Ryan Reynolds (2:44)

Foreign.

Ed Zitron (2:49)

Hello and welcome to Better Offline. I'm your host, Ed Zitron. In early June, three researchers from the University of Glasgow published a paper in the Ethics of Information and technology journal called ChatGPT is bullshit. And I just want to be clear. This is a great and thoroughly researched and well argued paper. This is not silly at all. It's actually great academia. And today I'm joined by the men who wrote it, academics Michael Townsend Hicks, James Humphries and Joe Slater, to talk about ChatGPT's mediocrity and how it's not really built to represent the world at all. So for the sake of argument, could you define bullshit for me?

Joe Slater (3:40)

So you are bullshitting if you are speaking without caring about the truth of what you say. So normally, if I'm telling you stuff about the world, in a good case I'll be telling you something that's true and like trying to tell you something that's true. If I'm lying to you, I'll be knowingly telling you something that's false or something I think is false. I'm bullshitting, I just don't care. I'm trying to get you to believe me. I don't really care about whether what I say is true. I might not have any particular view on whether it's true or not.

Ed Zitron (4:11)

Right. And you define between like soft and hard bullshit. Can you also get into that as well? Can you also identify yourselves as well?

Joe Slater (4:20)

Sorry, yeah. I'm Joe. So the soft bullshit, hard bullshit distinctions are very serious and technical distinction.

Ed Zitron (4:26)

Right.

Joe Slater (4:28)

So we came up with this because bullshit is in the technical, philosophical sense, comes from Harry Frankfurt, recently deceased, but really great philosopher, and he talks about the amount of bullshit that there is in popular culture and just in general discourse these days. Some of the ways he talks about bullshit seem to suggest that it needs to be accompanied by a sort of malign intention.

Ed Zitron (4:54)

Right.

Joe Slater (4:54)

I'm doing something kind of bad. I'm intending to mislead you about the enterprise of what I'm doing.

Ryan Reynolds (5:01)

Yeah, maybe about who you are or what you know. So you might be trying to portray yourself as someone who is knowledgeable about a particular subject. Maybe you're a student who showed up to class without doing the work. Maybe you're trying to portray yourself as someone who's virtuous in ways you're not. Maybe you're a politician who wants to seem like you care about your constituents, but actually you don't. So you're not trying to mislead somebody about what you're saying, the content of your utterance. You're trying to mislead them instead about, like, why you're saying it. That's what we call hard bullshit. And it's one of the things Frankfurt talked about.

Joe Slater (5:40)

Yeah. So Frankfurt doesn't make this hard bullshit, soft bullshit distinction, but we do, because sometimes it seems like Frankfurt has this particular kind of intention in mind, but sometimes he's just a bit looser with it. And we want to say that ChatGPT and other large language models, they don't really have this intention to deceive because they're not people. They don't have these intentions. They're not trying to mess with us in that kind of way, but they do lack this kind of caring about truth.

James Humphries (6:07)

Well, I'm James, by the way. I suppose we strictly don't want to say that they aren't hard bullshitters. And we just think if you don't think that large language models are sapient, if you don't think they're kind of minds in any important way, then they're not hard bullshitters. So I think in the paper, we don't. We don't take a position on whether or not they are. We just say if they are, this is the way in which they are. But minimally, they're soft bullshitters. So the kind of soft bullshit, as Joe says, doesn't require that speakers attempting to deceive the audience about the nature of the enterprise. Hard bullshit does. So if it turns out that large language models are sapient, which they're definitely not, like, that's just tech broker up.

Ed Zitron (6:42)

Yeah, that's nonsense.

James Humphries (6:44)

Yeah, but if they are, then they're hard bullshitters and minimally they're soft bullshitters or they're bullshit machines.

Ed Zitron (6:51)

So you also make the distinction in there, the intention. So the very fabric of hard bullshit that you intentionally are bullshitting to someone, you kind of make this distinction that the intention of the designer and the involved prompting could make this hard bullshit. Because with a lot of these models and someone recently jailbroke chatgpt, and it listed all of the things it's prompted to do. Could prompting be considered intentional that Sam Altman, CEO of OpenAI, could be intentionally bullshitting? I think he is, yeah.

James Humphries (7:23)

This again, I think it's something. I don't know what the kind of hive mind consensus on this is. I'm sort of sympathetic to the idea that if you take this kind of purposive or teleological attitude towards what an intention is, is an effort to do something, then maybe they do have intentions. But again, I think in the paper we just wanted. I mean, it's a standard philosophical move, right, to sort of go, look, here's all this uncontroversial stuff as we can make it now. We can hit you with the really controversial shit that we wanted to get to. So in the paper we sort of deliberately went, maybe you might think it has intentions for this reason. We kind of have no judgment on this officially. I'm sympathetic for the sort of view that you're putting. I think you're kind of sympathetic this as well, right?

Ryan Reynolds (8:02)

Yeah, yeah. So I'm Mike. There are a few ways that you can think of ChatGPT as having intentions, I think, and we talk about a few of them. One is by thinking of the designers who created it as kind of imbuing it with intention. So they created it for a purpose and to do a particular task. And that task is to make people think that it's a normal sounding person. Right. It's to make people, when they have a conversation with it, not be able to distinguish between what it's outputting and what a normal human would say. Right?

Ed Zitron (8:34)

Right.

Ryan Reynolds (8:34)

And that kind of goal, if it amounts to an intention, is the kind of intention we think a bullshitter has. Right. It's not trying to deceive you about anything. It's saying. It doesn't care whether what it's saying is true. That's not part of the goal. What the goal is to do is to make it seem as if it's something that it's not. Like specifically a human interlocutor. And one source for that goal is the programmers who designed it. Another is the training method. So it was trained by being given sort of positive and negative feedback in order to achieve a specific thing. And that specific thing is just sounding normal. And that's so similar to what our students are doing when they try to pretend that they read something they haven't.

Ed Zitron (9:20)

Read There is something very collegiate about the way it bullshits though. It reminds me of when I was in college. I went to Penn State and Aberystwyth, two very different institutions.

Ryan Reynolds (9:32)

Both kind of in the middle of nowhere.

