 --> 16:04.600 tells you something. That says a lot. And so, you know, slowly what we've been doing is kind of just 16:04.600 --> 16:09.880 adding more in the core of the degree programs, because we just realized everybody was picking 16:09.880 --> 16:15.720 it as an elective. But you know what, this is now fundamental to being a computing professional 16:15.720 --> 16:22.280 nowadays, to have some of this sensibility about artificial intelligence. So much so that we even 16:22.280 --> 16:26.440 made a whole master's degree in artificial intelligence that opened this year. Now we've had 16:26.440 --> 16:30.360 other ones where I mean, you could do a master's in computer science and just fill up your courses 16:30.360 --> 16:35.960 with a bunch of AI courses. But I think just as another sign of the times, we've created this 16:35.960 --> 16:42.440 whole new program that's a master's in AI. I think maybe where you were starting with the question 16:42.440 --> 16:47.160 though was what has happened with this whole generative AI, because now you can have it to 16:47.160 --> 16:53.480 your homework, right? So I mean, where a lot of folks, I mean, I think a lot of the press about 16:53.480 --> 16:59.800 this has been about like, Oh, no, is this the end of the essay or something like that, writing essays 16:59.800 --> 17:05.480 in college or something. And I think there is a lot of worry about what happens when it's really 17:05.480 --> 17:14.760 easy to generate fluent text in that way. What has a lot of us pondering what we're about to do next 17:14.760 --> 17:20.760 in pedagogy is actually the fact that this stuff can write computer code too, right? Yeah. And you 17:20.760 --> 17:26.680 might if you read some English texts that these things generate, sometimes you can sort of tell 17:26.680 --> 17:29.960 sometimes you can tell a little bit about style, it's getting so good that actually it's hard to 17:29.960 --> 17:37.720 tell. But when it generates computer code, it's trained to make it look really fluent. And the 17:37.720 --> 17:43.480 trouble is, if there's a bug in that code, it's insidious. I mean, the code will look beautiful, 17:43.480 --> 17:51.640 but there's a terrible flaw in it sometimes. So, but it works pretty good on introductory courses. 17:51.640 --> 17:57.480 So what we're now facing is how do we help educate a whole nother generation of computing 17:57.480 --> 18:03.160 professionals, where there's now a tool that you literally can give it your homework assignment 18:03.160 --> 18:07.960 for an introductory programming class, and it does a pretty good job. Yeah. And the trouble is the 18:07.960 --> 18:14.840 output is computer code, right? So it's actually a little tough to catch. Oh, yeah. This is the 18:14.840 --> 18:20.680 topic of a lot of faculty meetings around the college. You know, where I think we're headed. 18:20.680 --> 18:27.160 Well, what we're doing this year, this year, in our college, the rule is, if a faculty member 18:27.160 --> 18:33.720 is teaching a computing course, you have to say something in your syllabus about what your policy 18:33.720 --> 18:39.880 is on whether you can use generative AI or not or for what assignments. And if like you've got 18:39.880 --> 18:43.560 like a course where everybody's teaching like five different sections of the course because 18:43.560 --> 18:47.400 everybody needs intro to programming, you have to have the same policy across them. 18:47.960 --> 18:52.760 But we're treating this semester as a bit of an experiment to kind of encourage faculty to 18:53.720 --> 18:58.120 someone to embrace it, someone to be like, Oh, no, don't use it. That's cheating. 18:58.120 --> 19:03.640 We're, we're trying it all. We're a big college. So we've got about 5000 computing students. 19:04.200 --> 19:09.480 So we can also try this strategy a little bit of, let's try a bunch of things. Let's see what 19:09.480 --> 19:13.720 works something something's going to take. And then this spring, we're going to bring it back 19:13.720 --> 19:18.200 together and have a lot of conversations among faculty about what worked, what didn't work. 19:18.600 --> 19:24.920 You know, early directions that I'm hearing from faculty is if it's an introductory course, 19:25.560 --> 19:29.480 we really have to do something to make sure that folks are able to code themselves. 19:29.480 --> 19:35.560 And maybe that means like more activities in the classroom, live things, that kind of stuff. 19:36.760 --> 19:42.280 As folks get more senior though, through their degree, if they don't know how to use these tools, 19:42.280 --> 19:46.920 that's actually a problem. I mean, they need to be able to do this and use co-pilot or any of these 19:46.920 --> 19:52.520 assistive tools when they go out in the profession. Yeah, 100%. And it's funny, all the things that 19:52.520 --> 19:57.720 you've mentioned resonate so much with me. So the, I was, I use co-pilot a lot. I've been using it 19:57.720 --> 20:02.440 throughout, I was using it throughout the beta and I pay for it, which is the, which is GitHub's 20:03.400 --> 20:11.480 like code, Gen AI on, and it's 100% built on top of open AI. And it wrote some JavaScript code for 20:11.480 --> 20:16.200 me. And I'm like, why doesn't this, I couldn't think about why it wouldn't work for a good 10 20:16.200 --> 20:20.760 minutes. And I was like, pulling my hair out. And I'm not reading it and reading it. And like, 20:20.760 --> 20:26.600 if I didn't know that, you know, about like, you know, like hoisting variables and JavaScript, 20:28.280 --> 20:32.200 I probably would have just given up, but I recognized, I was like, wait a minute, that part's 20:32.200 --> 20:39.160 wrong. So I rewrote it, right. And now it's beautiful. But what I love about it so much is 20:39.880 --> 20:44.760 it's helped keep me fresh. And it's helped teach me things that maybe I've forgotten or didn't know. 20:45.560 --> 20:49.880 Because I can select some, I can, it's kind of weird, like it can be very, very lonely, 20:49.880 --> 20:54.840 but my friend is now is chat GP is GitHub co pilot, because I could select some code and I'd 20:54.840 --> 21:00.760 be like, explain this, or why am I getting this error? Or how would you make this better? Like, 21:00.760 --> 21:05.480 so you have a function or a method or whatever that's ginormous, how would you make this cleaner? 