The Daily Zeitgeist - Resist The Urge To Be Impressed By A.I. 02.27.24

Episode Date: February 27, 2024

In episode 1631, Jack and Miles are joined by hosts of Mystery AI Hype Theater 3000, Dr. Emily M. Bender & Dr. Alex Hanna, to discuss… Limited And General Artificial Intelligence, The Distinctio...n Between 'Hallucinating' And Failing At Its Goal, How Widespread The BS Is and more! LISTEN: A Dream Goes On Forever by VegynSee omnystudio.com/listener for privacy information.

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Starting point is 00:00:00 I'm Jess Casavetto, executive producer of the hit Netflix documentary series Dancing for the Devil, the 7M TikTok cult. And I'm Clea Gray, former member of 7M Films and Shekinah Church. And we're the host of the new podcast, Forgive Me for I Have Followed. Together, we'll be diving even deeper into the unbelievable stories behind 7M Films and Shekinah Church. Listen to Forgive Me for I Have Followed on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. I'm Keri Champion, and this is season four of Naked Sports. Up first, I explore the making of a rivalry,
Starting point is 00:00:37 Kaitlyn Clark versus Angel Reese. People are talking about women's basketball just because of one single game. Clark and Reese have changed the way we consume women's basketball. just because of one single game. Clark and Reese have changed the way we consume women's basketball. And on this new season, we'll cover all things sports and culture. Listen to Naked Sports on the Black Effect Podcast Network, iHeartRadio apps, or wherever you get your podcasts.
Starting point is 00:00:56 The Black Effect Podcast Network is sponsored by Diet Coke. I'm Keri Champion, and this is season four of Naked Sports. Up first, I explore the making of a rivalry. Kaitlyn Clark versus Angel Reese. Every great player needs a foil. I know I'll go down in history. People are talking about women's basketball just because of one single game. Clark
Starting point is 00:01:15 and Reese have changed the way we consume women's sports. Listen to the making of a rivalry. Kaitlyn Clark versus Angel Reese on the iHeartRadio app, Apple Podcasts podcast or wherever you get your podcast presented by capital one founding partner of iheart women's sports hello the internet and welcome to season 326 episode 2 of der daily's i guys stay production of iheart radio this is a podcast where we take a deep dive into American shared consciousness. And it is Tuesday, February 27th, 2024.
Starting point is 00:01:48 Oh, yeah. I mean, what is that? That means it's Tuesday. We said 27th? Is that where we are? That's right. 22724. It's Anosmia Awareness Day.
Starting point is 00:02:00 It's National Retro Day. So I guess honor your see-through telephones and vinyl players. National Polar Bear Day. National Strawberry Day. National Kahlua Day. For all my Kahlua lovers out there, the day is yours. The day is yours. The white Russian.
Starting point is 00:02:18 Is Kahlua white Russian or no? That's Bailey's, right? I think so. I don't know. It's just mudslide. Either way, it's just way too much sugar. And you will have a bad time if that's all you drink. So, yeah. That's right.
Starting point is 00:02:30 Well, my name is Jack O'Brien, a.k.a. Don't you wish your snack food were sweet like this? Don't you want more vague dissatisfying bliss? Don't you? Oh, that is courtesy of Clio Universe. ying bliss don't you that is courtesy of cleo universe in reference to the fact that some of the greatest science of the late 20th century was spent focusing on how to get the perfect balance of mouth feel and like enjoyment and dissatisfaction in nacho cheese Doritos. And yeah. Just got to keep on popping them.
Starting point is 00:03:07 Got to make them keep popping. That's who we are as a civilization, unfortunately, at times. And I'm thrilled to be joined, as always, by my co-host, Mr. Miles Gray. Miles Gray, a.k.a. Pastor Warren Bond at Rockhandside. Pastor Warren on the rock hand side. Pastor Warren on the rock hand side. And that is the reference to Senator Elizabeth Warren saying her dream blunt rotation was just to smoke with the rock. And I, my body curled into itself and I became a snail and drifted off into the sea.
Starting point is 00:03:43 Yes, thank you to La Caroni for that one, for letting us know that's where you're going to pass the dutchie, on the rock hand side. On the rock hand side. I wonder what the rock would be like high. I feel like... Oh, dude. Probably pretty fun, right?
Starting point is 00:03:56 Because you know he's like simmering conservative underneath the surface. So not good? It would just be like getting high with Joe Rogue. I feel like it's you know he'd say something weird and then being like he'd probably like make an observation about your physique he's like yeah dude he's like you're right-handed huh yeah i could tell man based on how your shoulders built then you're like okay what is going on please explain it all yeah yeah have some workout tips for you unsolicitedited. Don't need that. Miles, we are thrilled to be joined by the hosts of the Mystery AI Hype Theater 3000 podcast.
Starting point is 00:04:32 It's Dr. Alex Hanna and Professor Emily M. Bender! Hello! Hello! Hello. Welcome. Welcome to both of you. Yeah. In addition to being podcast hosts, the highest honor one can attain in our world.
Starting point is 00:04:48 You both have some pretty impressive credits. So I just want to go through those as well. You are a linguist and professor at the University of Washington, where you are director of the Computational Linguistics Laboratory. Alex, you are director of research at the Distrib Linguistics Laboratory. Alex, you are Director of Research at the Distributed AI Research Institute. You're both widely published. You've both received a number of academic awards. You both have PhDs.
Starting point is 00:05:15 What are you doing on our podcast? Yeah, how? How do you agree? Like, our booker is really good. Shout out to super producer Victor. But this is, I don't know what's going on here. Yeah, we're out of our depth here. We're excited to be here.
Starting point is 00:05:29 And part of what's going on is that, you know, we're talking to the world about how AI, so-called AI, isn't all that. Right. And so a chance to have this conversation is really helpful and important. We've been talking about that for a while, but listening to your podcast really drove some things home. So I'm very excited about this conversation. Yeah. Every time we have, like we've had Dr. Kerry McInerney on before, I think it's been on your show as well. Every time we pick and out in New York, we were just always talking about like our own evolution with how we felt about AI. Because before I was like, it's going to take all the writing
Starting point is 00:06:05 jobs. And then people were like, it's not. I'm like, how do you know? And they're like, here's some more information. I'm like, it's vaporware to make money. So it's always nice to like, yeah, it's always nice to kind of keep, you know, pushing my own understanding along because I also encounter, you know, a lot of friends and family who also kind of have the same thing. They're still at the like, this stuff looks like it's going to change the world forever in a way we'll never know. And yeah, so it's always great to have the input of actual learned experts on the topic. Learned expertise. So we're going to get into all of that. But before we do, we like to get to know our guests a little bit better
Starting point is 00:06:45 by asking you, what is something from your search history that is revealing about who you guys are? I have an exciting one. I can start. Hey, this is Alex. Yeah. So I'm building a chicken coop because my second job, or rather one of my third jobs is kind of being a little suburban farmer. And so I'm getting some chicks delivered from a hatchery. And they said, you need to put this directly into the brooder. And I'm like, what's a brooder? And I had looked up what a brooder is, and then came up and found that it can be anything from a rubber made tub where you put the chickens while they're very small until like a repurposed rabbit hut. So then I started thinking all morning about how to build the chicken brooder. That's my strategy.
Starting point is 00:07:35 And wait, just so it's just like a like it's like a pen, like a mini pen for the to just kind of. Yeah, it's like a little pen for the chicks. And you put in a heat lamp because they need to be warm. They have only got that chicken fuzz. They don't have the chicken feathers. Yeah, yeah. To me, this
Starting point is 00:07:55 sounds like a job for a shoebox. But that's probably... Too small. Unfortunately, that's what they're getting if I'm building a chicken coop. That use what i got if you're in if you're in a if you're in a rush you can use your bathtub if you have one of those and put some puppy pads right i learned a lot about this today as i was just waiting for another meeting to start and just read everything i could nice and of course that chicken coop is going to come in handy
Starting point is 00:08:25 free eggs during the robot apocalypse, right? Which Sam Altman has told me is coming. So I have to assume that's also what you're thinking, right? Right. I mean, she's prepping. She's prepping for the eventual demise. Yeah, I think during COVID, I think there was a run on chicken eggs.