Ed Zitron (9:34)

Yeah, Both very sad. But the one thing you saw with like students who were doing like B homework is they were using words they didn't really understand. They were putting things together in a way that really was like the intro body conclusion. There was a certain formula behind it and it's just, it feels exactly like it. But that kind of brings me to my next question, which is how did you decide to write this? What inspired this?

James Humphries (9:57)

Right. I wouldn't feel this because whenever Mike tells the story, you get sanitized version. We were in the pub whinging about student essays.

Ed Zitron (10:04)

Perfect.

James Humphries (10:04)

Yeah, like you were not long here, right? You were not long here.

Ryan Reynolds (10:07)

I just started.

James Humphries (10:08)

Yeah, not long in post. A whole bunch of us went to the pub on a notional let's welcome our new members of staff sort of event and inevitably within about two pints we were all pissing and moaning. Perfect. I think it might have been Neil that kind of prompted us.

Ryan Reynolds (10:21)

No, I don't think he was there, you know.

James Humphries (10:22)

Okay, fair enough.

Ryan Reynolds (10:23)

We talked to him about it.

James Humphries (10:24)

We talked about it after. Right. In any case, like sort of came up. We were talking about this sort of prevalence of ChatGPT generated so stuff and what it said about how at least some students were kind of approaching the assessments and I forget who. Someone sort of just went offhandedly. Yeah, but it's all just frank fertian bullshit though, isn't it? And we sort of collectively went oh hello. Because obviously all having a background in philosophy, we've all read on bullshit, we all went hehehe. We get to say bullshit in allegedly serious academic work. So the start of it was we'd had this experience of having to read all of this kind of uncanny Valley stuff and when prompted we all went, oh, it really is like Frankfurtian bullshit in a way that we can probably get a paper out of.

Ryan Reynolds (11:02)

Yeah. And at that point I think we were in the department meetings talking about how to deal with chatgpt written papers. And there were discussions going on all over the university, including kind of in high levels in the administration to come up with a policy. And we specifically wanted a stronger policy because our university is very interested in cutting edge technology. Right. And so they wanted the students to have an experience using and figuring out how to use whatever the freshest technology is. Right. As they should as they should. Right.

Ed Zitron (11:36)

But not for essays.

Ryan Reynolds (11:38)

Right. That's the worry we had. We thought, you know, if we're not very clear about this, the students will be using it in a way that will detract from their educational experience. Right. And at the same time, it was becoming more widely known how these machines work, like specifically how they're doing next token or next word prediction in order to come up with a digestible string of text. And when you know that that's how they're doing it, I mean, it seems so similar to what humans do when they have no idea what they're talking about. And so when we were talking about it, it just seemed like an obvious paper that someone was going to write. And we thought that had better be us. You know, eventually people are going to see this connection.

Ed Zitron (12:22)

And it's a great paper.

Ryan Reynolds (12:25)

I think it worked very well. I mean, I think that it's the kind of thing where when I pitch this to other philosophers, it doesn't take them very long to just agree to be like, ah, yes, that's right.

Ed Zitron (12:36)

It's an interesting philosophical concept as well, because the way that people look at ChatGPT in large language models is very much machine do this. But when you think about it, there are other ways where people are giving it consciousness. I just saw a tweet just now with someone talk about saying please with every request. It's like, no, I will abuse the computer in whatever manner I see fit. But it's. It's curious because I think more people need to be having conversations like this. And one particular thing I like that you said that. I actually would love you to go into more detail is you said that CHAT GPT in large language models, they're not designed to represent the world at all. They're not lying or misrepresenting. They're not designed to do that. What do you mean by that?

Ryan Reynolds (13:16)

I mean kind of his background. I do philosophy of science. But my thoughts about something like ChatGPT are largely inspired by the fact that I also teach a class called Understanding Philosophy Through Science Fiction.

Ed Zitron (13:28)

Oh.

Ryan Reynolds (13:29)

And in that we like talk about whether computers could be conscious. And I don't know what you guys think. Actually, I think they could. Right. I just don't think this one is. And part of the reason I think they could, but this one isn't is that I think that in order to sort of represent the world or have the kinds of things we have that are like beliefs, desires, thoughts that are about external things, you have to have internal states that are connected in some way to the external world, Usually causation. We're perceiving things. Information is coming in this. Then we've got some kind of stain in our brain that's designed just to track these things in the external world. Right. That's a huge part of our cognitive lives, is just tracking external world things. And it's a very important part of childhood development when you figure out how to track things.

Ed Zitron (14:23)

It's semiotics.

Ryan Reynolds (14:24)

Right.

Ed Zitron (14:25)

Daniel Chandler Aberystwyth taught me semiotics. It's like a perception of the world.

Ryan Reynolds (14:29)

This is like theory of meaning stuff. So, yeah, semiotics is like theory of signs. How is it that a sign.

James Humphries (14:35)

A sign can be both the representation of the thing and the thing itself?

Ryan Reynolds (14:39)

That can happen. Yeah. But not always. Sometimes it's just the representation of the thing. And there's a lot of philosophy is about figuring out how brain states or words on a page can be about external world things. And a big part of it, at least from my perspective, has to do with tracking those things, keeping tabs on them, changing as a result of seeing differences in the external world. And ChatGPT is not doing any of that. Right. That's not what it's designed to do. It's taking in a lot of data once and then using that to respond to text. But it's not remembering individuals tracking things in the world in any way, perceiving things in the world. It's just forming a sort of statistical model of what people say. And that's kind of so divorced from what most thinking beings do.

Ed Zitron (15:37)

It's divorced from experience.

Ryan Reynolds (15:39)

Yeah. I mean, as far as I can tell, it doesn't have anything like experience.

James Humphries (15:42)

Yeah. And that's one of the things that this, I think sort of in one way comes down to, is that if you sort of push this sufficiently far, someone is going to go, ah, isn't this just bio chauvinism?

Ryan Reynolds (15:51)

Right.