21:05.480 --> 21:08.280 How'd you make this better? And it can tell you and it can be like, I think you should do it this 21:08.280 --> 21:15.400 way. And you can accept the rejected. I find it to be really fascinating. But also, I think that 21:17.160 --> 21:20.520 personally, I think that you do need to have some fundamentals of understanding how, you know, 21:20.520 --> 21:28.680 computer science works. And in a lot of fields, the way that you help to cultivate somebody to 21:28.680 --> 21:35.560 be an expert is you usually start with showing them a lot of examples of products that other 21:35.560 --> 21:40.680 folks have produced. So for example, if you want to teach a model, sort of, I mean, 21:41.400 --> 21:47.160 if you want somebody to be a great creative writer, you would have them read a lot of literature and 21:47.160 --> 21:52.360 talk about the literature, talk about the writing, similar in many of the arts, right? You would look 21:52.360 --> 21:59.400 and consume and critique a lot of it. Historically, that has not been a way that we think about 21:59.480 --> 22:06.520 education in computing. But that idea of being a discerning critic of something that might not 22:06.520 --> 22:13.320 be perfect or something that could be improved may need to be more about how we think about and 22:13.320 --> 22:19.160 start teaching computing. If what it means to be a computing professional is also working with these 22:19.160 --> 22:28.520 AI tools that sometimes are producing beautiful looking but wrong code. I mean, we see this in 22:28.520 --> 22:35.000 the profession, if you think about code review, or sometimes like pair programming kind of things, 22:36.120 --> 22:41.080 and maybe sort of, you know, chatting with your buddy, chat GPT or co-pilot while your code is 22:41.080 --> 22:48.280 wherever my rubber duck programming ran away. But like that, that idea of sort of like, be a 22:48.280 --> 22:53.720 critic, be able to kind of consume something that's not quite right, I think is going to have to be 22:53.720 --> 22:59.080 an earlier and really important part of computer programming nowadays. I think that used to be 22:59.080 --> 23:04.840 something that happened later in the training of somebody, maybe when they took a software engineering 23:04.840 --> 23:09.160 course near the end of their computing degree or something, and they learned how to work with a 23:09.160 --> 23:15.320 bigger team of people, maybe they would get into code review and stuff like this. But yeah, I think 23:15.400 --> 23:16.760 it's become the new skill. 23:20.760 --> 23:25.160 This might sound like a sort of a strange analogy, but it's very, I think to me it works. 23:26.280 --> 23:31.720 When I learned how to, before I knew how to use a debugger, I was doing like, you know, 23:31.720 --> 23:36.520 print statement debugging. And once I learned how to use a debugger, I was like, this feels like 23:36.520 --> 23:42.040 cheating, and I'm 10 times better now. And I think AI for me is also helping me get there. Like, 23:42.120 --> 23:45.720 it's not going to solve all the problems, but it's going to help me become more efficient, 23:45.720 --> 23:50.760 less, you know, use less of my own energy, right? Like I'm sort of more of the conductor than I am 23:50.760 --> 23:56.760 the, you know, the guy tightening the guitar strings, or that's a terrible one. But you know 23:56.760 --> 23:59.880 what I mean, like I'm more of the chef than I am the cook that's just flipping burgers. 24:01.240 --> 24:05.320 And so I find, to me, that seems much more interesting because I love creating stuff and 24:05.320 --> 24:09.960 the faster I can create things, the better, I think. Well, that debugger analogy is interesting 24:09.960 --> 24:16.280 because that actually comes up in a lot of discussions and debates about how we ought to 24:16.280 --> 24:23.720 be educating the next gen of computing professionals because, you know, one way of thinking about 24:23.720 --> 24:31.240 how we approach chat GPT or tools like co-pilot from an education perspective is, well, maybe we 24:31.240 --> 24:38.200 should introduce it early on, but then maybe we don't do a ton of hand holding throughout an entire 24:38.200 --> 24:44.520 degree. Instead, we just try to build some competency in it. And then we let the students 24:44.520 --> 24:50.280 use it if they want or figure out their own style of using it. And in many ways, that's more analogous 24:50.280 --> 24:56.520 to how debuggers are treated in the curriculum for a lot of computing programs nowadays. 24:56.520 --> 25:01.080 Some early course or two, you might get taught how to use your debugger. But in general, you're 25:01.080 --> 25:05.400 not going to hear like professors bring it up a lot during your whole degree. They're just going 25:05.480 --> 25:10.600 to kind of assume like you figured it out. Like you showed you what a debugger was. If you needed 25:10.600 --> 25:17.800 it, you'll use it. And maybe that's where this is headed with co-pilot. I don't know. I think 25:17.800 --> 25:23.480 I feel like we're kind of searching for models or analogies that might help us. And a lot of the 25:23.480 --> 25:29.320 ones that I hear about things like chat GPT are stuff like, oh, it's like the calculator. And, 25:29.320 --> 25:33.960 you know, when calculators were invented, it didn't stop the need for math classes and everybody 25:33.960 --> 25:39.400 was worried about them at first. But, you know, we figured it out. Maybe we'll get there. Maybe 25:39.400 --> 25:45.240 it's a calculator. Or maybe it's like how we do debuggers. I don't know. Or it's going to flip 25:45.240 --> 25:49.160 the whole field upside down. I don't know. I think there's a couple of different ways that this could 25:49.160 --> 25:57.720 go. I just, I just can't wait to like, like, you know, tell, you know, I used to write my code 25:57.720 --> 26:01.800 with, you know, hole punches and paver like, man, you sound old. And now it's like, I used to write 26:01.800 --> 26:06.120 my code by hand. Like, there was no AI back in my day. And you're like, wow, you're really old. It's 26:06.120 --> 26:13.320 like, it's like, where are we going to be? You know, anyways. Okay, so I'm curious about education 26:13.320 --> 26:18.920 in general. And, and, you know, obviously, AI is a big thing. And I think at all levels of 26:18.920 --> 26:22.760 education, that's being, you know, high school, middle school, I don't know, maybe elementary 26:22.760 --> 26:27.640 school. There's been a lot of talks about that. But I'm curious what you think the, you know, 26:27.720 --> 26:32.840 what are the current trends in computer science education, and what impact they have on students? 