YouSaid · the spoken record

Charles Isbell

lines on the record: 192
first: 2020-11-02
most recent: 2020-11-02
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“You go back to those days mostly in New York, though not exclusively, but mostly in New York where it sort of came out of, you know, as a DJ that brought all the music together and the beats and showed that basically music is itself an instrument. Very meta. And you can bring it together and then you sort of rap over it and so on. And it moved that way. So that's going way, way back. Now, in the period of time where I grew up, when I became really into it, which was mostly the 80s, it was more funk was for a lot of the stuff public enemy at that time notwithstanding. And so, which is very nice because it tied into what my parents listened to and what I vaguely remembered listening to when I was very small. And by the way, complete revival of George Clinton and Parliament and funkedelic and all of those things to bring it sort of back into the 80s and into the 90s. And as we go on, you're going to see the last decade and the decade before that being brought in. And when you don't think that you're hearing something you've heard, it's probably because”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“That's been true since the beginning I mean, in fact, that's in some ways the DJ used to get. Top billing because it was the DJ that brought all the records together and made it worth so that people could dance.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Some of it's even good. Not all of it, but some of it is good. But I'd start you with it. It takes a nation and millions to hold his back.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Whereas that nobody else understands, right? And it becomes a part of hip hops the same way, everything's the same way. They're all cultural artifacts. But I would help you to see that there's a history of it and how it connects to other genres of music that you might like to bring you in so that you could kind of see how it connects to what you already like, including some of the good work that's been done with fusions of hip-hop and bluegrass.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Yes. He's amazing. He's amazing. And then after you got you there, I'd work you back to EPMD. And eventually I would take you back to the last poet, and particularly their first album, The Last Poets, which was 1970, to give you a sense of history that it actually has been building up over a very, very long time. So we would start there because that's where your music aligns. And then we would cycle out and I'd move you to the present and then I'd take you back to the past. Because I think a large part of people who are kind of confused about any kind of music, you know, the truth is this is the same thing we've always been talking about, right? It's about narrative and being a part of something and being immersed in something so you understand it, right? Jazz, which I also like, is one of the things that's cool about jazz is that you come and you meet somebody who's talking to you about jazz and you have no idea what they're talking about. And then one day at all clicks and you've been so immersed in it, you go, oh yeah, that's a Charlie Parker and you start using.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Particularly takes a nation of millions to hold his back, which is clearly the best album ever produced and certainly the best hip-hop album ever produced, in part because it was so much of what was great about the time. Fantastic lyrics, excuse me, it's all about the lyrics. Amazing music that was coming from Rick Rubin was the producer of that. And he did a lot of very kind of heavy mental-ish, at least in the 80s at the time. And it was focused on politics in the 1980s, which was what made hip-hop so great then. I would start you there, then I would move you up through things that have been happening more recently. I'd probably get you to someone like Amos Deaf. I would give you a history lesson, basically. Most deaf's amazing.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“There's a fascinating X no, it's okay. There's a fascinating exercise one can do by watching old episodes of I Love the 70s. I love the 80s. I love the 90s with a bunch of friends and just see where people come in and out of pop culture. So if you're talking about those people, then I would actually start you with where I would hope to start you with anyway, which is public enemy.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“A music party. I mean, you wouldn't call the stuff that DJs do the scratching. That's not rap, right? But it's a part of hip hop, right? So given that we understand that hip hop is this whole thing, what are the rap albums that best touch that for me? Well, if I were going to educate you, I would try to figure out what you liked and then I would work you there. Oh my God. I would probably start with.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Tagging is like graffiti. And there's all these, including the popping and the locking and all the dancing and all those things. That's all a part of hip hop. It's a way of life, which I think is true. And then there's rap, which is this particular.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“It's a whole set of things of which rap is a part. So tagging is a part of hip hop. I don't know why that's true, but people tell me it's true and I'm willing to go along with it because they get very angry about it. But hip hop is like...”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, so I listened to a lot, but I will tell you, well, first off, all great music was made when I was 14, and that statement is true for all people, no matter how old they are or where they live. But for me, the first thing that's worth pointing out is that hip-hop and rap aren't the same thing. So depending upon you talk to about this, and there are people who feel. Very strongly about this, much more strongly than you do.