James Humphries (15:51)

Like, aren't you just assuming that unless something runs on like meet, it can't be sentient? And this isn't something we get into in the paper, partly because we didn't really think it was worth addressing, but the sorts of things that seem like they're like never mind consciousness, Right. But that seem to be necessary in order for something to be trying to track the world or in order to be corresponding the world or to form beliefs about the world, ChatGPT just doesn't seem to meet any of them. If it does turn out that it's sapient, then ChatGPT has got some profoundly serious executive function disorders.

Ryan Reynolds (16:23)

Right.

James Humphries (16:23)

Of course it's not sapien. Right. So we don't have to worry about it, but kind of it's not the case that we've got some blundering proto general intelligence that's trying to figure out how to represent the world. It's not trying to represent the world at all. Its utterances are designed to look as if it's trying to represent the world. And then we just go, that's just bullshit. This is a classic case of bullshit.

Ryan Reynolds (16:41)

Yeah.

Ed Zitron (16:41)

It seems to be making stuff up, but making stuff up doesn't even seem to describe it. It's just throwing shit at a wall very accurately, but. But not accurately enough.

James Humphries (16:49)

It's got various guidelines that allow it to throw shit at the wall with a sort of reasonably high degree of action. No, you're right. I mean, one of the things that a human bullshitter could at least be characterized as doing is they'd have to try and kind of judge their audience. They'd have to try and make the bullshit plausible to the audience that they're speaking to. And ChatGPT can't do that. Right. All it can do is go on a statistically large enough model and it looks like Z follows Y follows X. It's not kind of got any. Well, it doesn't have any consciousness at all, of course, but it doesn't have any sensitivity to the sorts of things that people are in fact likely to find plausible. It just does a kind of brute number crunch. So it's more complicated than that, But I think it boils down effectively to kind of number crunching.

Ryan Reynolds (17:29)

Right.

James Humphries (17:29)

Kind of data and contexts in which probabilistic planning of.

Ed Zitron (17:33)

Well, planning. It doesn't plan. That's the thing. It's interesting. There are these words you use to describe things that when you think about it, are not accurate. You can't say it plans or thinks.

Ryan Reynolds (17:43)

I think one thing between when we came up with the idea and when we finished writing the paper, we spent some time reading about how it works and how it represents language and what the statistical model is like. And I was maybe more impressed than James about that because it is like doing things that are similar to what we do when we understand language. It does seem to kind of locate words in a meaning space. Right, right. And connect them to other words and, you know, show similarity and meaning. And it also does seem to be able to in some way understand context. But we don't know how similar that is for a variety of reasons, but mostly because it's too big of a system and we can only kind of probe it. And it's trained indirectly. Right. So it's not programmed by individuals. And even though that's kind of a very impressive model of language and meaning and may in some ways be similar to what we do when we understand language, we're doing a lot more things like planning things, like tracking things in the world, just having desires and representing the way you want the world to be and thereby generating goals. Doesn't seem to be something that it has anything, any room for in its architecture.

James Humphries (19:05)

This is something. It's just good to me. You were talking about the kind of. In some ways, it learns language the same way that we do. I mean, it's got no grasp of expletive and fixation. Right. This is one of Chomsky's.

Ed Zitron (19:14)

What does that mean? Just for. Not for me. I definitely know.

James Humphries (19:17)

Yeah. You know, of course, if I give you the sentence that's completely crazy, man, and tell you to put the word fucking into that sentence, there's a number of ways in which any language speaker is going to do it that they'll just go, yeah, of course. That where it goes. Right, right. But it seems that we've got to grasp on this incredibly early on in a way that doesn't look like it's the way at least most of us are taught language.

Ryan Reynolds (19:40)

Right.

James Humphries (19:40)

We get quite harshly told off when we try and do expletive in fixation.

Ryan Reynolds (19:43)

Yes.

James Humphries (19:44)

So this, I think, would be one of those cases where you could do a sort of disanalogy by cases. Right. You present chatgpt a sentence and say, insert the word fucking correctly in this sentence. And I don't think it would be very good at it.

Ryan Reynolds (19:56)

I think it would be.

James Humphries (19:57)

You reckon? I mean, we probably could test it. We could, but we shouldn't be making it easier.

Ryan Reynolds (20:02)

Yeah. One of the things that I thought was, like, kind of interesting about how it works is that it does learn language probably differently from the way we do, but it does it all by examples. So it's looking at all these pieces of text and thinking, ah, this is okay. That's okay. And one kind of interesting thing about how humans understand language is that we're able to kind of understand meaningless but grammatical sentences. It's not clear to me that ChatGPT would understand those. That's another Chomsky example. So, you know, Chomsky has this example that's like, what is it? The green?

James Humphries (20:38)

Colorless Greenwizzles sleep furiously.

Ryan Reynolds (20:40)

It's colorless green ideas, I think so curiously. Right. And that's a meaningless sentence, but it's grammatically well formed. And we can understand that it's grammatically well formed, but also that it's meaningless because ChatGPT kind of combines different aspects of what philosophers of language, logicians, linguistics people see as like different components of meaning. It sees these as all kind of wrapped up in the same thing. It puts them in the same big model. I'm not sure it could differentiate between ungrammaticality and meaninglessness.

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Michael Townsend Hicks (22:50)

Hello, I'm John Lithgow.

Ryan Reynolds (22:52)

We choose to go to the moon.

Michael Townsend Hicks (22:54)

I want to tell you about my new fiction podcast.

Ryan Reynolds (22:57)

That's One Small Step for Man.

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Ryan Reynolds (23:03)

You're a great pilot, Buzz. As far as I'm concerned, the best I've seen.

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Ryan Reynolds (23:13)

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Ryan Reynolds (23:19)

What do you Say, Buzz, another beer.

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Ryan Reynolds (23:22)

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Ryan Reynolds (23:28)

Buzz and I will proceed into the.

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Ryan Reynolds (23:41)

Can you put it through?

Michael Townsend Hicks (23:43)

Can you Translate on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts?

Ryan Reynolds (23:49)

Columbia. A foot washed up. A shoe with some bones in it. They had no idea who it was. Most everything was burned up pretty good from the fire that not a whole lot was salvageable.

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Ryan Reynolds (24:23)

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Ed Zitron (24:55)

So we're doing real time science right now. I just.