26:33.880 --> 26:39.400 Yeah, so I mean, you know, the big answer on that one is what what's about to happen with AI, 26:39.400 --> 26:45.400 right? So, but I'll set that aside for a moment. Other trends that I've been seeing in computing 26:45.400 --> 26:54.680 education is an approach to the field that really thinks about how computing needs to be considered 26:54.760 --> 27:02.280 in the way that it intersects with other disciplines. That, you know, we we use computing 27:02.280 --> 27:08.360 to do things. And at times, you also need to provide training and education to somebody 27:08.360 --> 27:13.880 that more explicitly gives them competency in a second field as well. So you see examples of this 27:13.880 --> 27:18.520 at some universities that have degrees that are sort of computing plus something else. 27:19.080 --> 27:25.720 I think we see trends of an increased awareness of the importance of electives 27:25.720 --> 27:29.400 and minors and things like that that a student would take along the way, 27:29.400 --> 27:34.760 where they figure out maybe a sub industry or field where, yes, they want to use computing 27:34.760 --> 27:38.360 to do something, but they want to also know about this other intersection with the world. 27:39.640 --> 27:45.240 So at RIT, all students have to do something called an immersion. It's kind of like a miniature 27:45.240 --> 27:49.480 minor where you got to take a couple courses to get a little bit of depth into something. 27:49.480 --> 27:53.000 And then usually you take two more classes, you get a minor, right? There's there's things like 27:53.000 --> 27:57.880 that that you can do if you really got interested. There's the carrot. Yes, yes. You're so close, 27:57.880 --> 28:04.360 just two more classes. The the other side of that, I think is, you know, there's been a lot of 28:04.360 --> 28:10.760 research on what really draws people to the computing field. And I think there are some 28:11.080 --> 28:16.680 students where, you know, they get really excited about tech in high school, or they think of 28:16.680 --> 28:21.800 themselves as like a tech person or a computing person. And they know, like they know they want 28:21.800 --> 28:28.360 to go to university and study computing. I think there's a lot of other folks that we're not catching 28:28.360 --> 28:34.600 yet in the computing field that would be awesome in the field, but we're not capturing their 28:34.600 --> 28:41.480 imagination or attention yet. Because we sometimes present the field as like a puzzle, a techie thing, 28:41.480 --> 28:49.080 a cool gadget, a futurist kind of thing. Whereas in reality, you know, computing changes the world 28:49.080 --> 28:55.400 in many different ways. And it's a powerful way to change the world. And so reframing the field 28:55.400 --> 29:03.000 with that interdisciplinary view of how does computing allow you to address social problems? 29:03.000 --> 29:08.680 How does computing allow you to do things that benefits people, improves lives? Yeah, 29:08.680 --> 29:13.000 research has shown that that resonates a lot more with students that are currently 29:13.000 --> 29:18.200 underrepresented in the field. So women, people of color, people with disabilities. 29:20.280 --> 29:27.000 And so, you know, our our college, for example, if you do the the wayback machine and take a look 29:27.000 --> 29:32.360 at our college website over the years, a trend you might notice is that now we kind of frame our 29:32.360 --> 29:38.280 college as we prepare students to improve lives and change the world through computing. 29:39.000 --> 29:45.160 And that wasn't an accidental shift. That was a really careful strategy to think about how we 29:45.160 --> 29:50.600 can draw more folks into the field from that perspective. So I think that's that's certainly 29:50.600 --> 29:58.520 a trend I've seen. Yeah. RIT always has had a long history too of co op. So doing a bunch of 29:58.520 --> 30:03.880 internships during during the course of your degree, and helps you pay for your degree too, 30:03.880 --> 30:07.240 because you don't pay tuition when you're doing that, you're making some money for a semester. 30:08.520 --> 30:13.080 I've seen more and more universities go that direction. I mean, so RIT has been there for 30:13.080 --> 30:20.520 like 50 years doing co ops. But I think other folks are kind of catching on to the idea that 30:21.480 --> 30:27.960 a lot changes when a student gets that first workplace or real world experience. And I know 30:27.960 --> 30:33.160 from like the professor side of it, if I'm interacting with a student, I can kind of tell 30:33.160 --> 30:37.800 if they've already been out on co op already, because like the kind of questions that they ask 30:37.800 --> 30:43.800 in the classroom are like, a little more pointed. Actually, when I was doing this, I saw I saw we 30:43.800 --> 30:48.440 were doing it this way, you know, this kind of stuff, which is great. And not normally 30:48.440 --> 30:51.080 something that you would see in the classroom at most universities. 30:51.880 --> 30:58.840 It also keeps us very honest in terms of are we really teaching the absolute latest stuff? 30:59.480 --> 31:03.320 Yes, it's not just going to be alumni coming back and telling us that it's going to be our own 31:03.320 --> 31:06.920 students. As soon as they come back from a co op, we're going to tell you like, oh, no, 31:06.920 --> 31:11.400 you're teaching the old version of this when I was in the my co op last semester, I was using the 31:11.400 --> 31:16.520 new version that kind of thing. Yeah, I don't know. So the co op thing was one of my favorites 31:16.520 --> 31:20.840 at RIT. And I don't know a single person that did a co op that said it wasn't we shouldn't do 31:20.840 --> 31:26.440 these. It wasn't worth it. And everyone that came back said that they learned so much more on the 31:26.440 --> 31:30.520 co op, like, because it's real world experience, you're applying the things you've learned. 