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“And the funk can be lots of different things, but I decided I should leave it up to the individual to figure out exactly what it is. But I will tell you that when my students graduate, when they get out, as we say at tech, I hand them, they put on a hat and star glasses and a medallion from the PFunk era. And we take a picture and I hand them a pair of fuzzy dice. Which they get to keep”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“So, a lot of my life is about making acronyms. So if I have one quirk, it's that people will say words and I see if they make acronyms. And if they do, then I'm happy. And then if they don't, I try to change it so that they make acronyms. It's just a thing that I do. So PFunk is an acronym. It has three or four different meanings. But finally, I decided that the P stands for probabilistic because at the end of the day, it's machine learning and it's randomness and it's uncertainty, which is the important thing here”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Counterintuitive science, right? And saying, no, you're doing this all wrong. Representation is crazy. The world is your own representation. You just react to it. I mean, this is amazing things and continues to do those sorts of things as he's moved on. I think he might tell you, I don't know if he would tell you it was good or bad, but I know that for everyone else out there in the world, it was a good thing. And certainly he continued to be respected. So it's not as if it destroyed his career by being popular.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“I don't know how it explains. I love Rod. I also love my other advisor, Paul. Paul, if you're listening, I love you too. Both very, very different people Both very interesting people, very different in many ways. But I don't know what Rod would say to you about what the reaction was. I know that for the students at the time, because I was a student at the time, it was amazing, right? This guy was in a movie, being very much himself. Actually, the movie version of him is a little bit more rod than Rod. I mean, I think they edited it appropriately for him, but it was very much Rod. And he did all this while doing great work. I mean, he was running. Run the A Lab at that point or not? I don't know. But anyway, he's running the I lab.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“It was a documentary that involved four people. I remember nothing about it other than Rod Brooks was in it and something about naked mole rats. Can't remember what the other two things were. It was robots, naked mole rats, and then two other”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“It's easy to convince yourself, and no one is immune to this, that the people who are better known are better known for bad reasons. The people who are out there dumbing it down are not being pure to whatever the values in Athos is for your field. And it's just very easy to do. Now, having said that, I think that ultimately people who are able to be popular and out there and are touching the world and making a difference our colleagues do in fact appreciate that in the long run. It's just, you know, you have to be very good at it or you have to be very interested in pursuing it. And once you get past a certain level, I think people accept that for who it is. I mean, I don't know. I'd be really interested in how Rod Brooks felt about how people were interacting with him when he did fast cheap and out of control way, way, way back when.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, there's a reason for that. Tenure isn't a test. It's a training process. Teaches you to behave in a certain way, to think in a certain way, to accept certain values, and to react accordingly. And the better you are at that, the more likely you are to earn tenure. And by the way, this is not a bad thing. Most things are like that. And I think most of my colleagues are interested in doing great work and they're just having impact in the way that they want to have impact. I do think that as a field, not just as a field, as a profession, we have a habit of Belittling those who are popular, as it were, as if the word itself is a kind of scarlet A, right? I think”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Has gotten worse and worse. Like Google really has been around that long. Anyway, the point is that I think that we sometimes forget that a part of our job is to impact the people who aren't in the world that we're in and that that's the point of being at a great place and being a great person, frankly.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Once you tell yourself that story. Then it is Beneath you to do that kind of thing, right? I think that's wrong. I think that, and by the way, everyone doesn't have to do this, everyone's not good at it, and everyone, even if they would be good at it, would enjoy it So it's fine. But I do think you need some diversity in the way that people choose to relate to the world as academics. Because I think the great universities. Are ones that engage with the rest of the world. It is a home for public intellectuals. And in 2020, being a public intellectual probably means being on Twitter, whereas, of course, that wasn't true 20 years ago because Twitter wasn't around. And 20 years ago, and if it was, it wasn't around in a meaningful way. I don't actually know how long Twitter's been around. As I get older, I find that my notion of time.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Tenure is a powerful thing that allows you to do whatever you want. But getting tenure. Typically requires you to be relatively narrow, right? Because people are judging you. Well, I think the answer is we have told ourselves a story, a narrative, that that is vulgar, which you just described as vulgar. It certainly unscientific. It is easy to convince yourself that in some ways you're the mathematician, right? The fewer there are in your major, the more that proves your purity, right?”