Ryan Reynolds (24:57)

Yeah, yeah, we should check it.

Ed Zitron (24:58)

The word into the following sentence in the correct way. Man, that's crazy. And I did it six times. And I would say 50% of the time it got it right. And it did. Man, that's crazy. Man, that's crazy. Man, that's crazy. Man, that's crazy. My favorite is man, comma, that's crazy, comma, fucking.

James Humphries (25:19)

To be fair, I think you're right.

Ryan Reynolds (25:21)

Very unreliable.

James Humphries (25:22)

You take the commas out of that last one and you've got a grammatical sentence.

Ed Zitron (25:25)

Yeah.

James Humphries (25:26)

Of course, in Glasgow, you can also start with fucking. Man, that's crazy. Yeah.

Ed Zitron (25:30)

West London as well. But the thing is, though, it doesn't know what correct means there.

Ryan Reynolds (25:34)

Yeah. No.

Ed Zitron (25:35)

When it's trained on this language, when it's trained on thousands of Internet posts it stole. It's not like it reads them and says, oh, I get this. Like, I see what they're going for. It just learns structures by looking, which is kind of how we learn language. But it kind of reminds me of like when I was a kid and I'd hear someone Say something funny, I'd repeat it. And my dad, who's wonderful, would just say, that doesn't make any sense. And he'd have to explain, because if you're learning everything through copying, you're not learning, you're just memorizing.

James Humphries (26:06)

Yeah, yeah, yeah, exactly.

Ryan Reynolds (26:07)

There's a. I don't know if you have already talked to somebody about this, but there's a classic argument from Chomsky against behaviorism, right? Behaviorism is the view that we learn everything through stimulus and response. Roughly. That's not exactly it, but I'm not a philosopher of mine, so I can get away with that. So Chomsky says, look, we don't get enough stimulus to learn language as quickly as we do just through watching other people's behavior and copying it. We have to have some inbuilt grammatical structures that language is latching onto. And there have been some papers arguing that ChatGPT shows Chomsky was wrong because it doesn't have the inbuilt grammatical structure. But one interesting thing is it requires 10 to 100 times more data than a human child does when learning language. Language. Right. So Chomsky's argument was we don't get enough stimulus. And ChatGPT can kind of do it without the structure, but it's not quite doing it as well. And it gets like orders of magnitude more input than a human does before a human learns language, which is kind of interesting.

James Humphries (27:20)

And it still can't do something as basic as putting the word fuck in.

Ryan Reynolds (27:23)

Right? It still can't do that.

Ed Zitron (27:25)

Yeah, it doesn't even see. And it doesn't have the knowledge to, say, request more context because it doesn't perceive content. And that's kind of the interesting thing. So there was another paper out of Oxford, I think was talking about cognition and chatgpt and all this thing. And it's just. It doesn't fe. ChatGPT features in no way any of the things that the human mind is really involved in. It seems it's mostly just not even memorization because it doesn't memorize. It's just guessing based on a very large pile of stuff. But this actually does lead me to my other question, which is, you don't like the term hallucination? Why is that?

Joe Slater (28:01)

Hallucination makes it sound a bit like I'm usually doing something. Right? I'm looking around seeing the world as something like what it really is. And then one little bit of the feature for a visual hallucination, one feature of my visual field actually isn't represented in the real world, it's not actually there. Everything else might.

Ryan Reynolds (28:23)

Well, my well be right.

Joe Slater (28:24)

Imagine I hallucinate. There's a red balloon in front of me. I still see Mike, I still see James, I still see the laptop. One bit is wrong, everything else is right. And I'm doing the same thing that I'm usually doing. Like my eyes are still working pretty much normally. I think this is the way I usually get knowledge about the world. This is a pretty reliable process for me. I'm learning from it.

Ryan Reynolds (28:50)

Right.

Joe Slater (28:50)

And representing the world in this way. So when we talk about hallucinations, this suggests that ChatGPT and other similar things, they're going through this process that is usually quite good at representing the world. And then, oh, it's made a mistake this one time. But actually, no, it's bullshitting the whole time. And sometimes it gets things right by bullshitting, just like a politician. Imagine a politician that bullshits all the time. If you could possibly imagine it, sometimes they might just get some things true and we should still call them bullshitting. Yeah, because that's what they're doing. And this is what ChatGPT is doing every time it produces an output. So this is why we think bullshit is a better way of thinking about this, or one of the reasons why we think bullshit is a better way.

Ryan Reynolds (29:40)

Of thinking about it. I also kind of think that some of the ways we talk about ChatGPT, even when it makes mistakes, lend themselves to overhyping its ability or overestimating its abilities. And talking about it as hallucinating is one of these. Because when you say that it's hallucinating, as Joe pointed out, you're giving the idea that it's representing the world in some way and then telling you what the content.

Ed Zitron (30:06)

And it has perception.

James Humphries (30:07)

Yeah, exactly. Like it has perceived something and like, oh, no, it's taken some computer acid and now it's hallucination. Hallucinating, like imaginary things. And. Yeah, just as you say, and that's.

Ryan Reynolds (30:17)

Not what it's doing. And so when the kind of people who are trying to promote these things as products talk about the AI hallucination problem, they're kind of selling a product that is a product that's representing the world, usually checking things and occasionally makes mistakes. And if the mistakes were, like Joe said, were a misfiring of a normally reliable process, or, you know, something that normally represents going wrong in some way that would lend itself to certain solutions to them and it would make you think there's an underlying reliable product Here. Right. Which is exactly what somebody who's making a product to go on the market will want you to think. Right. But if that's not what it's doing, in a certain sense they're misrepresenting what it's doing even when it gets things right. And that's, that's bad for all of us who are going to be using these systems. Especially since people, you know, most people don't know how this works. They're just understanding the product as it's described to them using these kind of metaphors. So the way the metaphor describes it is going to really influence how they think about it and how they use it.

