Speaker 1: Hello the Internet, and welcome to Season three h five,
Speaker 1: Episode two of dar Day Zai Guys Day production of iHeartRadio.
Speaker 1: This is a podcast where we take a deep dive
Speaker 1: into America's share consciousness. And it is Tuesday, September nineteenth.
Speaker 2: Three Oh yeah you know, oh yeah, National It Professionals Day.
Speaker 2: It's also National Voter Registration today. Hey, make sure you
Speaker 2: richter to vote because a lot of people would probably
Speaker 2: hope you aren't doing that. And also National butter Scotch
Speaker 2: Flitting Day. Shout out to all of my lovers of
Speaker 2: the butter scotch flavor, including myself.
Speaker 1: Yeah, I think that's one of the better putting flavors.
Speaker 2: It's also it's also Taco like a Pirate Day. But
Speaker 2: I just I.
Speaker 1: Didn't want to, you know, you don't want to do
Speaker 1: that to everybody with children?
Speaker 2: No, No, is that a thing you would do at
Speaker 2: the parent would You'd be like, Hey, guys, it's talk
Speaker 2: like a pirate day. We ready to annoy ourselves to death.
Speaker 1: In this household. We look down on international days that
Speaker 1: are made up for no reason. We scoff at them.
Speaker 2: Miles right right, right, right right. We're out here living
Speaker 2: in the real world. There's real consequences to our.
Speaker 1: Actions, and when we scoff at them, we say horror, horror,
Speaker 1: because it's always international to the part day. My name
Speaker 1: is Jack O'Brien aka L Jacko. That's courtesy of Max
Speaker 1: Her twelve sixteen, because they think I look like L
Speaker 1: Chapo's son. And oh okay, yeah, there was a new
Speaker 1: picture of El Chapo's son being extradited to the US
Speaker 1: on board of plane in handcuffs of people. Once again,
Speaker 1: anytime a picture of that fellow hits the news, I
Speaker 1: am reminded, oh okay, hey this you anyways, it is
Speaker 1: not I'm thrilled to be joined as always by my
Speaker 1: co host mister Miles.
Speaker 2: Great, well break, Okay, I'm far out of range.
Speaker 3: One bar is how I feel my own a searching hard,
Speaker 3: lying naked on my thigh, irradiation changed my guts do
Speaker 3: something real.
Speaker 1: They're wide awaken. I can't see a quato has.
Speaker 4: Been born.
Speaker 2: To study on discord. Yes, I how that iPhone twelve
Speaker 2: had higher levels of radiation, yeah, than the than the
Speaker 2: French government would allow h And I thought, hey, maybe
Speaker 2: that would just create a little total recall quato type character.
Speaker 1: And that's fun that's a fun one for you to have,
Speaker 1: you know, fun news story for you to have a
Speaker 1: laugh with, because you what what I turned out?
Speaker 2: Turned out? I had an eleven, I got that twelve, baby, But.
Speaker 1: No fair, you have to name your name your quato
Speaker 1: after me. Give me that quato, Miles. Yes, we are thrilled, fortunate,
Speaker 1: blessed to be joined in our third seat by an
Speaker 1: assistant Professor of Technology, Operations and Statistics at NYU, where
Speaker 1: his research focuses on the intersection of machine learning and
Speaker 1: natural language processing, which, of course means you know, his
Speaker 1: interests include conversational agents, hierarchical models, deep learning, spectral clustering.
Speaker 1: You guys are all probably finishing this sentence with yeah,
Speaker 1: of course, spectral estimation of hidden Markov models, yes, obviously,
Speaker 1: and of course time series analysis. Please welcome doctor Joao, sid,
Speaker 1: Doc doctor Joe.
Speaker 4: Hi. Thank you, Yeah, thank you Jack and Moles for
Speaker 4: having me. It's a pleasure to be here, the pleasure
Speaker 4: to have you.
Speaker 2: We're glad you're here because we got we got a
Speaker 2: lot of questions about a lot of stuff, some some
Speaker 2: to mostly to do with what your area of expertise is.
Speaker 2: Some things I just need a second opinion on just around.
Speaker 1: The career of Alan Iverson. Is it a bad joke
Speaker 1: if it's been used in like a cable I believe
Speaker 1: that it's a Direct TV commercial is using They're like
Speaker 1: and you we have our very own AI that helps
Speaker 1: you select shows, and then Alan Iversons sitting on the
Speaker 1: couch with the person. Wait, does that make it off limits?
Speaker 2: Yeah?
Speaker 1: Yeah, that's that's a real commercial. And I'm going to
Speaker 1: be running with that joke all day today because I'm
Speaker 1: not any better than the comedy writers at Direct TV.
Speaker 2: I know is Yeah, but what doctor said, Doc?
Speaker 1: Is that good? Doctor said Doc? Is that a good
Speaker 1: way to address you?
Speaker 4: Yeah? Sure, I mean I'm very easy about things. Okay, okay,
Speaker 4: how about Well, I've never been called that. I had
Speaker 4: some students in my class called me ja wow Wow. Yes, yeah,
Speaker 4: is it jo so? So the pronunciation is so, it's
Speaker 4: Brazilian Portuguese. That's what I named.
Speaker 1: I go by.
Speaker 4: Joo jook about it?
Speaker 2: Doctor j even doctor j.
Speaker 1: Amazing?
Speaker 4: All right?
Speaker 1: Well, yeah, I mean the main thing we we've brought
Speaker 1: you here today to ask the big questions around AI,
Speaker 1: such as what is that?
Speaker 2: What is AI?
Speaker 1: And we'll follow from there but you know, questions that
Speaker 1: reveal that we're smart people.
Speaker 2: Obviously.
Speaker 1: No, I actually do think that the fact that AI
Speaker 1: is used as the phrase to describe a bunch of
Speaker 1: different types of technology probably has something to do with
Speaker 1: where people's fear comes from and where people's like kind
Speaker 1: of confusion, where my confusion up to this point has
Speaker 1: come from. But yeah, so we're going to talk to
Speaker 1: you about a bunch of that stuff plenty more. But
Speaker 1: first we do like to ask our guests, what is
Speaker 1: something from your search history that is revealing about who
Speaker 1: you are or where you are in life.
Speaker 4: So I think the most revealing thing about my current
Speaker 4: search history is probably me searching for the which of
Speaker 4: Pfizer or Maderna had the highest amount of mRNA in
Speaker 4: the vaccine, which took me like forever to figure out.
Speaker 4: And that was, you know, a wasted thirty minutes of
Speaker 4: my day where I could have just slacked someone and
Speaker 4: had the answer.
Speaker 2: And wait, why were you trying to discern who which
Speaker 2: had a higher concentration of m marna?
Speaker 4: And yeah, I have a feeling that, like, you know,
Speaker 4: so that was kind of like, okay, the one with
Speaker 4: the higher dosage might still have me slightly more effective.
Speaker 4: The new vaccines have come or have been approved just
Speaker 4: a couple of days ago. Right trying to it.
Speaker 2: Seemed like on a spectrum like MODERNA was having the
Speaker 2: better results, right like on a continuum, I felt like
Speaker 2: the new one, or just in general, because I remember
Speaker 2: when the vaccine first came out, it was like, oh,
Speaker 2: you got Johnson and we got that Jay and J
Speaker 2: and then I was kind of like I had Maderna,
Speaker 2: but as an American consumer, I'm like, but I know
Speaker 2: the brand Peiser more. Yeah, And then I ended up
Speaker 2: being like, Okay, good, I got I got that good one,
Speaker 2: the Moderna it turned out, or at least better than
Speaker 2: the Pfiser slightly more effective there, I.
Speaker 4: Mean, both are extremely effective.
Speaker 2: But yeah, right right.
Speaker 4: Now, that was my That was probably the thing in
Speaker 4: my today's browsing history that told me the most about me,
Speaker 4: which is that I'm still after this many years, paranoid
Speaker 4: about something. I meanach everybody in the wrest of the
Speaker 4: world is sort of moved on about.
Speaker 2: Yeah, for better or worse. But yeah, it does seem
Speaker 2: like that. Yeah, I'm still I'm with you on that
Speaker 2: because like I still somehow have an ego like that
Speaker 2: attached to what brand of fucking vaccine I got, Like, well,
Speaker 2: you know, I got maderna, So you know, I'll sit
Speaker 2: over there with the elevated folks.
Speaker 1: And so it's not you're not googling to see which
Speaker 1: has the more emini or what's it called, m RNA
Speaker 1: mr in it because you are worried that it's going
Speaker 1: to kill you or cause you to start shaking uncontrollably
Speaker 1: like the people in those TikTok videos.