31:31.640 --> 31:35.240 And like, you're also getting paid. So it's way more exciting, right? Like, 31:35.240 --> 31:39.400 and it kind of like, it kind of warms you up into the idea of like joining the workforce, like, 31:40.040 --> 31:44.120 you know, instead of like, after four or five years, hey, here you go. And you're like, 31:44.120 --> 31:49.000 hope you can swim. You learn a little bit along the way. And I think that to me, it's, 31:49.000 --> 31:55.960 I don't I'm surprised on every school's already done this. And people will do a co op. And then 31:55.960 --> 31:58.920 they'll realize, Oh, my gosh, I hate this or something, right? You know, 31:59.480 --> 32:04.600 totally lies. Like, you know, a company of that size. Oh, no, I don't want to work there. Or, 32:04.600 --> 32:10.760 or this part of the country that I lived in for my co op that summer. Oh, I didn't like this. And 32:10.760 --> 32:16.680 that's actually really useful too. And better, better you figure it out on like a three month 32:16.680 --> 32:21.640 co op, rather than go off and move to what you thought was a permanent job and then have to 32:21.640 --> 32:27.480 figure this out. 100%. I think Greg, Greg Coburger may or may not be in the audience here. And 32:28.200 --> 32:33.080 he I remember this he one or two of his co ops he did with a startup company. And now he's founded 32:33.080 --> 32:39.320 his own startup company. And it's very successful. Greg, when you when you decide to send me some 32:39.320 --> 32:45.560 money, I'll give you a free ad here, even though your frequent podcast goes. But, but because of 32:45.560 --> 32:49.720 that, he he gained a lot of I believe, you know, I'm speaking for him now, but I think he gained a 32:49.720 --> 32:53.720 lot of confidence in knowing like what it's like to join a startup, what that life looks like, 32:53.720 --> 32:58.120 versus joining something like, you know, Apple, Microsoft, Google, your typical massive companies 32:58.120 --> 33:01.640 that a lot of people want to work at right out of school. So I think it's immensely valuable. 33:04.040 --> 33:09.800 So, okay, so there's always like, you know, if you read the comments, which they said, 33:09.800 --> 33:13.640 don't read the comments on the internet, there's always people saying like, education is broken. 33:14.360 --> 33:20.360 Right. And, you know, I know that there's a lot of really famous tech people that have said this, 33:20.360 --> 33:24.120 and, and there's a lot of different schools of thoughts. And so I'm really what I'm curious 33:24.120 --> 33:31.000 about is around sort of like, where do you one see need for change in education? And two, 33:31.000 --> 33:35.880 what is that change that you think needs to happen? Is it at a small level? Is it, you know, 33:35.880 --> 33:46.200 kind of a US or a global thing? I think the the trend that I've been noticing is it's a much more 33:46.200 --> 33:53.160 crowded market of choices. So there's everything from like a website where you teach yourself to 33:53.160 --> 34:01.720 code to some sort of online massive course you could do to a programming bootcamp. I mean, 34:01.720 --> 34:07.000 other things I'd put on that scale would be sort of like accelerated sort of programs, 34:07.000 --> 34:13.800 maybe like a for profit university. And then you get into things like full degrees that you might 34:13.800 --> 34:19.080 have at a traditional nonprofit university, whether it's a public institution or a private one. 34:20.360 --> 34:27.080 Now, I work at a private nonprofit university that offers four years degrees, but we also do 34:27.080 --> 34:31.400 other stuff too. I mean, we do these kind of certificates that people can do in a shorter 34:31.400 --> 34:37.560 period of time targeted more to professionals. So I think right now, what you're seeing is 34:38.440 --> 34:42.600 there's a crowded market of a lot of players to offering things that these different points on 34:42.600 --> 34:48.360 that spectrum I mentioned, and then even more traditional universities are experimenting with 34:49.080 --> 34:53.880 degree programs or non credit programs even that are shorter in experience shorter in the 34:53.880 --> 35:01.400 amount of time, right, folks get some experience. What I have seen is there is still a very big 35:01.400 --> 35:09.320 value, if someone can do it to doing like a university degree. You know, it can be expensive, 35:09.320 --> 35:15.160 you look at tuition prices, they look kind of surprising. A lot of things there. I mean, 35:15.160 --> 35:20.200 first of all, a lot of public universities have gotten much less government support over the years 35:20.200 --> 35:24.600 and have to raise that money through tuition. The other thing is when you see a tuition number 35:24.600 --> 35:29.400 for a university, that's really sort of the sticker price. I mean, kind of like buying a car, 35:29.400 --> 35:36.280 that's the starting point. But there's usually a lot of financial aid and scholarships. Really, 35:36.280 --> 35:42.440 that's put sort of putting the max end on things. And, you know, from the perspective of supporting 35:42.440 --> 35:49.000 students that don't have the resources to pay for a lot to go to university, it's actually kind of 35:49.000 --> 35:53.720 better that you see higher sticker prices there because what that means is some people might 35:53.720 --> 35:59.000 be paying that price. But then the university is using a lot of that money to offer financial aid 35:59.000 --> 36:04.440 and scholarships to folks that absolutely can't pay that price. And everybody at that university 36:04.440 --> 36:08.920 might be paying a slightly different price depending on what their financial circumstances are. 36:10.760 --> 36:15.720 There's a big jump in what you're earning is after getting a university degree, especially 36:15.720 --> 36:21.240 if it's in a very career relevant field, right? So I'm in computing. I feel good about this. I 36:21.240 --> 36:25.800 know you go, you somebody go gets goes and gets a computing degree. Yeah, it's going to be worth it, 36:25.800 --> 36:31.400 right? Because they're going to they're going to earn more. And then, you know, in studies of, well, 36:31.400 --> 36:35.720 what happens after graduation? Because, you know, they didn't work for four years, they went to 36:35.720 --> 36:41.880 university and and now they have that debt from some tuition debt. When does it catch up? You 36:41.880 --> 36:48.760 catch up pretty quick if you're in computing. So depends on how much you spend and other things. 