James Humphries (31:29)

Yeah. Just to sort of cap that off, if I can, this one of the responses to Some Corners has been to say of us, look, you whinge about people anthropomorphizing ChatGPT, but look, if you call it a bullshitter, you're doing exactly the same thing. And I mean, there might be some extent to which it's just really hard not to anthropomorphize it. I don't know why I picked a word that I can barely say. Like, we've been doing it constantly throughout this discussion, right. When we were talking through the, kind of, through the paper, we kept talking about ChatGPT as if it had intention, right? As if it was thinking about anything that might be another reason to call it bullshit. We go, look, if we have to treat it as if it's doing something like what we do, it's not hallucinating, it's not lying, it's not confabulating, it's bullshitting. If we have to treat it as if it's behaving in some kind of human like way, here's the appropriate human like behavior to describe it.

Ed Zitron (32:14)

I also think the language in this case, and one of the reasons they probably really like the large language model concept, is language gives life to things. When we describe the processes through which we interact with the world and interact with living beings, even cats, dogs, even we anthropomorize living things. But also when we communicate with something, language is life. And so it probably works out really fucking well for them. Sam Altman was saying a couple of weeks back, maybe a month or two, he was saying, oh yeah, AI is not a creature. It was something he said. And it was just so obvious what he wanted people to do was say, but what if it was? Or are people saying, this is a creature? And it almost feels like just part of the conversation?

Ryan Reynolds (32:55)

Yeah, yeah, yeah, it fully is. I hadn't thought about that as a reason for them to go for large language models, as a way of kind of, I don't know, being the gateway into more investment consciousness. Yeah, yeah. But I had thought about, like, how this might have been caused by just, like, deep misunderstandings of the Turing Test.

Ed Zitron (33:19)

Right.

Ryan Reynolds (33:20)

Go ahead.

Ed Zitron (33:20)

No, I want to hear this one.

Ryan Reynolds (33:22)

Yeah, yeah. So that, like, the Turing Test, I think this is closer to what Turing was thinking. But the Turing Test is a way of getting evidence that something is conscious. Right. So you, you know, I'm not in your head, so I can't feel your feelings or think your thoughts directly. Right. I have to judge whether you're conscious based on how you interact with me. And the way I do it is by listening to what you say. Right. And talking to you. And Turing sort of was asked, you know, how would you know if a computer was conscious? So, you know, we think that our brains are doing something similar to what computers do. That's a reason to think that maybe computers eventually could have thoughts like ours. Right. And some of us think that. I think it's possible.

James Humphries (34:09)

I think it's possible.

Ryan Reynolds (34:09)

Great. Yeah. I didn't know if they thought it was possible, because not everybody thinks it's possible.

Ed Zitron (34:13)

It's possible. I just don't know how.

Ryan Reynolds (34:16)

Yeah, exactly. So Turing was kind of thinking, like, how would we know? And one way we would know, the obvious way, is to do the same thing you do to humans. Talk to it and see how it responds. And that's actually pretty good evidence if you don't have the ability to look deeper. But it's not constitutive of being conscious. It's not what makes something conscious or determines whether they're conscious or in any way, like, grounds their consciousness. Right. Their ability to talk to you is just evidence. It's just one signal you can get, and that's the way to think of the Turing Test. So as a result of people thinking in a kind of behaviorist way, thinking, ah, passing the Turing Test is just all it is to be a thinking thing. There have been, at least since the 90s, attempts to design chatbots that can beat the Turing Test. Right. And popularizations of these attempts and run throughs of the Turing Test that talk as if, oh, if a computer finally beats the Turing Test, I should say what the Turing Test is. Right.

Ed Zitron (35:18)

Yeah.

Ryan Reynolds (35:18)

The way Turing suggests that the test works is you have a computer and a person both chatting in some way with a judge, and the judge is also a person.

Ed Zitron (35:28)

Right.

Ryan Reynolds (35:28)

And if the judge can't tell which of the people he's chatting with is a human, then the computer's one, because it's indistinguishable from a human. Right? So people have taken this, and it's been popularized as a way of determining sort of full stop, whether something's conscious. But it's just a piece of evidence, and we have a lot more evidence, like we know a lot more than Turing did, about how the internal functioning of a mind works functionally, what it's doing, how representation works, how experience and belief works, how they are connected to action and how they're connected to. To speech and thought. And once you know all that stuff, you have a lot of other avenues to get more evidence about whether the thing is conscious and whether it passes the Turing Test is just like a drop in the bucket compared to these, especially if you know how its internal functioning is.

James Humphries (36:19)

The other notorious problem with the Turing Test, and I think, to be fair, Turing did mention this, if not in the original, then kind of later on. One problem with the Turing Test is that it's like the Voigt Kampf in Duandroi's Generator of Electric Sheep. Right? Plenty of humans would fail the Turing Test. Yeah, yeah, it is a piece of evidence, but it was never, as Mike says, it wasn't supposed to be constitutive. It wasn't like, if you can do this thing, your conscious kind of full stops. It was supposed to be, here is the thing that might indicate the being you're talking to is conscious. Happily, as Mike says, we've got loads and loads of other evidence.

Ryan Reynolds (36:52)

So these guys have made a machine that's just designed to do one thing, and that's pass the Turing Test.

Ed Zitron (36:58)

I can give you one more annoying example. Are you familiar with Francois Chollet, the Abstraction and Reasoning Corpus? So this is going to make you laugh. So he's a Google engineer and he created this thing called the arc, the Abstraction Reasoning Corpus, to test whether a machine was intelligent and someone created a model that could be it. And then he immediately went, okay, you can't just train the model on the answers to the test.

James Humphries (37:23)

This is why people. Well, I say people. A fairly small subset of weird nerds. But this is why a small subset of weird nerds have been for the last 20 odd years, emphasizing artificial general intelligence. Right. What we'll call it when something really is a thinking being is when it's not specialized to do one and only one task, but rather when it's capable of applying reasoning to Multiple kinds of different and disanalogious cases. On the one hand it does seem a little bit like the guy flipping the table and going, oh, for fuck's sake, now you've won, I'm changing the rules. But on the other, I think he's got a point. Right? Yeah. If you're, if you're training a thing to do very specific, you know, like activate certain shibboleths, then unless you're some kind of mad hard behaviorist, then yeah, like it's not. That doesn't demonstrate intelligence. It is one thing that might indicate intelligence.