Speaker 4: Just to be clear, I mean, the vaccines have adverse
Speaker 4: side effects, but no, I'm in it for Hey, I'm
Speaker 4: already you know, old enough that you know that's not
Speaker 4: going to really matter. I'm more worried about, you know,
Speaker 4: adverse effects actually getting the disease.
Speaker 2: So yeah, you know, but very scientific answer.
Speaker 4: You know. I was thinking about it, and you know,
Speaker 4: it was funny because I was asking the chat bots
Speaker 4: and so one thing as I work on this stuff
Speaker 4: that's both funny and somewhat annoying to my wife is
Speaker 4: that like I'll do a search and then I'll play
Speaker 4: around with like three different chat bots, and then like
Speaker 4: half an hour later, she's like, have you not been
Speaker 4: listening to me? Right? And I haven't. I've been going
Speaker 4: trying to figure out.
Speaker 1: Where we're going to order from yet.
Speaker 2: I don't know, but being AI thinks that this chain
Speaker 2: is still in New York. It's not.
Speaker 4: Foolish foolishness one exactly. Yeah, and so it's you know, yeah,
Speaker 4: I do tend to get distracted while playing with you know,
Speaker 4: all the cool new things. And I mean both. I
Speaker 4: mean every once in a while, you learn something by
Speaker 4: anecdotally testing something, or you know, somebody making a statement like, oh,
Speaker 4: you know, did you notice like you know, this kind
Speaker 4: of behavior, and I'm like, oh, that's really cool. Okay,
Speaker 4: you know, and then if you go down the path
Speaker 4: of like trying to understand.
Speaker 2: It, right, cool?
Speaker 1: What what's something you think is over it?
Speaker 4: I think that in terms of the things that really overrated,
Speaker 4: like you know, probably artificial general intelligence also known as
Speaker 4: a g I occasionally people think about it like the singularity,
Speaker 4: where you know, we start to assume that, you know,
Speaker 4: the machines are going to take over and we're going
Speaker 4: to be in a terminator world. I think, you know,
Speaker 4: the likelihood of that risk is like super overstated.
Speaker 2: Mm hmm okay, yeah, okay, yeah, that's what that's what I.
Speaker 2: That's what I that's what I learned.
Speaker 1: Well, you actually just answered the only question we had
Speaker 1: on this episode, So I think, sorry, no, no, Yeah.
Speaker 1: So I think coming in like and we'll get to
Speaker 1: this a little bit. But coming into this week's episode,
Speaker 1: like I had, you know, read a couple of articles
Speaker 1: on AI, but I think the artificial general intelligence, like
Speaker 1: the idea of like some chatbot or you know, language
Speaker 1: model or you know, some sort of artificial intelligence deep
Speaker 1: brain model, whatever it is, like gains sentience and that
Speaker 1: then it like takes over weapons systems immediately was like
Speaker 1: the threat that I had in my mind, and after
Speaker 1: like doing some research, is no longer something that is it? Well,
Speaker 1: it doesn't seem to be the one that most people
Speaker 1: are are worried about at least, and then there are
Speaker 1: the people like the well we'll we'll get into it.
Speaker 1: But I do think, yeah, that's an important distinction and
Speaker 1: kind of gets it that first question of like what
Speaker 1: what is AI? Because people use it to stand in
Speaker 1: for a bunch of different things. What what something you
Speaker 1: think is underrated?
Speaker 4: This is maybe mildly underrated, But I think that the
Speaker 4: amount of upheaval that AIM let this generation of technologies
Speaker 4: is going to have in the next couple of years.
Speaker 4: This means that like, you know, certain jobs, so a
Speaker 4: lot of technology, like in the industrial age, has gone
Speaker 4: from lower jobs, like jobs that don't require you know,
Speaker 4: having skill sets that require a large amount of education.
Speaker 4: You know, I think chetchipt already has surfaced evidence of
Speaker 4: being able to either replace or facilitate somebody to be
Speaker 4: much more productive, and that this will actually cause a
Speaker 4: reasonably large amount of change in the workforce globally. You
Speaker 4: know that I think will have real impact, right and
Speaker 4: could cause problems, you know, with more erosion of middle
Speaker 4: class jobs and you know, needing to have like sort
Speaker 4: of deeper retraining.
Speaker 1: Interesting, what are the yeah, I guess, I guess let's
Speaker 1: let's dig into it, Like what are the jobs that
Speaker 1: you see being replaced, because like the ones that we've
Speaker 1: heard most about specifically, and I've seen sort of poor
Speaker 1: results for are the writing jobs, Like when people are like, no,
Speaker 1: we're just gonna have AI like write these articles for
Speaker 1: us now, and they seem like they do kind of
Speaker 1: a bad job and they have a tough time with
Speaker 1: like fact checking. What what where are you going?
Speaker 4: Where do you.
Speaker 1: Expect to see the kind of changes in the workforce first,
Speaker 1: because I get I guess I will caveat that by
Speaker 1: saying that it doesn't seem like a lot of companies
Speaker 1: care if the technology does a bad job. They're just like, yeah,
Speaker 1: but it's it's good enough to put butts in the seats,
Speaker 1: and it's less money, and the entire model of capitalism
Speaker 1: currently because of private equity, and you know, just that
Speaker 1: being how the incentive system is set up is like
Speaker 1: to cut costs. So maybe it won't matter and it'll
Speaker 1: just like make journalism shittier and have all journalists jobs
Speaker 1: replaced by these ais. But what where is that? Is
Speaker 1: that kind of where you see it? Or where where
Speaker 1: do you see the AI replacing jobs?
Speaker 4: Well, so, okay, so I think creatively true creative writing,
Speaker 4: right like things that JOURNALI writing from journalists, or let's
Speaker 4: say creative writing, songwriting, poetry. These are require such deep
Speaker 4: understanding of people and theory about how people interpret the
Speaker 4: words and the language and sort of the reactions and
Speaker 4: emotions that are evolved that I don't think AI is
Speaker 4: going to help very much with that. I think, sorry,
Speaker 4: replace right, I think it can help right and make
Speaker 4: you more productive but I don't think it's really going
Speaker 4: to be let's say, a replacement for a journalist. But
Speaker 4: some stuff that people do that are performa like a
Speaker 4: performer report, right, that's you know, almost template based, but
Speaker 4: not quite you know. So somebody's got to do some filing. Well, okay,
Speaker 4: CHT GBT can do this, you know, well enough for
Speaker 4: you know, for me that Okay, here's a filing. Very
Speaker 4: few people are probably going to look at it. Let
Speaker 4: me use chat GUPT, you know, and maybe not need
Speaker 4: to hire someone to do that, right. I think the
Speaker 4: other thing where we're going to see a lot of
Speaker 4: changes also in you know, coding. Here, I think we're
Speaker 4: seeing already the impact of it, where there's this tool
Speaker 4: called Copilot which is driven by similar technology as chatchept,
Speaker 4: which is able to create massive amounts of code for people.
Speaker 4: So it's making a certain subset of coders just way
Speaker 4: more efficient, you know. I see that in even with
Speaker 4: my students. So I teach a undergraduate data science class.
Speaker 4: Last semester, the projects that my students were able to
Speaker 4: do was actually much more impressive than the previous semester,
Speaker 4: and part of that was just them being able to
Speaker 4: use chat GUPT to be able to make better code
Speaker 4: to make their projects better.
Speaker 2: It is like I was just reading like an op
Speaker 2: ed from a former IBM employee that he's like describing
Speaker 2: himself as like a tech evangelist and had always been
Speaker 2: you know, you know, say like cheering on like the
Speaker 2: advent or the arrival of chat, GPT and things like that,
Speaker 2: And he said, and I only it only ended up
Speaker 2: actually taking a lot of work from me, like because
Speaker 2: some companies who were less interested in good writing were like,
Speaker 2: we're actually gonna use a lot of this for like
Speaker 2: content generation, so we don't need you know.
Speaker 1: Like your services as much. He said.
Speaker 2: It hasn't completely replaced him, but it's a signific He's
Speaker 2: he has noticed this more than significant amount of like
Speaker 2: businesses sort of be like, you know.
Speaker 1: What, we're kind of gonna just sort of lean.