Starting point is 00:08:40 So I'd go to Costco and you couldn't get the gross of chicken eggs. And then I'd go, I'd go, Hey, Hey. And I went to my backyard. Sold them to your neighbors at a market. Got them for eight bucks an egg if you want them. Yeah. They are still really expensive. Emily, how about you? What's something from your search history? So I took a look and it's a bunch of boring stuff. Like I can't remember, I can't be bothered to remember the website of a certain journal that I was interested in. So I'm like searching the name of the journal,
Starting point is 00:09:07 but then like down below that, um, we've been watching, uh, for all mankind, which is this like alternate timeline thing that, that that's a, uh,
Starting point is 00:09:17 what happens if the Soviets landed on the moon first? Right. So it diverges in the 1960s and, but it keeps referencing actual history. So my search history is full of like, OK, so when did the Vietnam War actually end? Right. And like, you know, which Apollo mission did what? So it's a bunch of queries like that sort of comparing what's in the show to actual history. How does that line up based on your sort of cursory research as you watch the show?
Starting point is 00:09:41 So interestingly, so there's there's a point where ted kennedy is like in the background being talked about not going to chappaquiddick oh and then an episode later he's president wow so there's and i suspect there's way more of that kind of stuff that i'm not catching right right right just subtle things right right the media is like and ted kennedy missed a barbecue this weekend in chappaquiddick that's that's super interesting yeah this is you know third or fourth person who's mentioned for all mankind to us i think this is pushing it over the threshold to where i have to i have to watch this damn thing it's enjoyable enjoyable, but it's tense. Yeah. You know, anything where it's like people in outer space really creeps me out
Starting point is 00:10:28 because like that degree of like loneliness and sort of lack of fail-safes. Yeah. You know, like when all the fail-safes are there are the ones that you built and beyond that, you know, your SOL, that's creepy. Seems uncomfortable, outer space.
Starting point is 00:10:43 Yeah. What is something, Alex, that you think is underrated? I was trying to think of something, and the only thing I could come up with this morning was the Nintendo Virtual Boy. The red goggles
Starting point is 00:10:58 on a tripod. The red goggles on a tripod, and I know in whatever, 20 years later, 30 years later, I think at this point, you know but then I was reading the wikipedia page and it kind of said you know it was giving people headaches and it was overpriced and but I'm going to stand by my claim that it is underrated it was ahead of its time and you know it was one of those products that completely, you know, I don't know. I think, you know, if you could go back, maybe it was just maybe I don't know.
Starting point is 00:11:53 I don't know what they could have done differently. But yeah, that's that's all I got. It was cool as hell. Have you seen? OK, so I was the same way. Like I was subscribed to Nintendo Power, all that shit. Totally. I was such a nerdy game kid. And when like those ads for it,
Starting point is 00:12:07 it was like, this is the future. It blew my mind. My parents obviously were like, that's a hell no for a month. Because of how silly you would look. We don't want to deal with or in public with that. Yeah.
Starting point is 00:12:19 It's also like a couple of grand wasn't, it was just ridiculously. It was something I think it was like a few, it was just something like more than like what a playstation cost which was sort of like the height of it or something like anyway i remember a kid in my school had one brought it to school no and we lined up to play it and it was the most underwhelming experience that like it broke me because like there's nothing vr this. It's like lightly 3d everything. I feel like in this like monochromatic, like red scale kind of graphic thing.
Starting point is 00:12:51 It just was really, it was underwhelming, but I, I completely follow the same path you had Alex and being like, this is, I need this. This is the future. Yeah.
Starting point is 00:13:01 Yeah. And yeah, that's so funny. And everyone thought about the vision pro as being like the, the, like the spiritual sequel. Exactly. It's the direct descendant.
Starting point is 00:13:11 Yeah. You know, the Nintendo virtual boy crawled. So the Apple vision could run. Right. How about you, Emily? What is something you think is underrated?
Starting point is 00:13:23 So after listening to a couple of your episodes and like all the nineties nostalgia, I have to say Gen X. Gen X is underrated. Yeah. The people I thought were the coolest. We've got some monsters among us. You know, but you know, Gen X, we're small, we're scrappy. I saw someone, a millennial that I know online posting something about how weird it is to talk to Gen X folks about their internet experiences. And I wrote back, don't cite the old magic to me. I was there when it was created. Although I feel like it's a bit meta, Emily, because I feel like Gen Xers are always going to say that they're underrated, like they're underappreciated. And it's kind of a class feature. It's our whole identity.
Starting point is 00:14:09 Exactly. It is a reference. Yeah, it's a class feature of Gen Xers to say that they are unappreciated. And, you know, you children have to struggle with AOL dial-up. How about this prior no internet? Yeah., you know, how about this, you know, prior, no internet or, I mean, unless you have that. Do you even know how to read a map? No.
Starting point is 00:14:31 I do. As an elder millennial, I do. Yeah. Yeah. I grew up in LA. I know how to use a Thompson guide or a Thomas guide. That's, that was, that was our Google maps before anything. But yeah. Map quest, right?
Starting point is 00:14:42 Yeah, exactly. But yeah, like I think about too like as like an older millennial like gen x were all the people i thought were the coolest people growing up like oh man this is like i want to be i want to be a hacker i want to be like them where's my oh yeah well hey i don't know what are we gonna say about ourselves as millennials i wonder i think we're just like we're just dead inside on some level that we're like, yeah, whatever. Cool. We're dead inside and we killed everything, right? The stock headline, you know, millennials are killing
Starting point is 00:15:15 the napkin industry. But the avocado toast is going to be so good. It's going to be amazing. We killed housing somehow because we spent too much on avocado toast yes and you know you know turmeric lattes or whatever those are good i like they are good though maybe even underrated oh okay there will be two people will be proposing to each other with rings made of turmeric and avocado instead of diamonds because you guys killed the diamond industry. Our new currency, yes. I mean, good riddance, though.
Starting point is 00:15:53 Yeah, but we always talk about that framing. It's just basically millennials can't afford X thing. Right. We can't afford. We're not killing the diamond industry. We don't have money for diamond industry. We don't have money for these other things. Millennials have this weird trend of living five to an apartment
Starting point is 00:16:10 because they love it. Yeah. Alex, what's something you think is overrated? Well, we're on the AI stuff. And so Emily and I are going to talk about parts of it. But image generators, for sure. Text-to-image generators. I mean, people think they're very flashy.
Starting point is 00:16:34 But, I mean, it does a lot of copying. You know, I was giving a talk at a San Francisco public library with Carla Ortiziz who's a um a concept artist and she had all these examples in which you know give it a prompt and it would literally just copy kind of a game art and then put it on the new thing and have some kind of squiggles around it right so the stuff is just i mean and it's also i mean the the kind of images i think it's also, I mean, the kind of images, I think, it's just this distinctive style that aesthetically, apart from all the problems with this stuff and the non-consensual use and the data theft and all the awful kinds of non-consensual deepfake porn and the kind of far-right imagery like the stuff is just ugly like it's got this like every every person and it just looks sunken they look like they've just seen some shit you know they've got some shadows behind like it's a thousand miles there yeah just just glassy and you're just you're just like what is the appeal you know and and so i just yeah i just i don't like it yeah it's not aesthetically
Starting point is 00:17:46 pleasing every so many things when people try and do like real life because i i look at like the mid journey subreddit on reddit to see like what people are making and that was sort of like my intro like wow these are like like when people get the prompts right it's interesting they're like simpsons but real life characters and also but from a korean drama like okay so we're getting the korean like the k drama irl simpsons but all the the aesthetic like all looks like it's like sort of like david la chapelle's photography it's weird there's like this hyper stylized look to it that feels very specific and i think the thing that interests me is sort of like as someone who's terrible at visual art it's like this way for someone with absolutely no talent in that area to be like, I summon this thing I'm thinking of.
Starting point is 00:18:33 And you're like, fine, it's a bunch of copies. But like, I think that's the thing that most people are like, oh, cool. Right. It made the thing. It made the thing. It made mediocre, like, art. I had the thought, AI is like a doesn't matter generator.