Ed Zitron (38:09)

It's the same problem with ChatGPT. It's built to resemble intelligence and resemble consciousness and resemble these things, but it's isn't. It's almost like it's meaningless. On a very high end philosophical level, I find the whole generative AI thing deeply nihilistic.

Ryan Reynolds (38:25)

I mean, one thing that connects to this is how bad it is at reasoning. And this is kind of good for us, especially in philosophy because our students, when they use it to write papers, the papers have to have arguments. And ChatGPT is very bad at reason doing reasoning. If it has to be sort of an extended argument or a proof or something like that, it's very bad at it. I think also that if there's one thing kind of we learned from ChatGPT, it's that this is not the way to get to artificial general intelligence.

Ed Zitron (38:59)

I was going to ask, do you think that this is getting to that?

Ryan Reynolds (39:02)

No. Partially because it's so subject specific. Right. It's one, it's trained to do one task and it takes quite a lot of training to get it to do that task. Well, it's bad at many of the other tasks that we think are connected with intelligence. It's bad at logical and mathematical reasoning. I understand that OpenAI is trying to fix that. Some. Sometimes it sounds like they want to fix it by just connecting it to a database or a program that can do that for it. But either way, what you have with these kind of big Bayes nets models is something that is really good at whatever you train it to do, but not going to be good at anything else. You know, it's fed a lot of data on one thing. It finds patterns in that, it finds regularities in that. It represents those. The more data you feed it, the better it'll be at that. But it's not going to have this kind of general ability and it's not going to grow it out of learning how to speak English.

James Humphries (40:02)

Have you heard the Terry Pratchett quote about it's quite early on. He's talking about Hex, the kind of steampunk computer they make in Unseen Universe University. And it just has this offhand line. A computer program is exactly like a philosophy professor. Unless you ask it the question in exactly the right way, it will delight in giving you a perfectly accurate, completely unhelpful answer. Right? So if you abstract the justified philosophy lecturers there basically what intelligent things do is go, you can't have meant that. You must have meant this right? Chat GPT goes I will take a question as read. And of course it doesn't have an I. There is nothing like I've just anthropomorphised it again. But it's the same thing and it's trained to do incredibly specific things and you get the same problem as any program. Like garbage in, garbage out.

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Ryan Reynolds (42:26)

We choose to go to the moon.

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Ryan Reynolds (42:38)

You're a great pilot, Buzz. As far as I'm concerned, the best I've seen.

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Ryan Reynolds (42:47)

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Ryan Reynolds (42:53)

What do you say, Buzz? Another beer.

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And triumph over addiction.

Ryan Reynolds (42:57)

Here's to you, Buzz Aldrin.

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Ryan Reynolds (43:02)

Buzz and I will proceed into the.

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Ryan Reynolds (43:11)

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Ryan Reynolds (43:23)

Columbia. A foot washed up.

Ed Zitron (43:26)

A shoe with some bones in it.

Ryan Reynolds (43:28)

They had no idea who it was. Most everything was burned up pretty good from the fire that not a whole lot was salvageable.

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He never thought he was going to get caught. And I just looked at my computer screen, I was just like, ah, gotcha.

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Ed Zitron (44:27)

So have you found a lot of students using chat GPT? Because this is a hard problem to quantify. Is it all the time?

James Humphries (44:34)

I mean, it's. It's a lot. I wouldn't say all the time. I. I'm Jay.

Ryan Reynolds (44:38)

You said you thought that there were more C's and D's this semester. Yeah.

Joe Slater (44:43)

So I think there are quite a few and sometimes it is difficult for us to prove. And if we can't prove it, then at our university, then, well, shucks, they kind of get away with it. We can interview them, but unless we're like, unless we have proof that you could take before, like a court, then we are. We're not able to really nail them for it, which is a bit of a shame.

Ed Zitron (45:07)

So it's suspicion.

Joe Slater (45:07)

Yes, we Suspect that a lot of them are very. I'm 100% on some of them.

Ed Zitron (45:12)

I just know what are the clues I want to hear from all of you on this one. Like, what are the signs?

James Humphries (45:16)

It's the uncanny valley. Like, I will not shut up about this. Right? You know that like, you of course will be. Imagine a lot of you, kind of this readable view as well. But the uncanny valley thing in respect of humans is that there's a kind of a point up to which humans seem to trust artificial things more than the more they look like a human. So like, we'll trust a robot if it's kind of bipedal or if it looks like a dog. But after a point we really rapidly start to trust. So like, if it. Basically when it starts looking like data, some deep buried lizard brain goes, danger, danger. This thing's trying to fuck with you somehow.

Ed Zitron (45:50)

Yeah, right.

James Humphries (45:50)

And ChatGPT writes exactly like that. It writes almost, but not entirely, like a thing that is trying to convince you that it's human. I mean, the dead giveaway for me is that it never makes any spelling mistakes, but it can't format a paragraph to save its life. Normally you would expect someone who didn't know how to kind of order their sentences to misspell the occasional word. ChatGPT spelled everything correctly and doesn't know what like subject object agreement is. It's like, it's bad.

Ed Zitron (46:18)

So can you just define that, please? Subject object.

James Humphries (46:22)

The beer that I drink. Right. Not the drink that I beer.

Ed Zitron (46:26)

Right. Because it's interesting. It almost feels like there is just an entire way of processing and delivering information as a human being that we do not understand. There is something missing.

Ryan Reynolds (46:37)

I mean, for me, like, it's very good at summarizing, but when it responds, it responds in the. In really trite and repetitive ways. So like, you'll get a paper that summarizes a bunch of literature at length very effectively and then responds by saying, well, you know, this person said this. That is doubtful. They should say more to support that, you know, which is basically saying nothing. Right? And that's pretty common. It also does lists. It formats things in kind of like a list. And even if the student has done something to like make it look less like a list, the paper still reads like a list.

Ed Zitron (47:15)

Oh, because someone has asked, Give me a few thoughts on X. Yeah, yeah, yeah. That's very depressing.

James Humphries (47:23)

What about you?