Speaker 2: Into this thing that costs like way less money, and
Speaker 2: are these kind of like the stories that are like
Speaker 2: canaries in the coal mine. But I feel like, sort
Speaker 2: of like in the industrial age, we've always seen like
Speaker 2: there was just automation right where people who had jobs
Speaker 2: at a bank to do specific things like file things
Speaker 2: or put things in a ledger, ended up like those
Speaker 2: jobs ended up going away because of automation or just
Speaker 2: you think of customer service now a lot of that
Speaker 2: is automated. And I was also reading about how a
Speaker 2: lot of local governments are now adopting or really interested
Speaker 2: in chat bots as a way to like sort of
Speaker 2: replace bureaucracies at certain levels. Like is that kind of
Speaker 2: is that sort of where you see it ending or
Speaker 2: what like what's the sort of fifty year outlook, because
Speaker 2: I think to Jack's point two, we always look at
Speaker 2: this as like, well, when we're trying to reconcile that
Speaker 2: with like capitalism and the corporation's need to like always
Speaker 2: look at their bottom line, is it a thing that
Speaker 2: there we can strike a balance where it's like, yeah,
Speaker 2: we have these human employees who use this as a
Speaker 2: tool obviously because it makes them better or or is
Speaker 2: it like the cynical version is like they're going to
Speaker 2: get as much as they can done with it, only
Speaker 2: up until the point that they probably need human workers
Speaker 2: to kind of really fine tune the processes.
Speaker 4: Yeah, I think the latter. I mean, I think you know,
Speaker 4: the company is their interest is to optimized, so there,
Speaker 4: I mean, the truth of the matter is that the
Speaker 4: tool right now, right is just not good enough for
Speaker 4: most you know, really for most tasks. I think, you know,
Speaker 4: fifty years from now is a really hard thing for
Speaker 4: me to predict.
Speaker 1: I know, but you have to know, you know, it's
Speaker 1: a wild speculation, but sound extremely common because because this.
Speaker 2: Is going to go on TikTok and we're going to
Speaker 2: scare the heck out of a lot of young people.
Speaker 2: So go ahead, you're saying, how sky net is imminent?
Speaker 4: Yees, sky net is imminent. You know, I'm kidding. So
Speaker 4: I think that you know, looking forward, like looking far
Speaker 4: forward into where I think it will be in you know,
Speaker 4: maybe ten or fifteen years. Sure, this technology is just
Speaker 4: really just going to improve. And what we're going to
Speaker 4: see is that, you know, we will have certain jobs
Speaker 4: which were done by people for a very long time
Speaker 4: go away. That will probably mean the new jobs will
Speaker 4: open up and people will just be more productive. That's
Speaker 4: the sort of optimist in me, right.
Speaker 1: That's also how everything has happened to this point, right,
Speaker 1: is that like people are at first scared of new technology,
Speaker 1: like airplanes are going to be really scary, and like
Speaker 1: make it so the you know, nobody has to ever
Speaker 1: take a train and it's like, well, then there's like
Speaker 1: the entire aerospace jet propulsion industry, and you know, I
Speaker 1: guess that one's a little easier to foresee, but like,
Speaker 1: it does feel like there's always fear of new technology
Speaker 1: and like belief that it's going to end the economy
Speaker 1: as we know it, and it does, but it's always
Speaker 1: replaced by a new a new version, right.
Speaker 4: Yep, exactly, And so I think, you know, we're going
Speaker 4: to see something similar in this some questions of factuality.
Speaker 4: Sometimes people call this hallucinations in our models. How difficult
Speaker 4: is that going to be to really fix those sort
Speaker 4: of corner cases. But you know, given the amount of
Speaker 4: money and people that are working on this, you know,
Speaker 4: I think that within the next ten to fifteen years
Speaker 4: we're going to see that you know, a lot of
Speaker 4: that gets solved, or at least the likelihood of it
Speaker 4: coccurring is so small that it's you know, more that
Speaker 4: the likelihood of it, you know, lying to you or
Speaker 4: saying something that is untrue is going to be you know,
Speaker 4: way way way less than any person. Right, So that's
Speaker 4: kind of where where I think we're going. And so
Speaker 4: we'll see, you know, some jobs like you know, entry
Speaker 4: level coders, make away certain jobs like you know, certain
Speaker 4: types of business analysts, even some form of middle management
Speaker 4: I think is at risk. You know, lots of various
Speaker 4: amounts of places I think are at risk. I do
Speaker 4: want to say one other thing, which I think is
Speaker 4: going to be amazing. And we're seeing this in higher education,
Speaker 4: but in education in general. Is it Probably the place
Speaker 4: that's been most impacted by chat GPT has been education.
Speaker 4: And I think what we'll see is in the next
Speaker 4: ten to fifteen years, education is just going to dramatically reform, right,
Speaker 4: hopefully for the better, but like we're going to see
Speaker 4: like major changes in how we teach students, how we
Speaker 4: assess students. Hopefully this will lead to you know, just
Speaker 4: better quality of education for everyone.
Speaker 2: Right, because is it sort of like the main I
Speaker 2: guess I feel like the point of our traditional educational
Speaker 2: system is like almost like memory recall. It's like how
Speaker 2: good is your factor recall? Memory recall and things like
Speaker 2: that at or can you sit through reading this thousand
Speaker 2: page historical textbook to glean like these eight points really
Speaker 2: that we want you to come away with it come
Speaker 2: away with and I see, like how much that distillation
Speaker 2: of information how quickly that occurs with like you know, chat,
Speaker 2: GPT and things like that. So I guess it does
Speaker 2: become more like, Okay, granted, if this is the information
Speaker 2: we want people to learn, then how are we now
Speaker 2: taking that next step to make sure it's sort of
Speaker 2: ingested properly for people to know that they are making
Speaker 2: sense of it, rather than like being like, yeah, here
Speaker 2: are the eighteen things you need to say to pass
Speaker 2: like a like a historical course on the Colombian Exchange,
Speaker 2: and more like Okay, we know you know how to
Speaker 2: get to those answers, but how can you demonstrate that knowledge?
Speaker 2: And I guess that's sort of where the I guess
Speaker 2: excitement is in academia, or at least that's the challenge, right.
Speaker 4: Yeah, yeah, it's the challenge, the worry, the you know,
Speaker 4: and I guess excitement goes in both ways positive and
Speaker 4: negative depending on what you are and how you want
Speaker 4: to deal with this. But I think that like this
Speaker 4: has this type of technology has the potential of being
Speaker 4: you know, a tutor and a tutoring system that is
Speaker 4: almost as good as you know, the best tutor, where
Speaker 4: we can help people learn better and just be able
Speaker 4: to interactively one on one, you know, sort of teach
Speaker 4: certain concepts and.
Speaker 1: Like with an AI teacher or you're saying it would
Speaker 1: help teachers teach.
Speaker 4: Help teachers, help teachers. So it'd be like a tutor, right,
Speaker 4: so you know, the teacher is still going to teach,
Speaker 4: but the tutor is going to be able to, like
Speaker 4: the AI tutor is going to be able to, you know,
Speaker 4: help the student with Okay, I didn't understand this, right,
Speaker 4: Like I mean, and one thing that we do know
Speaker 4: about chatbots is that in general, you know, people have
Speaker 4: this impression that chat bots have less judgment, right, and
Speaker 4: so people are willing to ask you know, in air quotes,
Speaker 4: stupid questions.
Speaker 2: Thank you, Yeah, because no questions are stupid.
Speaker 4: Yeah, we're in a classical classroom. You know, they wouldn't
Speaker 4: be able to they wouldn't be willing to ask that
Speaker 4: to a person, and they're willing to ask you to
Speaker 4: the AI. Yeah. I don't know.
Speaker 1: As a parent, I would be very worried just based
Speaker 1: on the work I've seen from chatbots up to this point,
Speaker 1: Like like what at this point, we've covered Yeah, up
Speaker 1: to this point, like we've covered the Columbus dispatch like
Speaker 1: recap of like of football game, like high school football game,
Speaker 1: and it's just like such absolute shit. It's like one
Speaker 1: of the worst articles I've ever read, you know, the
Speaker 1: sports the Star Wars one that Gis Moto put up
Speaker 1: is terrible. So I don't like I I believe that,
Speaker 1: like the chatbots will continue to get better, but I
Speaker 1: guess I have questions about what they're going to get
Speaker 1: better at, whether they're going to get better at like
Speaker 1: fooling us into thinking that they have like human intelligence,
Speaker 1: or whether they're gonna get like more more accurate, because
Speaker 1: it seems like within the world of AI, like there's
Speaker 1: still people who are like I think it was somebody
Speaker 1: who worked it open AI was like Wikipedia level accuracy
Speaker 1: is like years off at this point, and like like
Speaker 1: Wikipedia is suddenly being used as this phrase for like
Speaker 1: something that is like the gold standard, whereas like before,
Speaker 1: outside of the context of AI training, it's something that
Speaker 1: we like joke about being easy, easily editable and stuff.
Speaker 1: So yeah, it worries me a little bit like that.