Starting point is 00:18:50 Like, Star Trek has the matter generator, and AI just, like, shits out a bunch of stuff that doesn't matter, that's, like, uninspired. But it, like, matters to you for a split second. You know, it's like, oh, wow, that's weird that, like, that just came from a text prompt. But it actually doesn right wow that is that's weird that like that just came from a text prompt but it's it actually doesn't matter in any long-term sense right yeah that's i love that framing i mean what's that famous that i the like image of the like the diner yeah like
Starting point is 00:19:19 night hawks is that what it's called yeah Yeah, yeah, yeah. Yeah, yeah. Yeah, Night Hawks, yeah. Someone had this great- Terrible thread. Well, no, it was a troll thread, though. Do you know what I'm talking about, Emily? There was like the Night Hawks, the image, and then someone was like, I thought it, like, look at this composition. It's so boring.
Starting point is 00:19:38 What if they were happier? And it was kind of like a troll thread. I think it was like- Was it a troll thread? I thought it was genuine. I thought that they were really saying, I'm making it better with AI like a troll thread. I think it was like... I thought it was genuine. I thought they were really saying I'm making it better with AI. I think it was a troll thread.
Starting point is 00:19:50 It's like, why are these people so sad? What if they were happy? What if it was daytime? Yeah, it was sort of like that. Like, you know, and I thought it was a troll thread. Maybe I'm granting posters like a little too much, like gracier. But I think it was a troll thread. Maybe I'm granting posters like a little too much.
Starting point is 00:20:06 But I think it was like the idea of like, I made it interesting. Look at this. Why is it so dark? Yeah. Right. What if there was confetti? Yeah, I know. What if like a swagged out Pope was also sitting in a lightsaber?
Starting point is 00:20:23 Yeah, right. Oh, so much. I don't know if it can lie to any image. also sitting at that time. With a lightsaber. Yeah, right. The Swagdow Pope can lie to any image. The Swagdow Pope did fool me, though. I thought it was real. And then I was like, this is such a cool But again, it's not like ChatGPT was like, you know, it'd be funny.
Starting point is 00:20:40 It was somebody was like, you know, it would be funny and gave that prompt to ChatGPT and then it ended up funny and gave that prompt to chat GPT. And then, you know, it ended up being. But like, that's that's the thing that you guys talk about a lot is just the erasure of like people are like, well, and here's chat GPT doing this thing. And it's like that somebody told it to do and then programmed it to do. Right. It's doing a specific.
Starting point is 00:21:04 It is not a person. Right. Who is coming up with ideas. It's like a specific, it is not a person who is coming up with ideas. It's like talking about Picasso's paintbrush, but just as the paintbrush, like, look what the paintbrush did. Oh my God, dude. Which is kind of cool and zen. There's a little Buddhism there that I appreciate, but I feel like that's not where it's headed, unfortunately. Emily, do you have something that you think is overrated? Yeah. I mean, the short answer is large language models are overrated.
Starting point is 00:21:29 But I think we're going to get into that. We are. Probably. So I'm going to shift to my secondary answer, which is actually to take a page from Alex's work to say that scale is overrepresented. That if the goal of taking something and scaling it to millions of people is like the thing, the only folks really benefiting from that are the capitalists behind it. The product is worse. The impact on the societies or the communities that lost access to whatever their local solution was is worse. So scale is the thing that so many people are chasing, especially in the Bay Area, but also up here in Seattle.
Starting point is 00:22:02 And it's way overrated. I can tell you that All over, in every place. You hear that all the time. How does scale make lines go up? I worked on a website that was having
Starting point is 00:22:18 really fast growth and it was just based on publishing these three articles a day and really focusing on making them as good as possible and unfortunately once it got a lot of attention then the executives came in and their first question was how do we scale this how do we scale this though like how do we get a hundred articles a day and that was like back in 2010 those right now but it's just been how capitalism thinks about this from the beginning. Yeah.
Starting point is 00:22:50 And now they're doing it with movies. They're like, who needs movies now? I could make myself the star of Oppenheimer. It's like, why would you want to do that? Seems like you missed the point of that movie. Okay. I want to be destroyer of world. That'd make me feel strong.
Starting point is 00:23:07 Yeah. Yeah. All right. Well, let's take a quick break and we'll come back and get into it. We'll be right back. I'm Jess Casavetto, executive producer of the hit Netflix documentary series Dancing for the Devil, the 7M TikTok cult. And I'm Clea Gray, former member of 7M Films and Shekinah Church. And we're the host of the new podcast, Forgive Me For I Have Followed.
Starting point is 00:23:34 Together, we'll be diving even deeper into the unbelievable stories behind 7M Films and L.A.-based Shekinah Church, an alleged cult that has impacted members for over two decades. LA-based Shekinah Church, an alleged cult that has impacted members for over two decades. Jessica and I will delve into the hidden truths between high control groups and interview dancers, church members, and others whose lives and careers have been impacted, just like mine. Through powerful, in-depth interviews with former members and new, chilling firsthand accounts, the series will illuminate untold and extremely necessary perspectives. Forgive Me For I Have Followed will be more than an exploration. It's a vital revelation aimed at ensuring these types of abuses never happen again. Listen to Forgive Me For I Have Followed on the iHeartRadio app,
Starting point is 00:24:16 Apple Podcasts, or wherever you get your podcasts. Hey, I'm Gianna Pradente. And I'm Jemay Jackson-Gadsden. We're the hosts of Let's Talk Offline, a new podcast from LinkedIn News and iHeart Podcasts. When you're just starting out in your career, you have a lot of questions, like how do I speak up when I'm feeling overwhelmed? Or can I negotiate a higher salary if this is my first real job?
Starting point is 00:24:40 Girl, yes. Each week, we answer your unfiltered work questions. Think of us as your work besties you can turn to for advice. And if we don't know the answer, we bring in experts who do, like resume specialist Morgan Saner. The only difference between the person who doesn't get the job and the person who gets the job is usually who applies. Yeah, I think a lot about that quote.
Starting point is 00:25:00 What is it, like you miss 100% of the shots you never take? Yeah, rejection is scary, but it's better than you rejecting yourself. Together, we'll share what it really takes to thrive in the early years of your career without sacrificing your sanity or sleep. Listen to Let's Talk Offline on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. I'm Keri Champion, and this is season four of Naked Sports, where we live at the intersection of sports and culture. Up first, I explore the making of a rivalry, Kaitlyn Clark versus Angel Reese. I know I'll go down in history.
Starting point is 00:25:37 People are talking about women's basketball just because of one single game. Every great player needs a foil. I ain't really near them boys. I just come here to play basketball every single day, and that's what I focus on. From college to the pros, Clark and Reese have changed the way we consume women's sports. Angel Reese is a joy to watch. She is unapologetically black.
Starting point is 00:25:56 I love her. What exactly ignited this fire? Why has it been so good for the game? And can the fanfare surrounding these two supernovas be sustained? This game is only going to get better because the talent is getting better. This new season will cover all things sports and culture. Listen to Naked Sports on the Black Effect Podcast Network, iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.
Starting point is 00:26:19 The Black Effect Podcast Network is sponsored by Diet Coke. Effect Podcast Network is sponsored by Diet Coke. And we're back. We're back. And yeah, so as we mentioned, you know, we've done some episodes on AI, how there's a lot of hype around it. Your podcast really helped me understand just how much of the current AI craze is really hype. understand just how much of the current AI craze is really hype. There's this one anecdote I just wanted to mention where a physicist who works for a car company was brought into a meeting
Starting point is 00:26:55 to talk about hydraulic brakes. And one of the executives of the car company asked them if putting some ai in the brakes wouldn't help them operate more smoothly which they're kind of confounded and we're like what what does what do you but like i guess that gets to the big question i have a lot of the time with ai hype in the media which is what do these people think AI is? It's magic fairy dust, but you actually made it slightly more plausible by making it breaks. The story was pistons. Pistons. Okay. And the engineer was like, it's metal.