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“So, even the objective is an objective, because at the end, you've got to tell a story, you've got to make decisions, you've got to make trade-offs, or what else is engineering other than that. So I think that the rankings capture something. They just don't necessarily capture what people assume they capture”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Object, they're just capturing light. No, they are doing the things that they're doing based upon decisions by real human beings to privilege, if I may use that word, some physics over others, because it's an engineering problem. There are trade-offs, right? So I can either worry about this part of the spectrum or this part of the spectrum. This costs more, that costs less, this costs the same, but I have more people paying money over here, right? And it turns out that if a giant conglomerate demands that you do something different and it's going to involve all kinds of money for you, suddenly the trade-offs change, right? And so there you go. I actually don't know how I ended up there. Oh, it's because this notion of objectiveness, right?”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Cameras, which are just reflecting light and putting them on film, like, did not work for dark skinned people until the 1970s? You know why? Because you were building cameras for the people who are going to buy cameras, who are all, at least in the United States and Western Europe, were relatively light-skinned. Turns out took terrible pictures of people who look like me. That got fixed with better film and whole processes. Do you know why? Furniture manufacturers wanted to be able to take pictures of mahogany furniture, right? Because candy manufacturers wanted to be able to take pictures of chocolate. Now, the reason I bring that up is because you might think that cameras.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“which I think is worth examining for a moment, right? You said it's, I forget the word Jesus. He said, we're living in the space of narrative as opposed to something objective. Narrative is objective. I mean, one could argue that the only thing that we do as humans is narrative. We just build stories to explain why we do found. Someone once asked me, but wait, there's nothing objective. No, it's... Completely an objective measure is an objective measure of the opinions of everybody else. Now, is that physics? I don't know. But, you know, what, I mean, tell me something you think is actually objective and measurable in a way that makes sense. Like cameras. Don't you know that? I mean, you're getting me off on something, but do you know that?”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, what MIT is going for, well, MIT has many things going for it. One of the things MIT is going for it is. It has a nice logo. It's a lot better than it was when I was here. Nice colors too. Terrible. Terrible name for a mascot. But the thing that MIT has going for it is it really does get the best students. It just doesn't get all of the best students. There are many more best students out there, right? And the best students want to be here because it's the best place to be or one of the best places to be. And it just kind of is a sort of positive feedback. But you said something earlier.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Beyond that, it's just inertia, and there's huge history system in the system, right? Like, I mean, there was these, I can't remember this, this is maybe apocryphal, but there's a major or department that, like, MIT was ranked number one in, and they didn't have it. It's just about what you, I don't know if that's true, but someone said that to me anyway. But it's a thing, right? It's all about reputation. Of course MIT is great because MIT is great. It's always been great. By the way, because MIT is great The best students come Which keeps it being great. I mean, it's just a positive feedback loop. It's not surprising. I don't think it's wrong.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“We created these schools at a time when most public universities anywhere were afraid to do it. We did the online masters. And that mattered because people were trying to figure out what to do with MOOCs and so on. I think it's about being observed by your peers and having an impact. So, I mean, that is what reputation is, right? So the way you move up in the reputation rankings is by doing something that makes people turn and look at you and say, that's good, they're better than I thought.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“As opposed to having someone else move down. So we used to be number 10, and then we became number nine because UT Austin went down slightly and now we retired for ninth because that's how rankings work. And we moved from nine to eight because our raw score moved up a point. So George, something, something, something about Georgia Tech, computer science or computing anyway. I think it's because we have shown leadership at every crisis level, right? So we created a college, first public university to do it, second college, second university to do it after CMUs, number one. I also think it's no accident that CMU is the largest and we're depending upon how you count and depending exactly where MIT ends up with its final college of computing, second or third largest. I don't think that's an accident. We've been doing this for a long time. But in the 2000s, when there was a crisis about undergraduate education, Georgia Tech took a big risk and succeeded at rethinking undergrad education and computing. I think we...”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“It can help. I can tell you how Georgia Tech did it, or at least how I think Georgia Tech did it, because Georgia Tech is actually the case to look at. Not just because I'm at Georgia Tech, but because Georgia Tech is the only computing unit that was not in the top 20 that has made it into the top 10. It's also the only one in the last two decades, I think, that moved up in the top 10.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, the only one that matters is US news. Nothing else matters. Sorry, CS rankings.org, but nothing else matters but US News. So US News has formula that it uses for many things, but not for computer science, because computer science is considered a science, which is absurd. So the rankings for computer science. Is one hundred percent reputation So, two people each department it's not really department whatever at each department basically rank everybody slide the more complicated than that but whatever they rank everyone and then those things are put together and somehow”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“So it depends on which rankings you're talking about. Do you want to talk about computer science or we want to talk about university?”