Speaker 1: I think people's faith is being misplaced in the language
Speaker 1: models because language is inherently an abstractive system that is
Speaker 1: designed to lie like essentially, it's I mean, it's to
Speaker 1: tell you a story that gives you meaning. But it
Speaker 1: feels like from a philosophical level like that, I see that.
Speaker 1: I see where people who are skeptical that this is
Speaker 1: the path to like really useful stuff are coming from.
Speaker 1: But let's take a quick break and we'll come back.
Speaker 1: And I just I do just want to like kind
Speaker 1: of nail down two different things that are being called
Speaker 1: AI that seem vastly different to me.
Speaker 5: So let's let's take a quick break. We'll be right back,
Speaker 5: and we're back.
Speaker 1: So yeah, I guess I think Chad GBT seems to
Speaker 1: be the thing that everyone has been taken by like
Speaker 1: very like interested in right like that, it seems to
Speaker 1: have reached a new level where people can do things
Speaker 1: and have conversations that are remarkably like human seeming and
Speaker 1: can do right really a good maybe B minus term
Speaker 1: papers and then use that to kind of scrap together
Speaker 1: something or depending you know, maybe maybe it's a higher
Speaker 1: level of term paper. I don't grade term papers, so
Speaker 1: I wouldn't know, But just based on the journalistic work
Speaker 1: I've seen it, Dove, I haven't been impressed. But so
Speaker 1: that's the main thing that I'm hearing referred to as AI,
Speaker 1: and they're like this, there's a new future upon us.
Speaker 1: Look at chat GPT, and then there's like when you
Speaker 1: look into some of the things that are being done
Speaker 1: with machine learning, like accurately predicting how proteins fold, which
Speaker 1: is like a problem that has been just input too
Speaker 1: complex for humans to solve on their own, just like
Speaker 1: too slow for humans to know the atomic shape of proteins,
Speaker 1: Like they just kind of fold in ways that he
Speaker 1: is like too small, too complicated for humans to predict,
Speaker 1: and like through machine learning and like this deep brain
Speaker 1: system at Google, they were able to like knock it
Speaker 1: out within a couple of years, and like they gave
Speaker 1: it to the public. They were like here, here is
Speaker 1: the shape of the proteins. And so if you're using
Speaker 1: AI to describe both of those things, I think that
Speaker 1: is that's where the creepiness comes in, because you're like, Okay,
Speaker 1: it has this like godlike science ability, and then it
Speaker 1: also has this like child personality where it like can
Speaker 1: like talk to you and flirt with you a little bit,
Speaker 1: and it's like that that mismatch seems uncanny and weird
Speaker 1: to me. Like, and I think that that is what
Speaker 1: is happening in people's minds when they're like, oh, yeah,
Speaker 1: AI is scary. It's this like massively powerful thing, and
Speaker 1: it is massively powerful. I think it's just more massively
Speaker 1: powerful when it has a task and like a specific
Speaker 1: thing that it's seeking, which is not what you can
Speaker 1: really have with the language models, which are like predictive. Right.
Speaker 4: Yeah. I think I think it's kind of unfair in
Speaker 4: the way that people characterize the language models as like, oh,
Speaker 4: they just predict the next word, right, I mean, in
Speaker 4: some sense, it's what we know of what the language
Speaker 4: model is trying to do, is it is trying to
Speaker 4: predict some sequence of text, and in doing so, it's
Speaker 4: learning a whole bunch of the knowledge in the world
Speaker 4: and how the world is connected. It's learning some seemingly
Speaker 4: probabilistic logic rules. Yeah. However, yeah, I mean this is
Speaker 4: oftentimes you see this weird sort of disconnect between chatjepte
Speaker 4: or that technology, which we call large language models in
Speaker 4: general being so smart and so stupid at the same.
Speaker 1: Time, right, Right, that's kind of our specialty on the show.
Speaker 4: Well, and and I think as we as like society
Speaker 4: interact with the technology more and more, we're going to
Speaker 4: get sort of a better mental model of the technology,
Speaker 4: right and in some sense, like right now, a lot
Speaker 4: of people, you know, I ask my students, okay, like
Speaker 4: what do you think of Like, how do you reason
Speaker 4: about chat GPT?
Speaker 2: Right?
Speaker 4: How do you reason about the quality of the technology
Speaker 4: and how it you know, is you know, understanding the
Speaker 4: input and giving you output. And some people think about
Speaker 4: it kind of like this person, and you know, reason
Speaker 4: about it like a person. Other people see it like
Speaker 4: Google Search, but just a really really interactive version of
Speaker 4: Google Search. Sure, and somehow it's somewhere in between, which
Speaker 4: I think is like the weird sort of place that
Speaker 4: we're at. And you know, I think that the fact
Speaker 4: that the same type of deep learning and machine learning
Speaker 4: models can predict protein folding and find new, you know,
Speaker 4: ways of inverting matrices that are even more efficient and
Speaker 4: doing all this very very incredible intelligent stuff at the
Speaker 4: same time as you know, making incredibly dumb statements is
Speaker 4: something that we will like people are going to have
Speaker 4: to deal with rights as Okay, you know, there's this
Speaker 4: weird disconnect. You know, if you think about it like
Speaker 4: a person, it just it's not a person, right, it's
Speaker 4: not a you know, it doesn't map on Like in general,
Speaker 4: we like to take technologies or different types of constructs
Speaker 4: and map them onto what we already know. And in
Speaker 4: some sense it's not mapping well onto what we already know,
Speaker 4: and so we're gonna have to figure out how to
Speaker 4: sort of properly map it onto its own new sort
Speaker 4: of construct.
Speaker 1: Yeah, I get like the one thing that you know
Speaker 1: in talking about it as like well, it's just predicting
Speaker 1: the next word, or you know, it's doing like when
Speaker 1: you describe the very specific tasks that's being programmed to
Speaker 1: do versus the emergent abilities that are coming out of
Speaker 1: that task. Like the analogy that I heard used that
Speaker 1: that made senses Like, I guess it's a quote from
Speaker 1: Darwin that like from so simple a beginning, endless forms
Speaker 1: most beautiful, like that that quote being applied to basically
Speaker 1: the argument is like that's all the human mind is doing. Also,
Speaker 1: like in some ways, like the human mind is just
Speaker 1: can can be seen as being programmed to like look
Speaker 1: for lions in the bushes and move towards food and procreation,
Speaker 1: and then like from all of these like complicated synapses firing,
Speaker 1: you get this amazing thing called consciousness, and that you know,
Speaker 1: just by describing AI in a reductive way, you're ignoring
Speaker 1: the fact that, like it could be these very basic
Speaker 1: things and also be moving towards you know, what we
Speaker 1: describe as what we think of as consciousness. So yeah,
Speaker 1: I think, yeah, it's a super interesting conversation. That was
Speaker 1: Like I think I was scared to like read into
Speaker 1: like to get like to research because it's just so
Speaker 1: massive and like when I was I was a philosophy
Speaker 1: major in college, and when I was studying philosophy back
Speaker 1: in like the early two thousands, like AI, Like the
Speaker 1: question of AI and what was going to happen was
Speaker 1: like a major question in philosophy all the way back then.
Speaker 1: And it's like all of the all of the ways
Speaker 1: that philosophers have been like thinking about and asking all
Speaker 1: the questions they've been asking about AI for you know,
Speaker 1: since like the sixties are now like coming to a forum,
Speaker 1: like as we've gotten closer to the moment, we still
Speaker 1: don't really have any clearer of an idea of like
Speaker 1: what exactly is going to happen. So it's it's a
Speaker 1: little scary. I do want to. I do want to
Speaker 1: take a break and then come back and just talk
Speaker 1: about like kind of some specific ways, just like take
Speaker 1: some guesses as to like specific ways that the future
Speaker 1: might look different, that we might not be that I
Speaker 1: at least going into like researching this hadn't hadn't been
Speaker 1: taken into account as a possibility. So we'll be right
Speaker 1: back and we're back and Miles, I mean we we
Speaker 1: talk a lot about how we we what we think
Speaker 1: this future is going to look like?
Speaker 2: Right, Yeah, I mean I share the name with Miles Dyson.
Speaker 1: Ever heard of him.
Speaker 2: I started a little thing called the sky net, you
Speaker 2: know that keeps me up all night?
Speaker 1: Well but seriousness, I hey, he went out of here, Miles,
Speaker 1: you know I did. I did.
Speaker 2: Look it's all about altruism, you know at the end.
Speaker 2: But like I think for me personally, right, so much
Speaker 2: of my so much of my understanding of science is
Speaker 2: derived from film and television because I'm American, and I
Speaker 2: think with like with Ai, I think whenever I would
Speaker 2: think of like, oh my, like he's like, you don't
Speaker 2: know this thing's gonna go. The place I think it's
Speaker 2: gonna go is sky net from Terminator.