Starting point is 00:27:35 There's no circuits here. Right. Yeah. But yeah, I mean, there are three kind of big ideas that I got a new perspective on from your show that I wanted to start with. The first one is kind of this distinction between limited and general intelligence or like general AI, which is something that I've heard mentioned a lot in the past couple of years in articles about chat GPT. and articles about chat GPT, they're basically trying to use this as a distinction to say, look, we've known that computers can beat a chess master for a while now,
Starting point is 00:28:12 but the distinction that we are trying to sell to you is that this one is different because it's a general intelligence. It can kind of reason its way into doing lots of things. And one of the details I heard you point out on your show is that it's still pretty limited. Like it's still basically doing a single thing pretty well. Like the chat GPT is. Can you talk about that? What is that distinction and how kind of imaginary it is? Yeah. So before Alice goes off on chess as a thing, and we'll get there, Alex, you're right that chat GPT does one thing well. But the one thing that
Starting point is 00:29:00 is doing well is coming up with plausible sequences of words. Right. The problem is that those plausible sequences of words can be on any topic. So it looks like it is doing well at playing trivia games and being a search engine and writing legal documents and giving medical diagnoses. And the less you know about the stuff you're asking it, the more plausible and authoritative it sounds. But in fact, underlyingly, it's doing just one thing, predicting a plausible sequence of words. Right. Yeah. And the thing about chess is that it wasn't too long ago that general intelligence meant chess playing, you know, and so you had, you had these, you know, during the cold war, they would have these machines that can play chess and then that was supposed to be a substitute for general ai they thought that was general intelligence and it was a big deal when
Starting point is 00:29:50 you know ibm watson beat gary kasparov and you know ibm watson was that deep blue deep blue deep blue sorry yes yes watson watson won jeopardy jeopardy yeah it beat it beat ken jennings and then so yeah thank you it was another one those ibm ones and so then that was the kind of that was that was the bar and then they're like well test is now too easy we have to do we have to do go go you know and then and then they got it into some real-time strategy games like StarCraft and Dota 2. And so there's always been this kind of thing that's been a stand-in for intelligence, and this has been what the advertisement for general intelligence is. And so in addition to what Emily's saying, it's really good at doing this next word thing. I mean, it seems to achieve some acceptable baseline for all these different tasks.
Starting point is 00:30:49 And then these tasks become like stand-ins for general intelligence. And it really gives away the game when people like Mark Zuckerberg come out and they say, well, Meta is going to work on AGI now. I don't really know what that is, but, you know, we're going to do it. But you guys seem to like it as investors. And so therefore, that is what we're going to call our thing now. Yeah, yeah. It's literally turning back towards the machine and like dialing up the AGI knob and seeing if the crowd, you know, seems to tear at it. Yeah. So so i think emily you were saying that just you were specifically saying that they would take an existing sentence like one of the training methods take an existing sentence cover up a word computer guesses what that word is and then
Starting point is 00:31:37 compares guess to what the actual word is and like it got better and better at doing that until it seems like the computer is talking to you using the language a human would use in conversation like just hearing it put that way for some reason was like oh it's so it's like just better it's it's doing the same thing that a chess computer does but it's just more broadly impressive to people who don't know how to play chess so it's uh it's not actually doing the same thing that a chess computer does. So what Deep Blue did was they just threw enough computation at to calculate it out. What are the outcomes of these moves?
Starting point is 00:32:15 What opens up? What opens up? And you put enough calculation in for chess, that's doable with computers of the era of Deep Blue. Go, it turns out the search space is much bigger. computers of the era of Deep Blue. Go, it turns out, the search space is much bigger. So the AlphaGo, what they did was they actually trained it more like a language model
Starting point is 00:32:29 on the sequences of moves in games from really highly rated Go players. Someone beat it recently by playing terribly. And then it was like, I don't know what to do. It was completely out of the training. They're just so crap at it. That's why I usually lose at chess,
Starting point is 00:32:45 because I'm so much better than everybody. It's just their low level confuses me. So there was a big deal about how GPT-4 could play chess super well. And one of the things about most of the models that are out there right now is we know nothing about their training data, or very little.
Starting point is 00:33:00 The companies are closed on the training data, even open AI, right? But people figured out that there's actually an enormous corpus of highly rated chess players, chess games in the training data and the specific notation for GPT-4. So when it's playing chess, it is doing predict a likely next token based on that part of its training data. But that's not what Deep Blue is up to. Deep Blue is a different strategy. And in all of these cases, there's this idea that like, well, chess is something that smart people do. So if a computer can play chess, that means we've built something really smart, which is ridiculous. And I just want to be very clear that Alex and I aren't saying there's some better way to build AGI.
Starting point is 00:33:37 We're saying there's better ways to seek out effective automation in our lives. I'm kind of speaking for you there, Alex, but I think we're in agreement. Yeah, or rather, I mean, even if we want automation in particular parts of our lives, what is the function of making chess robots, right? And insofar as building chess robots in the Cold War, I mean, a lot of it had to do with Cold War kind of scientific ac a lot of it had to do with, you know, Cold War kind of scientific acumen, you know, the US versus the USSR and seeing if we could do better, you know,
Starting point is 00:34:11 and, you know, chess was one front getting to the moon. Speaking of the show, which has already completely evaded me that we were talking about earlier. For all mankind. For all mankind. Thank you. Please cut me out. Make me sound smart. It's a tough title. It doesn't stick in the brain. And they should have used AI to name that show. Yeah, exactly. Yeah. Yeah.
Starting point is 00:34:32 That was the historical sexism that makes it stick. Or maybe makes it a little bit slippery. Right. Yes. Yeah. So it's the same thing. You know, getting to the moon first. So, I mean, this becomes a stand-in, you know, and it's, you know, a lot of it's
Starting point is 00:34:45 frankly kind of show in his own, you know, mine can do it better than yours. And, you know, and really getting to that. And so, you know, this association with chess, as Emily said, of like this thing smart people can seem to do not things like this automation useful in these people's lives, right? Will it make these kind of rut tasks kind of easier for people instead we sort of jumped over that completely to go let's make this art kind of thing and oh it's going to put out a bunch of you know concept artists and writers even if it doesn't work well you know we're going to scare the wits out of these people who do this for a living what's like is there i feel like you know looking at ces and just what happened at ces so many companies like it's got ai like this thing
Starting point is 00:35:33 this refrigerator is using ai and i feel like for most people who are just consumers or just kind of passively getting this information there's like a a discrepancy between how it's being marketed and what it is actually doing. Right. Yeah. And can you and so part of me is like, how the like, why are all these C-suite maniacs suddenly being like, dude, this is the future. Like, you got to get in on it. And I know that a lot of it is hype. But can you sort of like help me understand like the hype line or pipeline to how a company says, oh, this is what we do. And then how that creeps up to the capitalists who are then they're like, yeah, yeah, yeah. What, what, what? And then begin to say, like, make these proclamations about what large language models are doing or how it's going to revolutionize
Starting point is 00:36:19 things. What's sort of like, cause from your perspective, can you just sort of be like, just give us the, the unfiltered, like, this is how this conversation is moving from these laboratories into places like Goldman Sachs? Yeah, I mean, I think a lot of hype seems to operate via FOMO. It's honestly, honestly, if you want it kind of reductive kind of way, you need to get in on this at the ground level. If you don't, you're going to be missing out on huge opportunities, huge returns on investment, right? And one of the ways I would say that AI hype is kind of at least a bit qualitatively different than, let's say, I don't know, crypto or NFTs or,
Starting point is 00:37:04 you know, that's say, I don't know, crypto or NFTs or, you know, distributing, you know, DeFi, is that, you know, crypto has kind of shown itself to be such a, you know, house of cards that, you know, it takes only a few things, like your Sam Bankman free going to jail, or, you know, these huge kinds of scandals happening with with finance and coinbase that you know those things and and it's the wild fluctuation of bitcoin and other
Starting point is 00:37:34 types of crypto that at least you have some kind of proof of concepts on this on this chat gpt where it seems like this thing can do a lot. And so there's enough kind of stability in that where folks say, yeah, let's go ahead and get in on this. And if we don't get it on the ground floor, we're missing out on millions or billions of dollars in ROI. And so, you know, this is, you know, but the hype, I mean, the hype is really at its base, this kind of FOMO element of it. And I think it's just the thing where, you know, it obscures so much of what's going on under the hood. You see Gen AI, people say, we're putting Gen AI in this, Gen AI in that, that you can rub it on an engine.
Starting point is 00:38:39 When AI itself, I mean, itself, that kind of calling things AI, I technologies that have been called AI since the inception of AI in the mid-1950s, it can be anything as basic as a logistic regression, which is a very basic statistical method that gets taught in stats 101 or 201 to these language models that we see OpenAI hawking. And so you could say AI isn't anything. I've got AI. I've programmed by hand. I did the math by hand. Ooh. Right, right. So I think part of what's going on here is that because of the way ChatGPT was set up as a demo
Starting point is 00:39:19 and then all these people did free PR for OpenAI, sort of sharing their screen caps, everybody has this sense that there's a machine that can actually reason right now. And then you call anything else AI and that the, you know, gee whiz factor from chat GPT sort of like makes the whole thing sparkle.