36:48.760 --> 36:54.200 But usually in your mid to late 30s, it's you're catching up, right? Yeah, because the higher 36:54.200 --> 37:01.160 earning power that you've got from the degree. I think, you know, going to a university, I think 37:01.160 --> 37:09.240 also has a really formative kind of experience for students too, because for many, if they're 37:09.320 --> 37:12.840 doing a residential kind of program, they're staying at the university, they're not working, 37:12.840 --> 37:17.480 they're not commuting from home. It might be their first experience living on their own, 37:18.520 --> 37:24.040 trying out kinds of new social environments and joining a club and something they never thought 37:24.040 --> 37:29.800 they would join and you never know what might happen. You know, engaging in an entrepreneurial 37:29.800 --> 37:35.480 activity on their campus, for example, those kind of things, you just don't know where it's going to 37:35.480 --> 37:44.280 head. And a lot of that spontaneity and being part of that environment and that setting 37:44.280 --> 37:50.280 is a big part of the experience too. I think it's good that there's options at different levels, 37:50.280 --> 37:54.520 and there's ways that folks could do like a mid career switch and take a programming boot camp 37:54.520 --> 38:00.840 and do that as well. I think there's always going to be some folks for whom a four year 38:00.840 --> 38:07.000 university degree is the right answer for a lot of those reasons I mentioned. But even four year 38:07.000 --> 38:12.840 universities are getting into the business of more masters or certificates or things like this too, 38:12.840 --> 38:21.320 because we realize some folks want other options. Yeah, interesting. Alexis Ohanian, one of the 38:21.320 --> 38:28.520 founders of reddit.com, people would ask him a lot. He would do a lot of live talks, and I don't 38:28.520 --> 38:34.600 know if it's because he wants to be like a politician or something one day. But it seems like it. 38:35.640 --> 38:41.000 But he gets asked all the time, like, is it worth going to school? Actually, Gary Vaynerchuk 38:41.000 --> 38:45.320 also gets asked this all the time by parents. Is it worth going paying for four year degree? 38:45.320 --> 38:50.200 They're really expensive. Is it worth it? Because then you also hear about the people who didn't go 38:50.200 --> 38:56.280 and like, you know, maybe they're just edge cases like Bill Gates and the dropouts like Bill Gates 38:56.360 --> 39:03.320 and Zuckerberg and those people. But what he said, which I thought to be a really good point, 39:03.320 --> 39:09.400 is like, if you're able to go go, you can always try your entrepreneurial ideas while you're there. 39:09.400 --> 39:16.120 And if you fail, you're still in a safe spot. You haven't like put all your chips in and like, 39:16.120 --> 39:20.040 you know, you're not all in on the idea. Because what happens when you're all in and you and now 39:20.040 --> 39:24.360 you've got nothing to fall back on or you've got no support system there. So I really liked his 39:24.360 --> 39:31.400 answer on that. Should you go to college, basically. And Gary Vaynerchuk, I think, says a lot of 39:31.400 --> 39:37.480 similar things to that regard. I think it's also very disciplined specific too, because I think 39:37.480 --> 39:43.560 it really depends on kind of the field that someone is studying. When it's an area that you know 39:43.560 --> 39:51.480 there's really strong demand for folks to work in that field, I think it can change the calculus 39:51.480 --> 39:57.720 on that quite a bit. Yeah. Yeah. So that's an interesting question. Like, do you think school 39:57.720 --> 40:04.200 should encourage students into those fields or let them do whatever they want? 40:06.840 --> 40:15.960 I think that we need to provide the choices for students. But I think I think the world's a better 40:15.960 --> 40:20.840 place if we give folks more information, and then they can make an informed choice, right? 40:21.160 --> 40:27.720 So I don't think that every high schooler is in a family circumstance where maybe their parents 40:27.720 --> 40:34.120 didn't go to college, or maybe they're not getting advice about what is the best area to go work in, 40:34.120 --> 40:40.440 or what is a hot field or something, right? Some do, but many don't. And they may just look at 40:40.440 --> 40:45.080 like kind of the catalog of all the choices and just sort of pick one that sounds interesting or 40:45.080 --> 40:49.080 something. And I think that's great. I think it's good to be able to try a class or two and things 40:49.080 --> 40:54.920 and then see if it's your passion. But getting some more of that information to students about, 40:54.920 --> 41:00.200 oh, yeah, like, here's what we're expecting is job trends in that field over the next couple years. 41:00.200 --> 41:06.360 And what was the average, you know, starting salary for people who graduated in that program 41:07.400 --> 41:12.520 over the past couple years? Oh, that's interesting. And what percentage of people had a job in six 41:12.520 --> 41:19.160 months after they did that degree program, right? Sort of more intentionally choosing your degree 41:19.160 --> 41:26.520 than just sounds all right, or it's easy for me or I'll be fine in four years. Now, if it's something 41:26.520 --> 41:31.160 that you try it and you hate it, right? I mean, it kind of doesn't matter at that point if you 41:31.160 --> 41:36.200 could get a good job in it, right? So there is a matchmaking to this, right? And you're hoping to 41:36.200 --> 41:43.640 find kind of a sweet spot among all those different factors. But if we don't give that information 41:43.640 --> 41:50.280 or expose it really clearly to students also, I think we're doing them a disservice. So I agree. 