Speaker 1: Just see the shot from the sky of all the
Speaker 1: missiles being launched just coming down.
Speaker 2: I'm trying to have a nice day at the park
Speaker 2: with my kids. I'm watching through a chain link, and
Speaker 2: next some.
Speaker 1: Ladies over there shaking the chain link and skeletons rattling
Speaker 1: the kids over there.
Speaker 2: Get her out of here. But I'm you know, first
Speaker 2: of all, it's sort of twofold question, how how far
Speaker 2: off base is the idea of like how many jumps
Speaker 2: am I making in my brain to be like Chad
Speaker 2: gbt next stop sky net? And and then also because
Speaker 2: of that, what are all of the ways that people
Speaker 2: like me are not considering what those actual, real tangible
Speaker 2: effects will be of. And I don't want to be
Speaker 2: like the most cynical version, but you know, if we
Speaker 2: aren't careful and we have very sort of individualistic or
Speaker 2: profit minded sort of motivations to develop this kind of technology,
Speaker 2: like what does that worst case sort of look like
Speaker 2: or not worst case? But what are the ways I'm
Speaker 2: actually not thinking of because I'm too busy thinking about
Speaker 2: T one thousands?
Speaker 1: Right, Like I just to like add on to that,
Speaker 1: when when I think about the computer revolution, like for
Speaker 1: decades it was these people in San Francisco talking about
Speaker 1: how the future was going to be completely different and
Speaker 1: done on computers or something called the Internet, And we
Speaker 1: were just down here looking at a computer that was
Speaker 1: like green dots, like not that good of a screen display.
Speaker 1: And by the time it like filtered down to us
Speaker 1: and the world does look totally different, it's like, well, shit,
Speaker 1: like that's that turns out that was a big deal.
Speaker 1: So yeah, I feel like I want to be constantly,
Speaker 1: like on our show, just asking me a question like
Speaker 1: where is this actually taking us? Because some in the past,
Speaker 1: I feel like it's been hard to predict and when
Speaker 1: it did come, it wasn't exactly what the you know,
Speaker 1: tech oracles said it was going to be, and it
Speaker 1: was like unexpected and weird and beautiful and banala and
Speaker 1: weird ways. And so I'm curious to hear your thoughts
Speaker 1: on like once this technology reaches the level of consumers,
Speaker 1: like of just your average ordinary person who's like not
Speaker 1: teaching machine learning at m YU, like, what what is
Speaker 1: it going to look like?
Speaker 2: But first but obviously first, but first guy, I.
Speaker 4: Think it's kind of okay. So so I think the
Speaker 4: idea of worrying about some version of you know, this
Speaker 4: technology going out of control, right is there's so many
Speaker 4: checks and balances of ways in which we are thinking
Speaker 4: about and the technology is sort of moving forward. That
Speaker 4: is kind of you know, the idea of something emergent
Speaker 4: and then not only as an emergent, but it's going
Speaker 4: to take over and try to destroy civilization.
Speaker 2: And almost send and also send cybernetic organisms into the
Speaker 2: past to ensure that those people do not grow up
Speaker 2: to take arms. I can't kind of like John Connor and.
Speaker 4: Yeah, yeah, So I'm a firm believer that in being
Speaker 4: able to send people to the future, I still don't
Speaker 4: think that we're not going to be able to send
Speaker 4: people in the past. So that's that's maybe one problem.
Speaker 1: But that's just like your opinion. Man, all right, I'm
Speaker 1: is gonna happen. And by the way, I'm the Doc
Speaker 1: Brown character. I'm gonna be friend a young child, Yeah right, exactly,
Speaker 1: Like Marty and Doc been friends like probably like it
Speaker 1: seems like eight years so like when Marty was like
Speaker 1: nine years old, they became best friends. Anyways, sorry about
Speaker 1: that forgetting sidetracks so well, So I think you know,
Speaker 1: so what I'm what I'm thinking about when we think
Speaker 1: about this kind of technology and how it could be,
Speaker 1: how the technology itself could go wrong.
Speaker 4: I don't think that that kind of integration is likely, right.
Speaker 4: I think that the concept of you know, the singularity,
Speaker 4: it's so far out, and I don't think that we
Speaker 4: have a good ability or understanding of like consciousness. And
Speaker 4: I also don't think we have a really good understanding
Speaker 4: of like, Okay, you know, why would you know these
Speaker 4: large language models start, you know, trying to harm us.
Speaker 4: So there's all those steps and jumps and leaps and
Speaker 4: all the intermediate pieces. That just seems so incredibly unlikely. Now.
Speaker 4: I know that a lot of the ai AGI people
Speaker 4: who worry, they worry is, oh, well, we got to
Speaker 4: worry about this tail race, great, and a human level
Speaker 4: extinction event is worth worrying about. Yeah, and some people
Speaker 4: worrying about that is probably not a bad thing. But
Speaker 4: I just think it's very unlikely for the reasons of
Speaker 4: those of all the chain that would need to happen,
Speaker 4: and we're not very good at robots. Also, robots are
Speaker 4: you know, actually much further away.
Speaker 1: But that is one Okay, well, we'll talk about it,
Speaker 1: but let put a pin in that because I want
Speaker 1: to come back to that to bad robots, to bad robots,
Speaker 1: and how easy I just want to brag about how
Speaker 1: easy it would be for me to beat one up.
Speaker 2: But dynamics, Yeah, yeah, I got my on you in
Speaker 2: that fight.
Speaker 4: But the thing that I do want to point out
Speaker 4: is that, you know, the concept of starting to build
Speaker 4: some of these rules into the large language models, you know,
Speaker 4: to try to say, okay, well, you know, try to
Speaker 4: be benign, don't do harm. Like that's a really super
Speaker 4: good idea, right, And I think that, you know, even
Speaker 4: if you don't believe in sky Neet, actually believing in
Speaker 4: trying to incorporate responsibility into the large language models, I
Speaker 4: think that is something that's very important moving into some
Speaker 4: of the dangers though, Like I think actually large language
Speaker 4: models and people like Opening Eye was actually worried about
Speaker 4: this in one of its first iterations of GPT was
Speaker 4: the ability for the large language models to create misinformation
Speaker 4: and disinformation. And you know, I think that that's a
Speaker 4: really bad use of the technology and very very potentially harmful.
Speaker 1: And it already seems to be what it's being used for.
Speaker 1: Like the technology, like the ways that like companies are
Speaker 1: trying to replace journalism with it, or you know, clickbait article,
Speaker 1: like just generate tons of clickbait articles that are like
Speaker 1: targeted at people. Is like it, it feels like it's
Speaker 1: already training in that in a lot of ways.
Speaker 4: Yeah, Unfortunately, I think you're right like that, that there
Speaker 4: is this that there is this bad use of the
Speaker 4: technology where it's like, oh, let's make this so that
Speaker 4: it could be as persuasive as possible. You know, there's
Speaker 4: obviously been a ton of research in marketing on like
Speaker 4: figuring out, okay, how do we you know, position this
Speaker 4: product so that it's you know, you're more likely to
Speaker 4: buy it, right, And the same thing can be now
Speaker 4: applied to language of like okay, you know, for Jacob Ryan,
Speaker 4: how am I going to make this tailored advertisement just
Speaker 4: for him to be able to do to make him
Speaker 4: buy this particular product that I'm selling, or to make
Speaker 4: him not vote right? Yeah? Right, you know those kind
Speaker 4: of that's I mean, I think that this is scary,
Speaker 4: and I think that this is in the now, right,
Speaker 4: which you know, is something that in some sense is
Speaker 4: going to be hard to like really stop people from
Speaker 4: using this technology in that direction without things like legislation,
Speaker 4: you know, there's just some some components that need, you know,
Speaker 4: more legislation, and I think that's going to be hard
Speaker 4: to do but probably necessary. Right.
Speaker 2: Yeah, I could even see, like just even in politics,
Speaker 2: you can be like, Okay, I need to actually figure
Speaker 2: out the best campaign plan for this very specific demographic
Speaker 2: that lives in this part of this state, and sure,
Speaker 2: and then just imagine what happens. But I guess is
Speaker 2: that also part of the slippery slope is that like
Speaker 2: the reliance sort of gives way to like sort of
Speaker 2: this like thing where it's like this actually is gonna
Speaker 2: whatever this says is the solution to whatever problem we
Speaker 2: have and like just kind of throwing our hands up
Speaker 2: and all just becoming totally reliant. I mean, i'd imagine
Speaker 2: that's also seems like a place where we could easily
Speaker 2: sort of slip into a problem where it's like, yeah,
Speaker 2: the chatbot may give us this answer.