Starting point is 00:39:36 There's a funny story from this conference called NeurIPS, which is Neural Information Processing Systems. Not real neurons. These are the fake ones that these things are built out of. It's like a mathematical function that's sort of an approximation of a 1940s notion of what a neuron is. And a few years back, I want to say like- You sound impressed, by the way. Around 2016, 2017, I think, some folks at NeurIPS did a parody where they put together this pitch
Starting point is 00:40:00 deck of a company that was going to build AGI. And it's ridiculous. Like the pitch deck is basically step three, dot, dot, dot, step three profit. Like there's nothing in there. And this was just on the cusp of when AI went from being sort of a joke, like you wouldn't call your work AI if you were serious to where we are now. And what these people didn't realize when they were doing their pitch deck was that there were some folks in the audience who had already stepped over into that like you know ai true believer we're gonna make a lot of money on this step people came up and offered them money for their fake company that's great yeah so it's it's like the dot-com boom yeah there's just like what's the company called some dot-com yeah yeah They're ready for the next thing, right?
Starting point is 00:40:45 They've kind of stalled out post-iPhone, and they're ready for the next big thing, whether it's here or not. And so, yeah, the GWIZification or the GWIZ results from OpenAI and ChatGPT, I feel like they were like, good enough. Let's get this thing going. Let's get this machine cranking out. The idea of describing like the mistakes that ChatGPT makes as hallucinations, like the marketing that's being done across the board here is pretty impressive. The fact that ChatGPT even uses the word Right. That's a programming choice that could have been otherwise and would have made things much, much clearer.
Starting point is 00:41:29 Right. Yeah. Chad GPT is trained on the entire Internet. Not true. Yeah, that was something that I had accepted when it first started. I'm like, well, this thing hallucinates and its brain is the entire Internet. What could go wrong? So the thing about the phrase the entire internet is that the internet is not a thing where you can go somewhere and download.
Starting point is 00:41:50 Right. It is distributed. And so if you are going to collect information from the internet, you have to decide which URLs you're going to visit. And they aren't all listed in one place. Right. There's no way to say the entire internet. There's some choices happening already. Yeah.
Starting point is 00:42:04 no way to say the entire internet there's there's some choices happening already yeah and what they mean when they say the entire internet i mean most of the time they mean most of the english available internet and i mean and although they've got some but then much of the work that has been translated has been actually machine translated from from from english into another language so for instance you know a bunch of the urls that they have are from the uh google japanese patents and common crawl and the dodge paper yeah they a lot of it's been machine translated from english into japanese and it's just available through like google's japanese patent site and so a bunch of this stuff is you know just just loaded in and it's and so yeah and so i mentioned this data set common crawl which isn't you know in the gpt2 paper i think they cite it or is the gpt3 paper it's i think it's a gpt3 paper and they said yeah it's the common crawl is this data set that they say
Starting point is 00:42:58 they use which is this kind of what's this weird like non-profit i was collecting a bunch of data that could be useful for some limited scientific inquiry? But then it became, now they've completely rebranded themselves. They're saying, we have the data that, you know, fuels large language models. And Mozilla, the Mozilla Foundation, folks that also, the corporation makes the web browser Firefox, they did this report on Common Crawl
Starting point is 00:43:24 and kind of what's behind it too, and find the weird idiosyncrasies of it. But yeah, when they say the whole internet, I mean, yeah, it's these curated data sets. You can't get this whole internet. That's just a falsity. But for our listeners, you can get it from Jack and I. We do have that file.
Starting point is 00:43:42 Yeah, it's just one large zip file. Yeah. It's just going to. On your BitTorrent. Yeah, exactly. Yeah. Yeah. It's on Pirate Bay.
Starting point is 00:43:51 Check it out. Yeah. Yeah. And we read it every morning to prepare for this show. Just the whole thing. Just download it. Yeah. Let's take a quick break and we'll be right back.
Starting point is 00:44:02 Let's take a quick break and we'll be right back. I'm Jess Casavetto, executive producer of the hit Netflix documentary series, Dancing for the Devil, the 7M TikTok cult. And I'm Clea Gray, former member of 7M Films and Shekinah Church. And we're the host of the new podcast, Forgive Me For I Have Followed. Together, we'll be diving even deeper into the unbelievable stories behind 7M Films and LA-based Shekinah Church, an alleged cult that has impacted members for over two decades. Jessica and I will delve into the hidden truths between high control groups and interview dancers, church members, and others whose lives and careers have been impacted, just like mine. Through powerful, in-depth interviews with
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Starting point is 00:46:00 Without sacrificing your sanity or sleep. Listen to Let's Talk Offline on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. I'm Keri Champion, and this is season four of Naked Sports, where we live at the intersection of sports and culture. Up first, I explore the making of a rivalry, Kaitlyn Clark versus Angel Reese. I know I'll go down in history, people are talking about women's basketball
Starting point is 00:46:27 just because of one single game. Every great player needs a foil. I ain't really near them boys, I just come here to play basketball every single day and that's what I focus on. From college to the pros, Clark and Reese have changed the way we consume women's sports. Angel Reese is a joy to watch. She is unapologetically black. I love her. What exactly ignited this fire? Why has it been so good for the game?
Starting point is 00:46:50 And can the fanfare surrounding these two supernovas be sustained? This game is only going to get better because the talent is getting better. This new season will cover all things sports and culture. Listen to Naked Sports on the Black Effect Podcast Network, iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. And we're back. So, yeah, just in terms of juxtaposing, like what these companies are saying and the mainstream media is buying versus what is actually happening so i was reminded of sam altman telling the new yorker that he keeps like a bag with cyanide capsules ready to go in case of the ai apocalypse so you know he is an expert who gets billions of dollars richer if people think
Starting point is 00:47:47 his technology is so powerful that he's like freaked out by it so but that that's something that i i don't know i've seen reprinted and like long articles about the danger of ai and then there's this other like more realworld trend where you talk about a Google engineer who admitted they're not going to use any large language model as part of their family's healthcare journey. Oh, that was a Google senior vice president. Very high up, actually. Not a senior vice president. A Google VP, Greg Corrado, who's one of the heads of Google Health itself.
Starting point is 00:48:33 Oh, okay. Yeah, and there's also this story from, your show has a Fresh Health segment at the end where you talk about just saying examples, headlines that are just... Just fresh health. Yeah, it's just fresh health. It's new versions of health. The fresh AI health. Yeah.
Starting point is 00:48:50 The one about Duolingo from a recent episode where they're getting rid of human translators, firing them, cutting the workforce, replacing them with translation AI, even though the technology isn't there yet. But the point that you were making on the show is that they're willing to go forward with that because the user base won't notice the difference until they're in Spain and need to get to a hospital and asking for the biblioteca.
Starting point is 00:49:22 You know, like it's, they are specifically an audience who is not going to know how bad the product that they're getting is because they're just like not in a in a position to to know that by by the nature of the product and so just this distinction between being hyped to the mainstream media and like these long read like new yorker atlantic articles as this is a future that we should be scared of because like it's going to become self-aware and sam altman is freaked out and then what it's actually doing which is just making everything shittier around us is i think a big kind of chunk that I took away from your show that was just like, oh, yeah, that makes way more sense. That feels much more likely to be
Starting point is 00:50:13 how this thing progresses. Yeah. So the AI doomerism, which is when Altman says, I've got my bug out bag and my cyanide capsules in case the robot apocalypse comes or when jeff hinton um who's you know credited um has has a turing award for his work on the specific kind of computer program that's used to gather the statistics that's behind these large language models he's now concerned that it's on track to becoming smarter than us and it's gonna like these piles of linear algebra are not going to combust into consciousness. And anytime someone is like, you know, pointing to that boogeyman,
Starting point is 00:50:48 what they're doing is they're basically hiding the actions of the people in the picture who are using it to do things like make a shitty language learning project. Because it's cheaper to do it that way than to pay the people with the actual expertise to do the translations. Right. Yeah. Yeah. And it's just leading just to, I mean, I like this kind of thought on this, I mean, this kind of process. And Corey Doctor has
Starting point is 00:51:10 got this kind of sister concept of AI hype, which is enshitification, which I think the Linguistic Society of America, it was their overall... Yeah, American Dialect Society. Dialect Society, yeah. Picked it as the overall word of the
Starting point is 00:51:26 year for 2023. But it's gentrification of something very specific, right? It's not just like we're now swimming in AI-extruded junk, right? AI in quotes, as always. It's something more. The companies create a platform that you sort of get lured in because initially
Starting point is 00:51:41 it's really useful. You think about how Amazon was great for finding products. It sucked for your local brick-and-mortar businesses, but as a consumer it was super convenient because you could find things. But then the companies basically turn around and they extract all of the value that the customer is getting out of it, and then they turn around to the other parties there, the people trying to sell things, and they extract value out of them.