Joe Slater (47:24)

Things like the introductions you get. This is an interesting and complex question that philosophers have asked through the ages. And this is one of the things we shout at students not to write from first year. And then you'll get this garbage right back at you. And then at the end it'll be, oh, overall, this is a complicated and difficult question with many nuances.

Ed Zitron (47:48)

It's a world of contrasts.

Joe Slater (47:50)

One of the things we tell them, don't ever fucking do this. This is terrible. And right back at you in perfect English, the sort of English that you'd expect a really good student might have written. But clearly they can't be a good student because otherwise they've listened to our fucking instructions.

Ryan Reynolds (48:07)

I also, I had some papers that I suspected were chatgpt this year, but they were already failing, so I didn't. Oh, okay. Yeah, I didn't think it was worth it to pursue them, you know, as a plagiarism or ChatGPT case.

Ed Zitron (48:23)

So it's never good papers then? It's never like an eight like our first.

James Humphries (48:26)

Oh, no, absolutely not.

Ryan Reynolds (48:28)

So I think that part of what goes on is you can get a passing grade with a ChatGPT paper sometimes in the first couple years when the papers are shorter and we're not expecting as much, but then when you move into the, what we call honors level here, which is like upper level classes in the year us, like third and fourth year.

Ed Zitron (48:48)

I got a first AB with.

Ryan Reynolds (48:50)

I know, yeah, exactly.

Joe Slater (48:52)

Great.

Ryan Reynolds (48:53)

Well done. Well done. You would not have gotten it with ChatGPT because you get dropped in these classes where we expect you to have gained writing skills, minimal ones, in your first two years, and then we're going to build on that and have you do more complicated stuff. And ChatGPT doesn't build on that. Right. It just stays where it was. So. So you go from writing a kind of C grade passing paper to E or F grade paper. And it's also more obvious because the papers are longer. And ChatGPT can write long text, but it gets very repetitive and noticeably repetitive. And so you're kind of lost. Like, you haven't done the work of figuring out how to write on your own. And the tool that you've been using is not up to the task that you're now presented with. And so I think I have seen a few papers that I was suspicious of, but the papers that I was certain of were ones that were like senior theses. Very clearly, the person just had no way of writing coherent.

Ed Zitron (49:56)

That's insane at that stage.

Ryan Reynolds (49:58)

Yeah.

James Humphries (49:59)

I mean, it's bonkers. I mean, one of the things that we get told about is like, oh, students have got to Learn how to use AI, large language models, plagiarism machines responsibly and in a kind of positive way. Well, if they're using them in a way that means they don't learn how to write, then it's not positive, is it? Yeah, it's fucking hard to write a good essay. Yes, it is fucking hard to write. That's why we practice, that's why we have editors, that's why we do this collaboratively. And if you're using this as a sort of, oh, I don't know how to write, well, tough shit, you're never going to know how to write that. That doesn't seem to me to be a positive use of any of this.

Ed Zitron (50:31)

Well, that's the thing. Writing is also reading the consumption of information and then bouncing the ideas off of your brain. Allegedly.

Ryan Reynolds (50:39)

Yeah, I worry about like, because ChatGPT is good at summarizing, so I worry that one of the uses people will think, ah, this is a pretty good use for it is summarizing the paper that they're supposed to read. And it will do that effectively enough for them to discuss it in class if they're willing to be. Right. But they're not going to pick up a lot of the nuances and a lot of the kind of like stylistic ways of presenting ideas that you get when you actually do the reading.

Ed Zitron (51:09)

And it's, it's so frustrating as well because like for this, for example, I've just got the printing off things that don't read PDFs anymore because I feel like you do need to focus.

James Humphries (51:20)

Yeah, there's some evidence that reading physical copies makes you engage more. Sorry, I'm very old fashioned, I guess, but.

Ed Zitron (51:25)

No, it's true though. But also reading that, I wouldn't have really on the PDF, I wouldn't have given it as much attention. But also going through this paper, you could see what you were doing. Like you could see that you were lining up. Here are the qualities that we use to judge bullshit. But also summarizing a paper does not actually give you the argument, it gives you an answer. So what do you actually want students to do instead? Because I don't think there's any reason to use ChatGPT for these reasons. Like it doesn't seem to do anything that's useful for them.

Ryan Reynolds (51:56)

I don't have, no, I don't actually have any use for ChatGPT that I can put to my students and say, here's what I think you should do with it. We are like kind of developing strategies for keeping them from using it. So, like building directly on what you're saying. Like in my class next year, I'm going to have the students do regular assignments which are argument summaries and not paper summaries. So the idea is they have to read the paper, find an argument, and tell me what are the premises, what's the conclusion? And that's something that ChatGPT is not good at. Right. But it's also something that will give them critical reading skills, which is what I want to do. Right. So, yeah, I think that I've mostly been thinking about ways to keep them from relying on it. Because I think that often if they rely on it, they'll, they'll, they'll put themselves in the worst position. Yeah. When it comes to future work, they won't develop the skills that they're going to need and the skills that we tell them and their parents they're going to get with their college degree. Right.

Ed Zitron (52:59)

It almost feels like we need more deliberacy in university education because I was not taught to write. I just did a lot of it until I got good enough grades. And Daniel Chandler, great mentor, but I've had tons of them. And it almost feels like we need classes where it's like, okay, no computer for this one. I'm gonna print this paper out and you're gonna underline the things that are important and talk to me about. Almost feels like we need to rebuild this because, yes, we shouldn't be using ChatGPT to half ass our essays, but at the same time, human beings are lazy.

Ryan Reynolds (53:32)

Yeah. I mean, for me, I also prefer to read off the computer, but I often read PDFs because I'm terrible at keeping files. Right. Physical. Like, you know, I'm not going to keep a giant file drawer with all the papers that I've read and then written my liner notes in. You guys can see in my office, they're just piled around like, you can't see this end.

Ed Zitron (53:55)

That's academia.

Ryan Reynolds (53:56)

Yeah. But I just have piles of paper with empty coffee mugs everywhere that the camera is not facing. But it's the terrible system. So at least on my computer, if I'm like, oh, I read that paper like a year ago, what did I think? I can click on it and see my own notes. And I do think that there's something to keeping those records and kind of actively reading in that way. I don't know how I ended this without telling you how to make students do that.