Speaker 4: But well, or or that people are starting to make
Speaker 4: like very homogeneous decisions and choices right where you would
Speaker 4: make you know, many different choices by because you already
Speaker 4: have a template that's been given to you by you
Speaker 4: know this AI. You're like, oh, okay, well, you know
Speaker 4: I'm just gonna follow you know, this choice or this
Speaker 4: decision that it's going to make for me and not
Speaker 4: you know, do one of the thousand different alternatives right, right,
Speaker 4: and if you do that, I do that. Jack does that, right,
Speaker 4: Like all of a sudden, we would have done vastly
Speaker 4: different choices. But now we have this sort of weird,
Speaker 4: sort of centering effect where all of us are actually
Speaker 4: making much less, you know, very choices in our decision making, right,
Speaker 4: which has I mean it does possess real risk. I
Speaker 4: mean imagine applying this to resume screen right where you
Speaker 4: could imagine the same type of problem, right, and those
Speaker 4: are there's just so many scenarios that you can think
Speaker 4: of where you know, we need to take care, right, Yeah,
Speaker 4: and this is a good time to think about that.
Speaker 1: Right, And we're yeah, we're turning our free will over
Speaker 1: to the care of algorithms and you know, the phones,
Speaker 1: like the skinner boxes in our hands that we're carrying around,
Speaker 1: and like that feels like a thing that's already happening.
Speaker 1: A I might just make it a little bit more
Speaker 1: effective and like quicker to respond and like but yeah,
Speaker 1: it feels like a lot of the concern over AI
Speaker 1: that makes the most sense to me are the ones
Speaker 1: that are already happening. And yeah, just in like to
Speaker 1: kind of tip my head a little bit, like the
Speaker 1: in doing a lot of research on the kind of
Speaker 1: overall general intelligence concerns that we've been talking about, the
Speaker 1: ones where it like takes over and evades human control
Speaker 1: because it wants to you know, wants to defeat humans.
Speaker 1: I was surprised how full of shit those seemed to be. Like,
Speaker 1: for instance, one story that got passed around a lot
Speaker 1: last year where a like during a military exercise and
Speaker 1: AI was being told not to like take out human
Speaker 1: targets by its human operator, and so the AI made
Speaker 1: the decision to kill the operator so that it could
Speaker 1: then just like go rogue and start killing whatever it
Speaker 1: wanted to. And that story, like I passed around a lot.
Speaker 1: I think we've even like referenced it on this show.
Speaker 1: And it's not true. First of all, I think when
Speaker 1: it first got passed around, people were like it actually
Speaker 1: killed someone man, and it was it was just a
Speaker 1: hypothetical exercise first of all, like just in the story
Speaker 1: like as it was being passed around, And second of all,
Speaker 1: it was then debunked, like the person who said that
Speaker 1: it happened in the exercise later came out and was
Speaker 1: like that, actually, like that didn't happen. But it seems
Speaker 1: like there is a real interest and real incentive on
Speaker 1: behalf of the people who are like set up to
Speaker 1: make money off of these ais to like make them
Speaker 1: seem like they have this like godlike reasoning power. There's
Speaker 1: this other story about where like they were testing the
Speaker 1: I think it was GPT four to see like like
Speaker 1: during the alignment testing. Alignment testing is like trying to
Speaker 1: make sure that the AI's goal are aligned with humanities
Speaker 1: and like making humans more happy, and they like ran
Speaker 1: a test to see where the GPT four was basically
Speaker 1: like I can't solve the capture, but what I'm going
Speaker 1: to do is I'm going to reach out to a
Speaker 1: task rabbit and hire a task rabbit to solve the
Speaker 1: capture for me. And the GPT four made up a
Speaker 1: lion said that he was visually impaired and that's why
Speaker 1: he needed the task grabbit to do that. And again
Speaker 1: it's like one of those stories like it feels creepy
Speaker 1: and it gives you goosebumps, and again it's not true.
Speaker 1: It's like they were the GPT was being prompted by
Speaker 1: a human, Like it's very similar to the self driving
Speaker 1: car myth, like that that self driving car viral video
Speaker 1: that Elon Musk put out where it was being prompted
Speaker 1: by a human and like pre programmed, and like that.
Speaker 1: There were all these ways that the human agency involved
Speaker 1: with the kind of clever task that we're worried about
Speaker 1: this thing having done. We're just like taking out. We're
Speaker 1: just edited out so that they could tell a story
Speaker 1: where it seemed like the GPT four, which is like
Speaker 1: what powers chat GPT that like it was doing something evil, right,
Speaker 1: And it's like so it's I get how these stories
Speaker 1: get out there and become like because they're they're the
Speaker 1: version of AI that we've been preparing for because like
Speaker 1: and watching Terminator. But it's surprising to me how much
Speaker 1: like Sam Altman, the head of Open AI, like just
Speaker 1: leans into that shit and is like he like he
Speaker 1: in an interview with like The New Yorker, he was like, yeah,
Speaker 1: I like keep a Sinai capsule on me and like
Speaker 1: all these weapons and like a gas mask from the
Speaker 1: Israeli military in case like an AI takeover happens and
Speaker 1: it's like what, like you of all people should know
Speaker 1: that that is complete bullshit, but it and it totally
Speaker 1: like takes the eye off the ball of like how
Speaker 1: the actual dangers that AI poses, which is that it's
Speaker 1: going to just like flood the zone with shit, like
Speaker 1: it's going to keep making the Internet and phones like
Speaker 1: more and more unusable but also more and more like
Speaker 1: difficult to like tear ourselves away from. Like I feel
Speaker 1: like we've already lost the alignment battle in the sense
Speaker 1: that like we've already lost any way in which our
Speaker 1: technology that is supposed to like serve us and make
Speaker 1: our lives better and enrich our happiness like are doing that,
Speaker 1: Like they they stop doing that a long time ago.
Speaker 1: Like That's why I always like say that the more
Speaker 1: interesting question, like with the questions that were being asked
Speaker 1: in philosophy classes in the early two thousands about like
Speaker 1: singularity and like suddenly this thing spins off and is
Speaker 1: we we don't realize we're no longer being served and
Speaker 1: like we're like twenty steps behind, like that happened with
Speaker 1: capitalism a long time ago, Like that we're like capitalism
Speaker 1: is so far beyond and it's like, you know, We're
Speaker 1: no longer serving ourselves and serving fellow humanity. We're like
Speaker 1: serving this idea of the market that is just you know,
Speaker 1: repeatedly making decisions to make itself more efficient, take the
Speaker 1: friction out of like our consumption behavior. And yeah, I
Speaker 1: think AI is going to definitely be a tool in that.
Speaker 1: But like that is the ultimate battle that we're already losing.
Speaker 4: Yeah, I mean I completely agree with you on the
Speaker 4: on the front of like your phonees are I mean,
Speaker 4: the company is are trying to maximize their profits, which
Speaker 4: mean you know, possibly you being on your phone at
Speaker 4: the disservice doing something else like going outdoors and doing exercise, right,
Speaker 4: or you know, doing something social. I I do see
Speaker 4: on the other hand, that like, you know, maybe I
Speaker 4: can have positive effects right where you know, take tutoring
Speaker 4: for an example, or public health, where we take the
Speaker 4: phone and take the technology and use it for benefit,
Speaker 4: like providing information about public health by helping students who
Speaker 4: don't have the ability to have a tutor have a tutor, right,
Speaker 4: Like all of these kind of things where let's take
Speaker 4: advantage of the fact that you know, the majority of
Speaker 4: the world has phones, right and try to use that
Speaker 4: technology for you know, a good positive societal benefit. But
Speaker 4: like any tool in it has usage that are both
Speaker 4: good and bad. And I do think, like, you know,
Speaker 4: there's going to be a lot of uses of this
Speaker 4: technology that are not necessarily in the best interests of
Speaker 4: humanity or individual people.
Speaker 2: Right, So it's like really like sort of the real
Speaker 2: X factor is how the technology is being deployed and
Speaker 2: for what purpose, not that the technology in and of
Speaker 2: itself is like this runaway train that we're trying to
Speaker 2: rein in. It's that, yeah, if you do phone scams,
Speaker 2: you might come up with better you know, like both
Speaker 2: like voice models to get this Rather than doing one
Speaker 2: call per hour, you can do a thousand calls in
Speaker 2: one hour running the same script and same scam on people.