Starting point is 00:52:05 So you start off with this thing that's initially quite useful and usable, and then it gets enchinified in the name of making profits for the platform. And that's like the specific thing about enchinification. And I would say there's some kinds of processes. You can think about enchinification, the kind of idea that you have to rush to a certain kind of market that you have a monopoly on this kind of thing and i guess yeah i mean the thing about large language models i think that we get we get on and talk a lot about is that large language models are kind of born shitty with content so it's not like the platform started and that platform monopoly led to this kind of process of instantification it's more like you decided to
Starting point is 00:52:45 make a tool that is a really good word prediction machine, and you use it for a substitute for places in which people are meant to be speaking kind of with their own tone, with their own voice, with their own forms and their own expertise. And then, and so it's kind of, yeah, it's, it's born shitty. And so, you know, this so this kind of thing, I think, is really helpful. It makes me think of kind of a thing I think I saw a few times on Twitter where people are like, well, if you're an expert in any of these fields and you read content by large language models, you actually know anything about this. thing about this, you're going to know that it's absolute bullshit, right? You know, if you ask it to write you a short, you know, treatise on, I don't know, sociological methodology, something specific that I know a little bit about, it's going to be absolute bullshit, right? But good enough to computer engineers and, you know, higher ups at these companies. Yeah. So here's an example.
Starting point is 00:53:46 The other day I came across an article that supposedly quoted me out of this publication from India called Bihar Prabha. And I'm like, I never said those words. I could see how someone might think I would. And I searched my emails like, no, I never corresponded with any journalists at this outfit. So I wrote to them. I said, a fabricated quote, please take it down in print or retraction, which they did.
Starting point is 00:54:06 And they wrote back and said, oh, yeah, that actually we prompted some large language model to create that article for us and posted it. Yes, because it seems like you might have. And the large language models, they don't like that. That's isn't that what hallucinations are a lot of the time is just the large language model making up stuff. It seems like is what the person wants them to say. Exactly. But here's the whole thing. Every single thing output from a large language model
Starting point is 00:54:31 has that property. It's just that sometimes it seems to make sense. The whole thing is trying to do a trick of like, predict, I figured out what you wanted me to say. Ha ha. But it's like, well, but what I wanted you to say is not always, that's not how I want my questions answered. That's actually a wildly flawed way of coming up, like answering people. It's definitely something that I do in my day-to-day life because I'm scared of conflict and a people pleaser, but that's not, I'm not, I'm not a good scientific instrument for that reason. You know, like, but you just got a, you just an avoidant attachment style, which as an, as another avoidance, they've just made me a scientific model. That's terrible.
Starting point is 00:55:19 I can't believe this. I was like, I don't know if you saw that uh headline where tyler perry was like i was gonna open an 800 million dollar studio but i stopped the second i saw what sora this video generative ai could do and i realized we're in trouble he said quote i had no idea until i saw recently the demonstrations of what it's able to do. It's shocking to me. And he's basically saying, he's like, you could make a pilot and save millions of dollars. This is going to have all kinds of ramifications. That feels like quite, that feels like half like just ignorance because this person's like, Oh my God, like total wow factor, but also maybe hype. But I'm also curious from your perspective, what, what are the actual dangers that we're facing?
Starting point is 00:56:07 Because right now, I think everything is just all about these are the jobs it's going to take. I think in the LLM episode where the LLM predicted what the potential of LLMs were and the jobs that it could take in a very... The GPT's paper was so ridiculous. Yeah, where it's like, huh? You know, like just sort of the unethical nature of how even these companies are doing research and creating data to support this.
Starting point is 00:56:32 Can we just stop, Miles? Can you just stop and like explain exactly what the methodology of that paper was? No, please. I will allow the experts to do it because it's absolutely bonkers to hear because any person who's like been at any, like tried to look at a study or something and you look at methodology, like, um, so methodology is a very kind term for what was in that paper. Truly, truly. So Alex, did you want to summarize real quick what was in there was two different things we were looking at. There was something that came out of OpenAI and something from Goldman Sachs and the Goldman Sachs one was silly, but not as silly as the OpenAI one. Yeah.
Starting point is 00:57:09 I mean, getting in the deep, and I went through this and I puzzled this paper. I like poked my friend who's a labor sociologist. I'm like, what the hell is going on here? And, you know, okay. So there's this kind of metric that you can use to judge how hard a task is that the government collects. And there's this kind of job classification. They rate them from, you know, one to seven effectively. And so what Goldman Sachs said was, well, basically anything from one to four, probably a machine can do.
Starting point is 00:57:37 And you're like, okay, that's kind of silly. That's huge assumptions there. I understand, though, as a researcher, you have to make some assumptions when you don't have great data. But what OpenAI did is that they asked two entities what could be automated. They asked one, other OpenAI employees, hey, what jobs do you think could be automated?
Starting point is 00:58:01 Already hilarious, because they're pretty inclined. They're not doing those jobs. you know they're they're you know pretty they're not doing those jobs right yeah they're not doing those jobs they're pretty primed to think that their technology is great and then they asked dpt4 itself they prompted and say hey can we automate these jobs so you know and so you'll never guess what the answer was you'll never guess you'll never guess they took the output of that as if it were data yeah and then like you know these ridiculous graphs and blah blah and it's just like the whole thing is is is fantasy right so yeah well so is the danger there just sort of this reliance
Starting point is 00:58:36 like i guess so if we're classifying the sort of threats to our sense of like how information is distributed or what is real or what is hype or whatever, or if they're, they're actually taking jobs. What, what is something that I think people, that people actually need to be aware of or to sort of prepare themselves for how this is going to disrupt things in a way that, you know, isn't necessarily the end of the world, but definitely changing things for the, for the worse. There's a whole bunch of things. And the one that I'm sort of most going on about these days is threats to the information ecosystem. So I want to talk about that. But there's also things like automated decision systems being used by governments to decide who gets social benefits
Starting point is 00:59:14 and who gets them yanked, right? Things like Dr. Joy Bullen-Winney worked with a group of people in, I want to say, New York City who were pushing back against having a face recognition system installed as their like entry system. So they were going to be continuously surveilled because the company who owned the house that they lived in, or maybe it was, I'm not sure if it was government housing or not. Apartment complex. Yeah. Yeah. Wanted to basically use biometrics as a way to have them gain entry to their own homes, right, where they lived. So there's dangers of lots and lots of different kinds. The one that's maybe closest
Starting point is 00:59:51 to what we've been talking about, though, is these dangers to the information ecosystem, where you now have the synthetic media like that news article I was talking about before being posted as if it were real, without any watermarks, without anything that either a person can look at and say, I know that's fake. Like I knew because it was my name and I knew I didn't say that thing. Right. But somebody else wouldn't have. And there's also not a machine readable watermarking in there. So you can just filter it out.
Starting point is 01:00:14 And this stuff goes and goes. So there was, oh, a few months ago, someone posted a fake mushroom foraging guide that they had created using a large language model to Amazon as a self-published book. So then it's just up there as a book. And coming back around to Sora, those videos, they look impressive at first glance, but then just like Alex was saying about the art having this sort of facile style to it, there's similar things going on in the videos. But still, it should be watermarked. It should be obvious that you're looking at something fake. And what OpenAI has done is they've put this tiny little faint thing down the lower right-hand corner that looks like some sort of readout from a sensor going up and down.