41:50.280 --> 41:53.880 Some universities do a better job at this than others where they are very clear on, you know, 41:53.880 --> 42:01.560 starting salary stuff and things like that. But it is a debate in higher education. I mean, because 42:02.120 --> 42:07.880 certainly folks in some of the the science, technology, engineering and mathematics stem 42:07.880 --> 42:13.240 sort of fields. Sure, we like this because usually our students are doing pretty good when we graduate. 42:13.240 --> 42:18.440 But individuals from the humanities, you know, would really talk about kind of the way that 42:18.440 --> 42:25.400 education transforms your mind and forms you as a person. And some of this sort of career and 42:25.400 --> 42:33.480 dollar sign oriented stuff feels very different than that, right? So like everything in higher 42:33.480 --> 42:38.760 education, there is debate. And I think that's good. But but getting that information and choices 42:38.760 --> 42:42.680 out to students is important. Yeah, I think it's good. I think it's a really good idea to get it 42:42.680 --> 42:47.000 in front of them, let them see the options and sort of, you know, hey, look, this is what things 42:47.000 --> 42:51.640 are going to look like or look like now. But you still can make your own choice. I think that's 42:51.640 --> 42:59.560 important. So speaking of after you graduate. And you so you graduate, you know, you're paying 42:59.560 --> 43:06.280 off your loans if you have them. And then how do you approach Okay, so how do you approach the 43:06.280 --> 43:10.360 topic of asking alumni for money after they had just spent the money on school? This is a question 43:10.360 --> 43:18.920 I had so I had to get in here. Because I desperately want to know. Sure. Well, so when folks move 43:18.920 --> 43:23.720 into sort of higher education leadership positions, a big part of the job is kind of the 43:23.720 --> 43:29.320 advancement side of things of kind of reaching out to alumni or companies or supporters to try 43:29.320 --> 43:36.600 to raise funds for the university. Although the tuition price can look high, it actually doesn't 43:36.600 --> 43:42.760 pay for everything that the university needs to operate. And so universities depends on the 43:42.760 --> 43:49.960 type of university and things like this, a good chunk of how it operates may come from philanthropic 43:49.960 --> 43:56.360 dollars, or philanthropic dollars that at one point went into an endowment for them institution 43:56.360 --> 44:03.320 that produces funds for them to operate. I think also when a university wants to do new things, 44:04.760 --> 44:09.800 philanthropic dollars wind up being the thing that allows that to happen. That's kind of a new 44:09.880 --> 44:15.960 program or some new opportunity or space for students or things like that. 44:17.000 --> 44:21.000 Sometimes it's tough to fit that in your standard operating budget and save up all those funds to 44:21.000 --> 44:27.400 create something new like this. A gift can be the thing that makes the step change in that case. 44:28.520 --> 44:34.040 So then I think when approaching alumni or supporters about this, I think part of it is 44:34.040 --> 44:40.040 really about listening. You can't go in with a whole list of, well, we need this, we need this, 44:40.040 --> 44:48.840 here's our laundry list or something. Sure, somebody might donate some money, but in general, 44:48.840 --> 44:55.240 if you get a chance to talk with alums, you're actually getting really good data from them 44:55.240 --> 44:58.120 about what their experience was and what they're seeing in the world. 44:59.080 --> 45:06.200 So my disciplinary background is human-computer interaction. What that means is using psychology 45:06.200 --> 45:11.720 methods like interviews and focus groups and experiments to study things regarding people in 45:11.720 --> 45:18.040 tech. So the idea of having a really good interview conversation with somebody and learning a lot 45:18.040 --> 45:24.520 from it is just kind of baked in to the way I think about stuff as a scientist. And so the idea 45:24.520 --> 45:29.320 that you get to go around and talk to a bunch of alums and hear their story and hear from them 45:29.320 --> 45:33.640 like, what did you think was most important? And what do you think we ought to be thinking about 45:33.640 --> 45:39.640 next? That alone is hugely important. Sometimes they'll even donate their time and they'll come 45:39.640 --> 45:45.800 back and talk to our students or be like peer mentors. And then if they have some money to give, 45:45.800 --> 45:50.680 and what you want to understand is, well, what did they care about? What actually matches with 45:50.680 --> 45:55.480 something that resonates with them and something they would love to see us be able to do for students 45:55.480 --> 46:01.080 next. And a lot of that really comes from them reflecting on their own experience. Maybe something 46:01.080 --> 46:06.600 happened during their time at university where somebody was able to step in and help at a certain 46:06.600 --> 46:13.720 point or they realized that they had a challenge during their time at university. And they could 46:13.720 --> 46:19.720 imagine that, well, if I made this donation, it would make a scholarship or help create like a 46:20.760 --> 46:26.600 center for students to help them if they're having some kind of challenge and it might evoke 46:26.600 --> 46:32.840 what they had experienced themselves. And I think that is really sort of where it all comes down to. 46:32.840 --> 46:37.240 It has to be authentic. It has to actually relate to what the person cares about. 46:39.160 --> 46:43.400 I think you also have to talk about them with what that institution means to them 46:44.440 --> 46:49.000 and how it impacted their life. And sure, sometimes it's a philanthropic donation, 46:49.000 --> 46:53.880 but a lot of times it's really more just staying connected, having them interact with students, 46:54.440 --> 47:00.040 be a mentor, or just get some good advice. Especially when you're chatting with folks 47:00.040 --> 47:05.320 that have had really interesting life experiences or have been leaders of different companies 47:05.320 --> 47:10.280 themselves. Those are folks who probably would charge for their time if they were just giving 47:10.280 --> 47:17.400 out advice to people, right? So sure, I'll take the free consulting advice. I don't know. I think 47:17.400 --> 47:21.800 you've got to go into it that way. Yeah, okay. I think that's a very good way of thinking of it. 47:22.840 --> 47:27.240 Sort of building a community, but also you're getting value that's more than just monetary value. 