Speaker 2: Or to your point about how do you persuade Jack
Speaker 2: O'Brien to not vote or to buy X product? Then
Speaker 2: it's all going in that direction versus the things like
Speaker 2: how can we optimize like the ability of a person
Speaker 2: to learn if they're in an environment that typically isn't
Speaker 2: one where people have access information or for the public
Speaker 2: health use. And that's why, like I think in the end,
Speaker 2: because we always see like like, yeah, this thing could
Speaker 2: be used for good, and it's almost every example is like, yeah,
Speaker 2: and it just made two guys three billion dollars in
Speaker 2: two cents, and that's what happened with that, And now
Speaker 2: we all don't know if videos we see on Instagram
Speaker 2: are real anymore. Thanks.
Speaker 1: Yeah, Yeah, it's not. Yeah, it's not inherently a bad technology.
Speaker 1: It's that the system as is currently constituted, favors scams.
Speaker 1: Like that's why we have a scam artist as like
Speaker 1: our most recent president before this one and probably could
Speaker 1: be future president again, like because that is what our
Speaker 1: current system is designed for, and like it is just
Speaker 1: scamming people for money. That's why when when blockchain technology
Speaker 1: like for has its like infant baby steps, imdiately becomes
Speaker 1: a thing that people use to scam one another, because
Speaker 1: that is the software of our current society. So yeah,
Speaker 1: there are like tons of amazing possibilities with AI. I
Speaker 1: don't think we find them in the United States, like
Speaker 1: applying the AI tools to our current software. I would
Speaker 1: love for there to be a version of the future
Speaker 1: where AI is so smart and efficient that it changes
Speaker 1: that paradigm somehow and change it so that our software
Speaker 1: that our society runs on is no longer scams, you know, right, right.
Speaker 4: I mean there is a future where you know, AI
Speaker 4: starts to do a lot of tasks for us. You know,
Speaker 4: I think that there's starting to be you know, depending
Speaker 4: it's mostly in Europe now, but also here talks about
Speaker 4: like universal basic income. It's it's kind of I don't
Speaker 4: think that that's going to be the case. I don't
Speaker 4: think that in the US anybody has an appetite for that.
Speaker 4: Maybe in twenty thirty years. But you know, I do
Speaker 4: think that, you know, the there are certain things about
Speaker 4: my job right as a professor, about like writing and
Speaker 4: certain other components right where you know, here's some things
Speaker 4: where AI can help, right, And you know, today I
Speaker 4: use it as a tool to make me more efficient,
Speaker 4: Like you know, okay, I want to have an editor
Speaker 4: look at this. Okay, Well, you know it's not going
Speaker 4: to do as good as a real editor, but maybe
Speaker 4: as a cop as a you know, bad copy editor.
Speaker 4: Yeah it's good, you know, Like but you know, I
Speaker 4: mean I've been writing papers for a while. You know,
Speaker 4: when the undergraduates write the paper, it does an even
Speaker 4: better job, right because they have more room for growth, right,
Speaker 4: And so I think the you know, yeah, I think
Speaker 4: that on a micro level, these tools are now being used.
Speaker 4: I think the you know, Russian spambots have been most
Speaker 4: likely using large language model technology before chat GPT, right,
Speaker 4: and so you know, I mean there are some ways
Speaker 4: that I think we're going in a positive and good direction.
Speaker 2: Right.
Speaker 4: Yeah.
Speaker 2: Now it's like now that you say that, I'm thinking,
Speaker 2: I'm like, we thought Cambridge Analytico was bad, and it's
Speaker 2: like what happens now when we like turn it up
Speaker 2: to one thousand with this kind of thing where it's like, yeah,
Speaker 2: here are all these voter files, now, like really figure
Speaker 2: out how to suppress a vote or get to sway people.
Speaker 2: And yeah, I again, it does feel like one of
Speaker 2: these things where in the right hands, right, we can
Speaker 2: create a world where people don't have to toil because
Speaker 2: we're able to automate those things. But then the next
Speaker 2: question becomes, how do we off ramp our culture of
Speaker 2: greed and wealth hoarding and concentrating all of our wealth
Speaker 2: into a way to say, like, well, we actually need
Speaker 2: to spread this out that way everyone can have their
Speaker 2: needs met materially, because our economy kind of runs on
Speaker 2: its own in certain sectors. Obviously, other ones need real
Speaker 2: like human labor and things like that. But yeah, that's
Speaker 2: where you begin to see like, Okay, that's the fork
Speaker 2: in the road. Can we make that? Do we take
Speaker 2: the right path or does it turn into you know,
Speaker 2: just like some very half asked version where like only
Speaker 2: a fraction of the people that need like universal basic
Speaker 2: income are receiving it. Well, you know, we read more
Speaker 2: articles about why we don't see Van Vocht in Hollywood anymore.
Speaker 2: As Jack pointed out that yeah, terribly worded thing about
Speaker 2: Vince Vaughan that AI could not get right, couldn't get right.
Speaker 1: So like Van Vought the one. So the sci fi
Speaker 1: dystopia that seems like not not necessarily dystopia, but the
Speaker 1: sci fi future that seems like it's most close at hand,
Speaker 1: and like given you know, doing a weekend's worth research
Speaker 1: on like where where this is, and like where all
Speaker 1: the top thinkers think we're headed, the thing that make
Speaker 1: that seems the closest reality to me is the movie Her,
Speaker 1: Like Her is kind of already here. There's already these
Speaker 1: applications that use chat GPT and you know GPT four
Speaker 1: two again, Like it really seems to me, like and
Speaker 1: I don't necessarily mean this like in a dismissive way.
Speaker 1: This is probably you know, a good description of most jobs.
Speaker 1: Like that the thing that David Fincher I was like
Speaker 1: listening to a podcast where they talked about how David
Speaker 1: Fincher says, like words are only ever spoken in his
Speaker 1: movies by characters in order to lie, because like that's
Speaker 1: how humans actually use language, is just to like find
Speaker 1: different ways to like lie about who they are, what
Speaker 1: they're you know, approaches to things. And like I think,
Speaker 1: you know, these language models the thing that they're really
Speaker 1: good at, like whether it be like up to this
Speaker 1: point where people are like, holy shit, this thing's alive.
Speaker 1: That's talking to me, Well it's not, And it's like
Speaker 1: just doing a really good approximation of that and like
Speaker 1: kind of fooling you a little bit. Like take that
Speaker 1: to the ultimate extreme and it's like it makes you
Speaker 1: think that you're in a like loving relationship with a partner.
Speaker 1: And like that's already how it's being used in some
Speaker 1: in some instances to great effect. So like that that
Speaker 1: seems to be one way that I could see that
Speaker 1: being becoming more and more a thing where people are like, yeah,
Speaker 1: I don't have like human relationships anymore. I get like
Speaker 1: my emotional needs met by like her technology essentially is
Speaker 1: that what what would you say about that? And what
Speaker 1: is there a different fictional future sure that you see
Speaker 1: close at hand.
Speaker 4: So I think Her is great. I actually, I mean
Speaker 4: it's really funny because you know, I remember back in
Speaker 4: twenty seventeen, twenty eighteen where I was like, oh, her
Speaker 4: is like a great sort of this is where AI
Speaker 4: is going. And you know, for those of you who
Speaker 4: haven't seen the movie, it's a funny movie where you know,
Speaker 4: they have Scarlett Johansson is the voice of an AI
Speaker 4: agent which is on the phone. And I think that
Speaker 4: this is actually a pretty accurate description of what we're
Speaker 4: going to have in the future, not necessarily the relationship part,
Speaker 4: but the fact that we'll all have this personal assistant,
Speaker 4: and the personal assistant we'll see so many aspects of
Speaker 4: our lives right our calendars, our you know, meetings, our
Speaker 4: phone calls, everything, and so it'll be you know, this
Speaker 4: assistant that we all have that's helping us to like
Speaker 4: make things more productive. And as a function of the
Speaker 4: assistant to be effective, the assistant will probably want to
Speaker 4: have some connection with you, and that connection will be
Speaker 4: likely to allow you to trust it. And here's where
Speaker 4: the slippery slope comes from, you know, where you where
Speaker 4: you're like, oh, this understands me, and you start getting
Speaker 4: into a deeper relationship where you know, a lot of
Speaker 4: the fulfillment of a one on one connection can come
Speaker 4: with your smart assistant. And I do think that there's
Speaker 4: a little bit of a danger here. Like you know, again,
Speaker 4: I'm not a psychologist. I'm someone who studies AI machine learning,
Speaker 4: but I do, actually, you know, study how well machines
Speaker 4: can make sense of emotion and empathy. And really, you know,
Speaker 4: GPT four, which is the current state of the art
Speaker 4: technology is actually already really good and understanding. I use
Speaker 4: that phrase with a quote, the phrase understanding, but really
Speaker 4: what you were feeling, right, how you're feeling under this scenario.