Starting point is 01:00:54 And then it swirls into the OpenAI logo and it's faint. And it's in the same spot that Twitter puts the button for turning the sound on and off. So it's hidden by that if you're seeing these things on Twitter. And it's completely opaque, right? off. So it's hidden by that if you're seeing these things on Twitter. And it's completely opaque, right? If you are not in the know, if you don't know what OpenAI is, if you don't know that fake videos might exist, that doesn't tell you anything. Right.
Starting point is 01:01:15 So these are the things I'm worried about. And the things I'm really worried about is, you know, these things doing a pretty terrible job at producing written content and videos and and and images and so it's not that they could replace a human person but it just takes a boss or a vp to think that it's good enough right and then this replaces whole classes of of occupation so again, talking to Carla Ortiz, who's a concept artist, she's done work for Marvel and DC and huge studios and Magic the Gathering.
Starting point is 01:01:52 And she's basically saying, after Midjourney Stability AI produces this incredibly crappy content, jobs for concept artists have really dried up. They've gone and it's really hard. And I mean, jobs for concept artists have really dried up. They've gone and it's really hard. And I mean, especially for folks who are just breaking into the industry, who might just be trying to get their work out there for entry-level jobs, they can't find anything right now.
Starting point is 01:02:18 And so imagine what that's going to replace, what that's going to encroach on, right? I mean, that's kind of unique thing about kind of creative fields and coding fields and whatnot. And then I would say this, yeah, this automated decision making kind of in government and hiring, I mean, those are, you know, definitely, you know, terrifying, right? And then, I mean, this is already being deployed. I mean, at the US-Mexico border, there's kind of massive... The Mark have actually just put out this interview with David Moss
Starting point is 01:02:48 who's at the Electronic Freedom Foundation. No, either the Electronic Freedom Foundation, I think it's at the ACLU. I have to look this up. But it's basically a survey of surveillance technology that's at the southern border. And Dave Moss is at EFF, the Markdown,
Starting point is 01:03:04 but just published something with something about with him it was like a virtual reality tour of certain technology or something wild like that i was going to say there's also things like shot spotter which reports to be able to detect when a gun has been fired and this has been deployed by police departments all over the country and there's you know there's no transparency into how it was evaluated or how it even works or why you should believe it works and so what we have is a system that tells the cops that they are running into an active shooter situation, which is definitely a recipe for reducing police violence. Right? Yeah.
Starting point is 01:03:35 Right. Powered by Microsoft. Yeah. And there is a recent investigation that showed that it's almost always used in neighborhoods. Yeah, communities of color. Yeah, the wired piece on that, basically. Yeah, I think they said about, what, 70% of the census tracts? Something ridiculous like that.
Starting point is 01:03:56 Yeah, it's absurd. And then there's things like Epic, which is a electronic health records company, is partnering with Microsoft to push this synthetic text into so many different systems so that you're going to get like reports in your patient records that were automatically generated and supposedly checked by a doctor who doesn't have time to check it thoroughly. Right. And they're going to be doing things like, you know,
Starting point is 01:04:20 randomly putting in information about BMI when it's not even relevant or misgendering people over the place or, you know, this kind of stuff is going to hurt. Yeah. And I wanted to add to the issue of like entry-level jobs drying up for people who do, for example, illustration, Dr. Joy Bolanwini points out that we're getting what's called an apprentice gap, where those positions where the easy stuff gets automated. And I don't think this is just in creative fields, but the positions where you're doing the easy stuff and you're learning how to master it and you are working alongside someone who's doing the harder stuff. If that gets replaced by automation, then it becomes harder to train the people to do the stuff that requires expertise. in creative fields because there's such a just inability for executives to you know like they they don't know it they've never known anything about like what what is quality creative work so i feel like it's much easier for them to just be like yeah get rid of that and yeah like the way
Starting point is 01:05:16 that we'll find out about that that isn't working is the quality of the creative output will be far worse right i mean what i mean all those folks really tend to care about are content and engagement metrics. You can't actually have something that's kind of known for quality or creativity, right? It does remind me a little bit about kind of, you know, the first rebels against automation, the Luddites, and the kind of way in which they did have this apprentice guild system in which they trained for a decade or so before they could perhaps go ahead and open their own shop in a way that those folks were replaced by these water frames that were, they're called water frames because they were produced by hydraulic power,
Starting point is 01:06:05 but then, you know, effectively powered by unskilled people and by unskilled, usually children. Yeah. Doing incredibly dangerous work. But yeah, folks that have been training for this,
Starting point is 01:06:19 the apprentices were incredibly steaming mad. Yeah. And then we made their name a synonym for like dummy. Being a hater. Hater. Yeah. Tech hater. Not Canadian in the coal mine. But there's been some nice efforts to reclaim them by Brian Merchant and Kevin Mueller and some folks.
Starting point is 01:06:37 So just in the comparison to crypto, it feels like the adoption here, the hype cycle here is more widespread than crypto like with crypto there was that moment where we saw the person behind the curtain who was you know the people that there was the fall of crypto with with ai i don't feel like there is any incentive for anyone to any of the stakeholders i guess you got us involved to yeah to just come out and be like yeah it was bullshit you know there's just so much buy-in across the board where i i guess we've already talked about where you see this going but is there do you think there's any hope for this getting kind of found out, the truth catching on? Or do you think it's just going to have to be 100 years from now when somebody changes their mind about AI haters and is like, actually, they were on something the way we are about Luddites. We're still trying. That's what we're up to with the podcast, right?
Starting point is 01:07:48 A lot of our other public scholarship. There was an interesting moment last week when ChatGPT sort of glitched and was outputting nonsense. Oh, speaking Spanglish? Yes. I mean, was it actually Spanglish or were people just calling it that because it had some Spanish in it? It had some. It was doing some Spanglish
Starting point is 01:08:04 stuff, but the stuff is just even more inscrutable than usual. It was just completely nonsense. Yeah. Yeah. And that, the sort of open AI statement about what went wrong, basically described it for what it is. They had to like say something
Starting point is 01:08:19 other than what they usually say. And then there was a whole thing with Google's image generator, which, you know, the, so the baseline thing is super duper biased and like makes everybody look like white people. And, and there's this wonderful thread on medium and here I'm doing anything where I can't think of a person's name, but it's a wonderful post on medium where someone goes through this thread of pictures that I think were initially on Reddit, where someone asked one of these generators to create warriors from different cultures taking a selfie and they're all doing the
Starting point is 01:08:49 American selfie smile. And so there's this really uncanny valley thing going on there where these people from all these different cultures are posing the way Americans pose. So huge bias in these things underlyingly. Google has some kind of a patch that basically whatever prompt you put in, they add some additional prompting to make the people look diverse and then last week or so someone figured out that if you asked it to to show you a painting of nazi soldiers they're not all white because of this patch right right right so make it diverse yeah so google's backpedaling of that i I think, was ridiculous. There was some statement in there about how they certainly don't intend for their system to put out historically inaccurate images. I'm like, what the hell?
Starting point is 01:09:33 It's a fake image. It's not like there's no accuracy there no matter what. But these mishaps maybe sort of pulled back the curtain for a broader group of people. There's some true believers out there who are not going to be reached. But I think it may have helped for some slice of society. Yeah. I know some people who are like, how do we know that Reinhard Heydrich didn't have dreadlocks?
Starting point is 01:09:55 I think it's pretty clear. But okay, sure. Go off. Yeah. And I mean, I think this is such an interesting question, right? It's like, when is the AI bubble going to pop, right? And I mean, in some ways, it feels like, as much as we can do, we're kind of prodding it, right?
Starting point is 01:10:14 And one thing that I offhandedly said one time and Emily loves is ridicule as praxis. So one thing, and I will in a turn, one of Emily's great quotes is, oh gosh, now I'm going to mess it up right now. It's the refuse to be impressed. Oh yeah, resist the urge to be impressed. Resist the urge to be impressed. It's much better when she says it. And it's kind of the idea of like, some of it is a bit of the sheen, right? But it feels like at some point,
Starting point is 01:10:53 if in the kind of operations of these things, there'll be enough buy-in, especially with automation, that's hard to reverse a lot of the automation without just a huge fight. And so, I mean, I think something that helps are, you know, worker led efforts, you know, and one of the most awesome things that we've seen, this is something, um, uh, a scholar, uh, Blair, uh, tear frost calls AI counter-governance. She calls, uh, she calls uh and in one example she is is the wga strike and how folks struck for 148 days and after the strike they not only got a bunch of new kinds of guarantees for minimum pay when it
Starting point is 01:11:38 comes to streaming and the residuals they get for it they also you also have to basically be informed if any AI is being used in the writer's room. They can't be forced to edit or re-edit or rewrite AI-generated content. Everything has to be basically above board. I mean, it isn't as far as
Starting point is 01:11:59 it could have gone and banned it outright. But if there's any use of it, it has to be disclosed and you can't bring in these tools to whole cloth replace a writer's room. Yeah. Well, Alex and Emily, it has been such a pleasure having you on the show.