47:28.520 --> 47:33.080 However, I guess money doesn't hurt, right? Well, I mean, so for example, 47:34.840 --> 47:39.960 when I chat with a lot of alums, I'll ask them about, you know, well, what was the most impactful 47:39.960 --> 47:44.680 thing that you thought, you know, during your time? And they'll talk about different things, 47:44.680 --> 47:49.640 but co-op comes up a lot. So the fact that they had that internship experience, right? 47:51.480 --> 48:01.320 And what I use that for as a dean is kind of a compass that tells me that we're on the right course 48:01.880 --> 48:06.840 by continuing to keep that going, right? Because if alumni are telling me that like, 48:06.840 --> 48:11.480 that's the thing that like changed it all for me. And that's the thing that really helped 48:11.480 --> 48:15.800 me figure out what was next. Okay, we got to protect that got to keep it going. 48:17.160 --> 48:22.920 When I've had conversations with alums about, well, what are you seeing with like this generative AI 48:22.920 --> 48:28.760 stuff being used in the computing field? And I ask them things like, okay, are you somebody who 48:28.760 --> 48:34.360 hires computing folks? Okay, let's say in a couple years, you know, in the future, you were having 48:34.360 --> 48:39.000 an interview with somebody for a position at your company. What if they didn't know how to use 48:39.000 --> 48:43.400 co-pilot or didn't know how to use these AI tools? What would you think about that? Yeah, 48:43.400 --> 48:49.000 they tell me like, Oh, no, that would be a problem. Yes, that's that's a that's a sound bite that I 48:49.000 --> 48:54.440 can bring back to the college, talk about with faculty, and we can really think about like, okay, 48:54.440 --> 49:00.920 this is what I'm hearing from alumni. I have chatted with like, 35 alums at these variety of 49:00.920 --> 49:06.680 companies, and they've all told me this and this. And then it steers the course, right? And so that 49:06.680 --> 49:13.000 kind of insight, we're going to get from from keeping these connections alive. Yeah, 100%. 49:13.000 --> 49:17.960 Actually, that's, that's, you know, when we met in San Jose, like Campbell, California, that's 49:17.960 --> 49:21.640 some of the stuff that we talked about was, you know, AI in the workplace and, and what trends 49:21.640 --> 49:29.240 are happening. And, and I'm pretty sure I have a have a knack for talking too much. And I'm pretty 49:29.240 --> 49:32.520 sure we were scheduled to meet for like a half an hour an hour. And I think it took like a couple 49:32.520 --> 49:41.320 hours. But I enjoyed the conversation. It was a good chat. Yes. What you were part of a big study 49:41.320 --> 49:46.680 I was sort of doing of talking with a lot of folks around Silicon Valley about like, where's this AI 49:46.680 --> 49:52.840 stuff headed? What do you think we got to worry about next, right? Yeah. And that was really 49:52.840 --> 49:57.800 formative. Yeah. Yeah. And for anyone, you know, listening or watching, I do want to make one 49:57.800 --> 50:04.040 point that I think, if you are not familiar with some of the gen AI stuff in a year from now, like, 50:04.760 --> 50:08.600 catch up, or, you know, like, don't don't fall too far behind. Because I think it's, 50:08.600 --> 50:13.240 it's like, it's, you know, it's like ignoring the computer, because it's like new and scary. 50:13.240 --> 50:16.760 I think it's just going to be, it's going to be everywhere. I don't think you can avoid it in the 50:16.760 --> 50:25.560 future. Okay. So, let's see, the last, I guess the last thing I sort of want to, well, there's 50:25.560 --> 50:32.920 a couple things I want to finish up with. One of them is how do you support in underrepresented, 50:33.960 --> 50:40.200 you know, people and sort of what does the school do? And how do you look at that? 50:41.160 --> 50:46.760 So, I mentioned that, you know, my background's human computer interaction. So a lot of it is 50:46.760 --> 50:54.520 studying this intersection with people and tech. And I believe it because I've seen it, 50:54.600 --> 51:01.240 that if you have got folks that actually are reflecting the diversity of the world 51:01.240 --> 51:08.920 on a team, or as part of a project, you wind up learning a lot more. So, you know, for example, 51:08.920 --> 51:15.240 a lot of my work is on tech for people who are deaf and hard of hearing. And we've been able to have 51:15.240 --> 51:19.880 a lot of deaf and hard of hearing research team members, whether it's faculty collaborators at 51:19.880 --> 51:26.440 other universities or PhD students at our lab or master students undergrads. And, you know, 51:26.440 --> 51:33.800 I've been working in that field of accessibility for over 20 years. And there are still times where 51:33.800 --> 51:38.120 we will do a study or something or we'll interview somebody and ask them how they want to use some 51:38.120 --> 51:44.680 tech. And there will be some quote in an interview. And I don't know what to make of it, right? And 51:44.680 --> 51:48.920 then I'll talk about it with one of my deaf and hard of hearing colleagues. And they're like, 51:48.920 --> 51:53.880 oh, no, yeah, it means this, because their own personal experience gives them that window of 51:53.880 --> 52:00.920 insight, right? It also gives them the idea of how should we as a field be prioritizing the agenda 52:00.920 --> 52:05.800 of what we ought to be working on next in a way that doesn't just represent a tiny slice of the 52:05.800 --> 52:11.720 world, right? So, part of what we do is, as I mentioned before, you know, rebranding a little 52:11.720 --> 52:17.240 bit the field, like it's about computing impacting the world. And that brings in more students that 52:17.240 --> 52:23.720 might not have otherwise been interested in tech. But then once we get them here, we've got to support 52:23.720 --> 52:32.360 them. So, at our