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“The other answer to that question, by the way, which you could argue is the same as you either adjust the pool so the probabilities go up, that's a way of injecting a little bit of uniform noise in the system, as it were, as you change your loss function. Just let yourself be measured by something other than whatever it is that we're measuring ourselves by now. I mean, US News Enroll report, every time they change their formulas for determining rankings, move entire universities to behave differently because rankings matter.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“That I can tell you how everybody gets into grad school, more or less. Basically, admit everyone from places higher rank than you. You admit most people from places ranked around you, and you met almost no one from places ranked below you, with the exception of the small liberal arts colleges that aren't ranked at all, like Harvey Mudd because they don't have PhDs, so they aren't ranked. This is all CS, which means the decision of whether you become a professor at Cornell was determined when you were 17, right? What you knew to go to undergrad to do whatever, right? So if we can push these things back a little bit and just make the pool a little bit bigger.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Very hard to do with people. All the incentives are wrong there, but it turns out, and let's say that's the right answer, let's just give, for the sake of argument, that, you know, injecting randomness in the system at that level for who you hire is just not worth doing because the price is too high or the cost is too high. If we had infinite resources, sure, but we don't. And also, you've got to teach people. So, you know, you're ruining other people's lives if you get it too wrong. But we've taken that principle even if I grant it and pushed it all the way back. So we could have a better pool than we have of people we look at and give an opportunity to. If we do that, then we have a better chance of finding that. Of course, that just pushes the problem back another level. But let me tell you something else. You know, I did a sort of study. I call it a study. I call the beta my friends and ask them for all of their data for graduate admissions. But then someone else followed up and did an actual study. And it turns out.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“You have to be willing to take a certain kind of without taking a particular position on any particular person. You'd have to take risk, right? A small amount of it. I mean, if we were treating this as a, well, as a machine learning problem, as a search problem, which is what it is, it's a search problem. If we were treating it that way, you would say, oh, well, the main thing is you've got a prior, you want some data because I'm Bayesian. If you don't want to do it that way, we'll just inject some randomness in and it'll be okay. The problem is that feels very...”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“So, all the pressure drives you into that particular direction. Google To put too fine a point on it was in exactly the same situation with their search. It turns out you just don't want to give people the wrong page in the first three or four pages. And if there's 10 million right answers and 100 bazillion wrong answers, just make certain the wrong answers don't get up there and who cares if you the right answer was actually the 13th page. A right answer, a satisficing answer is number one, two, three, or four. So who cares?”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“It tells you is well, ask yourself the question. Why is it like that? Well, because it's easier. If we go all the way back to the 1980s, there was a saying that nobody ever lost his job buying a computer from IBM. And it was true. Nobody ever lost their job hiring a PhD from MIT, right? If the person turned out to be terrible, well, you know, they came from MIT. What did you expect me to know? However, that same person coming from pick whichever is your least favorite place that produces PhDs in, say, computer science, well, you took a risk, right? So all the incentives, particularly because you're only going to hire one this year, well, now we're hiring 10, but you know, you're only going to hire one or two or three this year. And by the way, when they come in, you're stuck with them for at least seven years in most places because that's before you know where they're getting tenure or not. And if they get tenure, you're stuck with them for a good 30 years unless they decide to leave. That means the pressure to get this right is very high. So what are you going to do? You're going to minimize false positives. You don't care about saying no inappropriately. You only care about saying yes inappropriately.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Oh, yes, it's a large part of my job. Number five is Illinois. Number six is a tie with UW and Cornell and Princeton and Georgia Tech are tied for eight and UT Austin is number 10. Michigan's number 11, by the way. So if you look at the top 10, you know what percentage of faculty in the top 10 are in their PhDs from the top 10? 65 roughly 65 if you look at the top 55 ranked departments 50% of the faculty earn their PhDs from the top 10 there is no universe in which The best faculty, even just for R1 universities, the majority of them come from 10 places. There's no way that's true, especially when you consider how small some of those universities are in terms of the number of PhDs they produce Now, that's not a negative. I mean, it is a negative. It also has a habit of intrinsic certain historical inequities and accidents.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“About 60% 60% of the faculty in the top four earn their PhDs in the top four. This is computer science. Which there is no top five, there's only a top four, right? Because they're all tied for one.