Speaker 4: And you can imagine that feeling heard is one of
Speaker 4: the most important parts of relationship, right, And if you're
Speaker 4: not feeling heard by somebody else and you're feeling heard
Speaker 4: by you know, your personal assistant, that could shift relationships
Speaker 4: to to the AI, which you know, could be fundamentally
Speaker 4: dangerous because it's an AI, not a real person.
Speaker 1: Right, Yeah, the one I was talking about is replica
Speaker 1: that app the R E P l I KA. Where
Speaker 1: they are you know, designing these things explicitly to like
Speaker 1: fill in as like a romantic partner and at least
Speaker 1: with some people. And it's always hard to tell, did
Speaker 1: they find like the three people who are using this
Speaker 1: to fill an actual hole in their lives or is
Speaker 1: it actually taking off as a technology. But yeah, the
Speaker 1: personal assistant thing seems closer at hand than maybe people
Speaker 1: realized any other like kind of concrete changes that you
Speaker 1: think are coming to people's lives that they are aren't
Speaker 1: ready for or haven't haven't really thought about or seen
Speaker 1: in another sci fi movie.
Speaker 4: Sci fi movies are remarkably good in predictas.
Speaker 1: Yeah, or maybe they have seen in a sci fi movie.
Speaker 4: No, But I think you know another another thing that
Speaker 4: one potential that I think not enough people are talking
Speaker 4: about is how much better video games are going to become.
Speaker 4: M So people are already integrating GPT four into video games,
Speaker 4: and I think our video games are just going to
Speaker 4: be so much better because you know, you have this
Speaker 4: ability to like interact now with a character AI that's
Speaker 4: not just like very boring and chatting with you, but
Speaker 4: they can actually be truly entertaining and fully interactive.
Speaker 2: Interesting.
Speaker 4: I think you know, computer games are going to be
Speaker 4: much much better and possibly also more addictive as a
Speaker 4: function of being much.
Speaker 2: Better perfect, and then that will dull our appetite for
Speaker 2: revolution when our jobs are all taken by day. Yes,
Speaker 2: this is great, This.
Speaker 1: Is great, all right. I feel much better after having
Speaker 1: had this conversation.
Speaker 2: Dude, Grant that auto is way better the kinds of
Speaker 2: conversations I have with people I would normally bludgeon on
Speaker 2: the street with my character something else.
Speaker 1: Well, doctor said, Doc, such a pleasure having you on
Speaker 1: the dailies. I guess I feel like we could keep
Speaker 1: talking about this for another two hours, but we've got
Speaker 1: to let you go. But thank you so much for
Speaker 1: joining us. We'll have to have you back. Where can
Speaker 1: people find you? Follow you all that good stuff?
Speaker 4: Yeah, thank you for having me. I'm on what is
Speaker 4: now called x at.
Speaker 2: J O aout on this podcast, we still call it Twitter.
Speaker 4: Yeah, okay, well Twitter fine, and you know, yeah, that's
Speaker 4: my that's my currently still my main venue. But yeah,
Speaker 4: and is.
Speaker 1: There a work of media you've been enjoying?
Speaker 4: Good question, Modern dance. So Fall for Dance is starting
Speaker 4: in New York City. So I've been, you know, moving
Speaker 4: into watching some modern dance, which is sorry, kind of
Speaker 4: a fun thing to do modern dance.
Speaker 2: Okay, Okay, here, I'm gonna have bing Chat recommend some
Speaker 2: modern dance show for me in New York.
Speaker 1: So what they say, through work we get access to
Speaker 1: the being chat butt, so pretty cool.
Speaker 2: All I do is mess around. I'm like a child
Speaker 2: with it. I'm like pitch me a movie with Seth
Speaker 2: Rogan where he's a stoner biker. Did a pretty good job.
Speaker 2: Pretty good job. Feels a little derivative, but it makes
Speaker 2: sense because it's only deriving its ideas from existing things
Speaker 2: out there.
Speaker 1: But yeah, I asked to summarize the plot of Moby
Speaker 1: Dick in the formatab wu tang wrap and it was
Speaker 1: not great, not great, well, not great. It was kind
Speaker 1: of saying so like more early eighties rap where it
Speaker 1: was like, hey, my name's Ahab and I'm here to
Speaker 1: say I hit this whale in a major way.
Speaker 4: Miles.
Speaker 1: Where can people find you? What is a work a
Speaker 1: media you've been enjoying?
Speaker 2: Now you really got me thinking.
Speaker 1: Now you've really done it.
Speaker 2: Wow, Jack sorry, I'm asking it to summarize of mice
Speaker 2: and men in the form of a ghost face rap verse.
Speaker 2: You can find me at Miles of Gray on Twitter.
Speaker 2: I don't even for you know formerly x. I'm calling
Speaker 2: it twitterformerlyex dot com. Okay, we're inverting the form here,
Speaker 2: so check me out there pretty much everywhere, Instagram all that,
Speaker 2: and obviously find us on our basketball podcast, Miles and
Speaker 2: Jack Got Mad Boosties, where I promise my takes are
Speaker 2: not written by AI or are they? And also find
Speaker 2: me on my true crime podcast The Good Thief or
Speaker 2: We're in Search of the Greek Robinhood, and also for
Speaker 2: twenty Day Fiance, where I talk about ninety day Fiance.
Speaker 2: Whoa do you know what? You know?
Speaker 4: What?
Speaker 2: You know? They just said when I said, give me
Speaker 2: of mice and men in the form of ghost face. Yo,
Speaker 2: let me tell you about a story so true of
Speaker 2: two migrant workers, George and Lenny, who we're on a
Speaker 2: mission to own their food and land and live off
Speaker 2: the fat of the land. That was the plan. George
Speaker 2: was smallish.
Speaker 1: Come on, you gotta give me like.
Speaker 2: A random Italian dish rather mixed with like gore tex
Speaker 2: or north face. Anyway, it's got it's got some got
Speaker 2: some learning to do. Let's see any tweets or works
Speaker 2: of media I'm liking. Not really, not really the thought
Speaker 2: I thought I had something that I saw recently. Oh,
Speaker 2: new season A Top Boy. I was watching the new
Speaker 2: season A Top Boy on Netflix.
Speaker 1: New Season A Top Boy. Yeah, it's Top Boy a
Speaker 1: show Top Boy.
Speaker 2: No, does sound like it would be like The Best Boy? Yeah, No,
Speaker 2: it's a it's like a London gangster show. Okay, yeah,
Speaker 2: yeah about Roadman in it?
Speaker 1: Roadman?
Speaker 2: Yeah, Roadman.
Speaker 1: I was a highwayman, all right. You can find me
Speaker 1: on Twitter at Jack Underscore O'Brien. Uh. Tweet I enjoyed
Speaker 1: was from Jeff at Used Wigs, tweeted the weekend ending
Speaker 1: Trump of seeing the sixty minute stop Watch as a
Speaker 1: kid lives forever and I feel that and it's not
Speaker 1: just as a kid, not just as a kid.
Speaker 3: Yeah.
Speaker 1: You can find us on Twitter at daily Zeitgeist. We're
Speaker 1: at the Daily Zeikegeist on Instagram. We have a Facebook
Speaker 1: fan page and our website Daily zeikeuist dot com, where
Speaker 1: we post our episodes and our footnote where we link
Speaker 1: off to the information that we talk about in today's episode,
Speaker 1: so as a song that we think you might enjoy.
Speaker 1: Miles with song and we think people might enjoy it.
Speaker 2: Uh. This is from a Thai artist. She's like a drummer, producer,
Speaker 2: dope drummer and named Salne s A L I N.
Speaker 2: I'm sorry if I I botched the pronunciations and I'm
Speaker 2: gonna do it again with the track. It's called see Chompu.
Speaker 2: The first word si the second where c h O
Speaker 2: m p h u and I believe that is a
Speaker 2: region of like northeast Thailand. But she's like this, like
Speaker 2: it's like a really funky drum track if you like
Speaker 2: crumbin and kind of sort of like funky like Southeast
Speaker 2: Asian funk kind of music. This is kind of what
Speaker 2: that track sounds like, except for drumming. She is so
Speaker 2: tight on the kit anyway, So check this one out.
Speaker 2: It's a Salin with see chompoop.
Speaker 4: All right.
Speaker 1: We will link off to that in the footnote. The
Speaker 1: Daily is a production of iHeartRadio Formal podcasts from my
Speaker 1: heart Radio Visits, the iHeartRadio w ap Apple Podcasts wherever
Speaker 1: you listen to your favorite shows that it is good
Speaker 1: to do it for us This morning back this afternoon
Speaker 1: to tell you what is trending and we'll talk to
Speaker 1: you then. Bye bye,