college, we have a big diversity initiatives office that has a large program called 52:32.360 --> 52:38.280 Women in Computing, and then another program called Computing Organization for Multicultural 52:38.280 --> 52:44.760 Scholars that comes, see OMS. And both of those groups are kind of like clubs. They're sort of 52:44.840 --> 52:51.640 affinity groups for students that want to connect with peers in that space. But we supercharge them 52:51.640 --> 52:59.160 by adding a professional staff member and admin support to the clubs and a budget. So, they can 52:59.160 --> 53:04.840 do a lot more than they might have been able to do if they had to just self organize and do all the 53:04.840 --> 53:11.320 fundraising themselves for things. Right. And so, it creates like a community inside the college 53:11.320 --> 53:17.480 where students can find peers. And we also wind up having a lot of their activities be 53:17.480 --> 53:22.920 things that reaches out to local middle schools. So, for example, the Women in Computing Organization 53:22.920 --> 53:28.040 does a lot of activities with local Girl Scout troops to kind of get them excited about computing. 53:28.040 --> 53:34.120 And so, it's kind of like a long game to kind of get a bigger pipeline of students interested. 53:34.120 --> 53:39.160 But then they're all doing it together. So, then they've got a community sense. And then because 53:39.160 --> 53:44.680 they had that experience together, the alums from that program come back and connect and do 53:44.680 --> 53:51.000 mentorship stuff. And so, it's kind of connecting a lot of dots to create this community and this 53:51.000 --> 53:56.760 activity. And similarly for students of color, we've got that other group comms that I mentioned. 53:57.320 --> 54:04.200 So, where we're going with a lot of this is really trying to increase the diversity of students in 54:04.200 --> 54:09.480 our college who are women or people of color. So, the Women in Computing Group has been around for 54:10.200 --> 54:16.920 over a decade. And over the past decade, we've more than doubled the percentage of women that are 54:16.920 --> 54:23.880 coming into our undergraduate class in the college. So, it's telling us that something there is working, 54:23.880 --> 54:28.840 which is why we're kind of using that model of affinity groups, supercharged with professional 54:28.840 --> 54:35.080 staff and kind of things to do this support. For students with disabilities, especially Deaf and 54:35.080 --> 54:42.040 Hard of Hearing, RIT also has a lot of supports. I mean, there's really amazing interpreters and 54:42.040 --> 54:48.600 captioners on the campus. A lot of other sort of student clubs and support that, you know, I 54:48.600 --> 54:52.680 mentioned I moved to RIT because I wanted to be able to have Deaf and Hard of Hearing students 54:52.680 --> 55:00.520 on our team. And, you know, if you imagine like a graduate mathematics course that PhD students 55:00.520 --> 55:05.800 in computing have to take, you know, it takes a really skilled interpreter to be able to in real 55:05.800 --> 55:11.560 time interpret all of that into American Sign Language consistently during a whole semester 55:11.560 --> 55:16.600 and using the same vocabulary that the student might have used in the last class in the sequence, 55:16.600 --> 55:21.160 so they don't get confused to really get a student through a graduate education there. 55:22.760 --> 55:27.160 And we're doing it. We're graduating students through the pipeline that reflects some of this 55:27.160 --> 55:31.880 diversity. So, yeah, there's a lot of things to do in this space and those are a couple of 55:31.880 --> 55:38.280 things we do at RIT, but I believe in it because I know it's important. As a computing field, 55:38.280 --> 55:43.720 we are not going to be as good a computing field as we can be if we're only recruiting a tiny slice 55:43.720 --> 55:48.440 of the world. We're going to ignore things. We're going to not realize certain things are important 55:48.440 --> 55:53.320 and we're not even going to know what to make of feedback from our users because we don't have 55:53.320 --> 56:00.200 the perspective to understand it. It sort of reminds me of, I use this a lot at the allegory of the 56:00.200 --> 56:05.400 cave, if you're familiar, with the allegory of the cave, where Socrates, Aristotle and Socrates 56:05.400 --> 56:11.160 are discussing like there's these, if you will, prisoners and they're chained up and the only 56:11.160 --> 56:15.000 thing they can see is a shadow is projected on the wall in front of them. And it's not until one 56:15.000 --> 56:19.000 of the prisoners is able to, and they don't know the world has color in three dimensions and all the 56:19.000 --> 56:23.560 sounds and smells and butterflies and whatever, but when one of the prisoners gets out, he's 56:23.560 --> 56:27.880 able to see all these things and comes back in to sort of free the rest of the people in there. 56:27.880 --> 56:34.040 They're skeptics, right? Like, oh, we don't need to do that. This is life here. And so it reminds 56:34.040 --> 56:37.560 me a bit of that because then you get a bigger picture of the world as it is. And I think it 56:37.560 --> 56:41.640 helps in entrepreneurship, especially at least coming from my point of view, because you're not 56:41.720 --> 56:45.000 just serving like you said, just a slice of the population, you can serve, you know, 56:45.000 --> 56:50.040 more people, which I think is huge. All right, well, on that note, I, you know, I greatly 56:50.040 --> 56:55.800 appreciate your time. I do, I do, you know, enjoyed this conversation and I hope to have you 56:55.800 --> 57:00.200 again on the podcast soon. I know you're a very busy person. So thank you very much for being here. 57:00.200 --> 57:04.680 Happy holidays. Happy holidays. This was really fun. It was great to pick it up and I enjoyed 57:04.680 --> 57:09.320 talking with you all about this. Yeah. And I know it's snowing up there. So I don't envy. I don't 57:09.320 --> 57:12.680 think I'll be visiting right now, but maybe, maybe when it's a little bit warmer and everyone 57:12.680 --> 57:18.440 comes out from the tunnels underground. Indeed. Thanks again, Matt. I really appreciate it. 57:18.440 --> 57:20.760 Bye bye. Bye.