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Anyway, so. We're going to try to hire the best professor. That's what we say, the best person for this job. But that's not what we do at all. Do you know which percentage of faculty in the top four earn their PhDs from the top four? Say in 2017 for which we have, which is the most recent year for which I have data.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“It's minimizing false positives. We say things like we want to find the best person to be an assistant professor at MIT. The new College of Computing. Which I will point out was founded 30 years after the College of Computing I'm a part of. Both of my alma mater. That more fighting words. I'm just saying, I appreciate all that they did and all that they're doing.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Like 95. I see 110 and I see, but where did 95 go? I'm very grateful for Google. But, you know, they just have to make certain the first five things are right. And everything after that is wrong. Look, we're going off in a totally different topic here, but. About the way we hire faculty, it's exactly the same thing. I'm getting controversial. I get incontroversial. It's exactly the same problem.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“We're learning the wrong problem in the first place, but I don't think that matters. I think the point is that Google has not solved information retrieval”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Then the problem wasn't give me the things that are relevant. The problem is don't give me anything that's irrelevant, at least in the first page, because nothing else matters. So Google is not solving the information retrieval problem, at least not on this webpage. Google is minimizing false positives, which is not the same thing as getting an answer. It turns out it's good enough for what it is we want to use Google for, but it also changes what the problem was we thought we were trying to solve in the first place. You thought you were trying to find an answer, but you're not, where are you trying to find the answer? But it turns out you're just trying to find an answer. Now, yes, it is true it's also very good at finding you exactly that webpage. Of course, you trained yourself to figure out what the keywords were to get you that webpage. But in the end, by having that much data, you've just changed the problem into something else. You haven't actually learned what you set out to learn. Now, the counter to that would be maybe we're not doing that either. We just think we are because we're in our own heads.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“People were trying to solve information retrieval, the ad hoc information retrieval problem forever. I mean, first major book I ever read about it was, what, 71, I think, was when it came out. Anyway, it's, you know, we'll treat everything as a vector and we'll do these vector space models and whatever. And that was all great. And we made very little progress. I may made some progress. And then Google comes and makes the ad hoc problem seem pretty easy. I mean, it's not. There's lots of computers and databases involved. But, you know, and there's some brilliant algorithmic stuff behind it too and some systems building. But the problem changed, right? If you've got a world that's that connected so that you have their 10 million answers quite literally to the question that you're asking?”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“I'll give you an example, which is like the one you just described at YouTube. Let's get completely out of machine learning. Well, not completely, but mostly out of machine learning. Think about Google.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Videos. I mean, I can't think of a more terrifying world to live in than a world that is based on YouTube videos. But yeah, I think the answer that I just kind of don't think that'll quite well, it won't work that easily. You will get somewhere and you will learn something, which means it's probably worth it, but you won't get there. You won't solve the, you know, here's the thing. Build these things and we say we want them to learn, but what actually happens, and let's say they do learn, I mean, certainly every paper I've got and publish the things learn. I don't know about anyone else, but they actually change us, right? We react to it differently, right? So we keep redefining what it means to be successful, both in the negative and the AI case, but also in the positive in that, oh, well, this is an accomplishment.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“You're going to have live for months at a time in an environment that is messy and chaotic you cannot control, then you're never going to make progress in that direction. So I guess my answer to you is yes. My idea is that you should, it's not no. It's yes. You should be. Deploying these things and making them live for months at a time and be okay with the fact it's going to take you five years to do this. Not rerunning the same experiment over and over again and refining the machine so it's slightly better at whatever, but actually having it out there and living in the chaos of the world and seeing what it's learning algorithm say can learn, what data structure it can build and how it can go from there. Without that, you're going to be stuck ultimately.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source
“Is but it does make this gap seem really big, which is on my long way of saying I don't have a great answer to it, except that stop doing n equals one. At least try to get n equal two and maybe n equal seven so that you can say I'm gonna, or maybe t is a better variable here, I'm gonna not just solve this problem, I'm gonna solve this problem and another problem. I'm not gonna learn just on you. I'm gonna keep living out there in the world and just seeing what happens and that we'll learn something as designers and our machine learning algorithms and our AI algorithms can learn as well. But unless you're willing to build a system.”
2020-11-02 · Lex Fridman Podcast · #135 – Charles Isbell: Computing, Interactive AI, and Race in America · IDENTIFIED FROM THE TRANSCRIPT · source