Starting point is 01:12:15 I feel like we could keep talking about this for hours, for days. But thank you so much for coming on. And yeah, I would love to have you back. Where can people find you, follow you, hear your podcast, all that good stuff? Yeah. So the podcast is called Mystery AI Hype Theater 3000, and you can find it anywhere. Find podcasts are streamed. And we're also on PeerTube if you prefer that kind of content as video. So we start off as Twitch and then show up that way. I'm on all the socials. I tend to be Emily M. Bender. So Twitter, Blue Sky on Mastodon. I'm Emily M. Bender at, what are we, DARE Institute about social. And I'm very findable on the web, very Google-able at the University of Washington. How about you, Alex? want to check catch the twitch stream it's twitch.tv slash dare underscore institute usually
Starting point is 01:13:05 on mondays usually this time slot so next week we'll be here uh wait are we i forget we'll be here eventually yeah today's two today's tuesday though in tbz land oh that's right that's right yeah it's actually not so mondays check us out you can can catch me at Twitter and Blue Sky, Alex Hanna, no H at the end. And then yeah, our Mastodon server, dare-community.social. What else? I think those are all the socials we have. Yeah. Amazing. Is there a work of media that you've been enjoying? So I am super excited about Dr. Joy Boulamouni's book, Unmasking AI. It came out last Halloween. It is a beautiful sort of combination memoir slash introduction into the world of how so-called AI works, how policymaking is done around it, how activism is done around it.
Starting point is 01:14:00 And I actually got to interview her here in Seattle at the University of Washington last week, which was amazing. Nice. How about you, Alex? Yeah, I'd recommend the podcast Worlds Beyond Number. And it is a Dungeons and Dragons live play, actual play podcast that is put together by Brenna Lee Mulligan, Abrea Iyengar, Lee Wilson, and Erica Ishii talking about writing that is not generated by AI, but generated by some very talented improv comedians
Starting point is 01:14:36 and storytellers themselves. But how does it scale? How do you scale? Oh my God. It is actually surprising. I mean, that podcast is actually, I think the single most funded thing on Patreon for a bunch of records for about 40,000 subscribers.
Starting point is 01:14:54 People want good content. Yeah. Not just high art, you know, people want this vibrant storytelling, amazing creation, you know, and so the more we can, we can plug that stuff better. By the way, People want this vibrant storytelling, amazing creation, you know?
Starting point is 01:15:08 And so the more we can plug that stuff, the better. By the way, you can also find Mystery AI Hype Theater 3000, like where podcasts are. So in case you don't do Twitch. Yeah. Like I was listening on Spotify or whatever. You weren't on Twitch? I wasn't on Twitch this weekend. I was taking it. I was taking a break,
Starting point is 01:15:26 you know, it was just like too much, too much Twitch. Couldn't get a hype train on? That's right. Okay. All right. Miles,
Starting point is 01:15:33 where can people find you? What's working media you've been enjoying? Uh, the at base platforms at miles of gray. Also, if you like the NBA, you can hear Jack and I just go on and on about that on our other podcast. Miles and Jack got mad. And if you like trash reality TV, like me me, I like I comfort myself with it.
Starting point is 01:15:49 Check me out on 420 Day Fiance where we talk about 90 Day Fiance. A tweet I like. This is just kind of a historical day, I would have to say, for the Internet. We missed an anniversary on Sunday, apparently. The very famous clip of Peter Weber, the bowler, who won and came out with the iconic phrase, Who do you think you are? I am. That had its 12th anniversary. And I'll play that audio because it's one of our favorites.
Starting point is 01:16:20 Here we go. That is why I said it. That's number five. Are you kidding me? That's right. Who do you think you are? I am. All right.
Starting point is 01:16:31 Who do you think you are? Point to himself with a stump. Who do you think you are? Oh, man. The whole thing is good also. The run up to that is great. That's right. I did it.
Starting point is 01:16:41 I did it. God damn it. What? Sure, man. I did it. I did it. God damn it. What? Sure, man. I love it. Yeah, I play an amateur sport, and just like the exhilaration you get, and you just say anything. Yeah, exactly. I know.
Starting point is 01:16:56 That's what it is. I love that clip. I respect it so much. I think you are. It's like, yeah, you've glory fried your brain circuits, and now that's what you're saying. And this other one from AtTheDarkProwler. It's a screenshot of an Uber notification on the phone. It says, young stroker, the body snatcher, will be joining you along your route.
Starting point is 01:17:15 You're still on schedule to arrive by 7.54 or earlier. Okay. By the way, can I get those chicken nuggets glory fried? Thanks. That'd be great. Oh, yeah. Oh, a tweet I've been enjoying. Caitlin at Kate Holes tweeted,
Starting point is 01:17:35 Overnight oats sounds like the name of a racehorse who sucks. That was an old one. That was apparently September 25th, 2022. Good one. Banger. You can find me on Twitter at Jack underscore O'Brien. You can find us on Twitter at Daily Zeitgeist. We're at The Daily Zeitgeist on Instagram.
Starting point is 01:17:56 We have a Facebook fan page and a website, DailyZeitgeist.com, where we post our episodes and our footnotes. We link off to the information that we talked about in today's episode, as well as a song that we think you might enjoy. Miles, is there a song that you think people might enjoy? This is a nice little instrumental clip, not clip, a full-on track, from a London-based producer who goes by Vegan, V-E-G-Y-N, and the track is called A Dream Goes On Forever. And it's a super dreamy track.
Starting point is 01:18:26 It's just kind of an interesting production. So maybe, you know, maybe, you know, just check out some mid journey, you know, images,
Starting point is 01:18:33 some Sora AI videos, and just blast this in your headphones. Just kind of go on for a dream goes on forever. Or just go for the music and leave the synthetic media out of it. Just fully embrace. Listen to the music, close your eyes. And actually the mid journey images that your brain will produce whoa i've found that like at night
Starting point is 01:18:52 when i sleep sometimes my brain produces sora images this is like you sound like you sound like a youth pastor talking to kids about god or it's like you know where it's really the ai is actually up in here kids yeah. Yeah. Down here. You really want to get down with. Yeah. Yeah. Yeah. The real training data we had is the word of God.
Starting point is 01:19:12 Exactly. Exactly. The only one I need. Well, the Daily Zeitgeist is a production of iHeartRadio. For more podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts, or wherever you listen to your favorite shows. That is going to do it for us this morning. We are back this afternoon to tell you what is trending. we'll talk to you all then bye bye i'm jess casavetto executive producer of the hit netflix documentary series dancing for the devil the 7m tiktok cult and i'm
Starting point is 01:19:40 cleo gray former member of 7m films and sheah Church. And we're the host of the new podcast, Forgive Me For I Have Followed. Together, we'll be diving even deeper into the unbelievable stories behind 7M Films and Shekinah Church. Listen to Forgive Me For I Have Followed on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. I'm Keri Champion, and this is season four of Naked Sports. Up first, I explore the making of a rivalry, Caitlin Clark versus Angel Reese. Every great player needs a foil. I know I'll go down in history. People are talking about women's basketball just because of one single game.
Starting point is 01:20:18 Clark and Reese have changed the way we consume women's sports. Listen to the making of a rivalry, Caitlin Clark versus Angel Reese on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. Presented by Capital One, founding partner of iHeart Women's Sports. I'm Keri Champion, and this is season four of Naked Sports. Up first, I explore the making of a rivalry,
Starting point is 01:20:40 Kaitlyn Clark versus Angel Reese. People are talking about women's basketball just because of one single game. Clark and Reese have changed the way we consume women's basketball. And on this new season, we'll cover all things sports and culture. Listen to Naked Sports on the Black Effect Podcast Network, iHeartRadio apps, or wherever you get your podcasts. The Black Effect Podcast Network is sponsored by Diet Coke.

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