James Humphries (54:22)

You started with the correct answer, which is don't use ChatGPT. Yeah, I actually, I've got a certain amount of sympathy with, like, just keep writing until you get good at it. But I realize as a lecturer, that can't be my official position and I certainly think that it's the case that certainly Glasgow has got better over the last few years about going, oh, actually, you do. Like, we do need to give you some kind of structuring and some buttressing on. Here's how to write academically, here's how to do research. And I think that's all to the good. It's worth saying this started happening well before ChatGPT started pissing all over our doorstep. So they don't get to claim that as being a benefit.

Ed Zitron (54:57)

There was the whole Wikipedia panic when I was in school.

Ryan Reynolds (54:59)

Yeah, yeah.

James Humphries (55:00)

The thing about Wikipedia, right, It's like, I used to say this to my.

Ed Zitron (55:03)

Students, actually one of the best resources.

James Humphries (55:05)

It's absolutely fine as a starting point for research.

Ryan Reynolds (55:08)

Yeah.

James Humphries (55:09)

Absolutely no problem with it whatsoever. But if you're turning in an honors level essay, I want you to go and read the fucking things it's referencing.

Ryan Reynolds (55:16)

Yeah, that's right.

James Humphries (55:17)

Yeah.

Ryan Reynolds (55:18)

I think these things are often greatest sources. My worry about ChatGPT is that it's not great as a source. It's just. Yeah, we've been saying it often gets things wrong and it often. It'll make up sources, whereas Wikipedia will never do that.

James Humphries (55:30)

I don't think there are some famous.

Ryan Reynolds (55:33)

Hoaxes, but let's edit it out fast.

James Humphries (55:35)

They get cool. Yeah. Joe, have you got any positive things to say about ChatGPT?

Joe Slater (55:40)

Positive things to say about it?

Ed Zitron (55:41)

Big fan.

Joe Slater (55:43)

So I know some people who have used these kinds of things productively, not in ways that our students would, but I know some mathematicians who have been using it to do sort of informal proofs and things like that. And it does feel bullshit, and it bullshits very convincingly, which makes it very difficult to use for this kind of purpose. But it can do some interesting and cool things, I think some people in that sort of field have found useful. And also, we've mentioned this before, like, if you want ChatGPT to write you a bibliography, you've got a bibliography in one style. Tell it to put something into a different one, then it's good for that and it's good for coding, data processing, doing certain things.

Ryan Reynolds (56:25)

I also think. I don't know. I'm not sure how I feel about what I'm about to say, but perfect. Yeah, I'm going for it. It is a Somewhat positive thing maybe for ChatGPT which is that we often have students who have like really interesting ideas and well thought out arguments but for whom English isn't their first language and the actual writing is kind of rough and you have to like push through reading it to get the good idea which is often really there quite, you know, creative and insightful and so I do wonder if there's a way to use it so it just smooths off the edges of this kind of thing. But I worry that if you tell students to do that they'll just first they can develop the language skills. They often get really good by the end. Yeah. What are you going to say, James?

James Humphries (57:11)

I want to say yeah, you can see me getting agitated. I think Mike's correct about like that this is a kind of possible use but I think this, and this is why I'm getting visibly agitated here. That's students either need to or feel they need to use. This speaks to a deeper issue, right? To a social issue, to a political issue, to an issue about how universities work. If a student is having problems with English then there's a number of like explanations or a number of kind of responses. Right. One response is that like Glasgow is an English teaching university. If someone's English isn't good enough to be taking a degree then plausible they shouldn't have been let in. And why have they been let in? Well, because of money or alternatively if someone's having problems with English for like whatever reason at all, there should be support here. There should be kind of tutors, there should be people who can help with English. But again that will cost university money. So of course that doesn't happen, Right. It doesn't happen anywhere. It doesn't anyone extent. It would have to happen in order for this to be a general policy, right?

Ryan Reynolds (58:07)

Yeah, I think it could be better. But I do think that universities often have like a writing center or a tutoring center that you can and.

James Humphries (58:16)

But they don't, they don't have the sort of spread that would be needed or the staff that would be needed for this to be. Instead of using chat GPT to sound the edges off.

Ryan Reynolds (58:25)

Yeah, I think for example to get.

James Humphries (58:27)

Through with your supervisor.

Ryan Reynolds (58:28)

My worry especially would be that this is my first year here at Glasgow, but I think they probably have a good, I think they probably have a good writing center. Universities I've been in the past, I felt very confident sending students to the, the writing center when they have these problems. But I think James is completely right that we don't Want the universities to see this as a way to get rid of the writing center. And that's 100% a risk given the financial problems that universities are facing. And maybe we're already not in the writing center as much as we'd like, given the quality of papers we sometimes get. But they're often good. I think another thing, as far as this is like a social problem is that when grading, I myself try to grade in terms of like, the ideas and argument, because this is philosophy and not the quality of the right. But not everybody does that. So I kind of think that another part of this is figuring out how we want to evaluate the students and what we want to privilege in that evaluation.

James Humphries (59:27)

Yeah, sure. So then again, the kind of that. That becomes a problem about what people are checking for. Not let's take this arch backwards approach to marking, which is like, how fancy is your English? Fancy English is good. Eng have an A. But rather, we should be kind of checking for different things. Right. So again, the blame lies differently in that case. But it still becomes a question that's not solved technologically.

Ryan Reynolds (59:47)

Yeah.

Ed Zitron (59:48)

Almost feels like large language models are taking advantage of a certain kind of organizational failure.

Ryan Reynolds (59:53)

Oh, yeah, what an idea.

Ed Zitron (59:56)

Crazy that the tech industry manipulating a part of society that was weak.

Ryan Reynolds (60:01)

I have a kind of related tangent here, which is like, what are the use cases that OpenAI was expecting but didn't want to emphasize? Because for everybody in universities, as soon as this came out, the first thought was, students are going to use this to cheat. And certainly, like, the people in OpenAI went to college. Right. That's what I hear about them. So they must know.

Ed Zitron (60:24)

Well, Sam Altman dropped down.

Ryan Reynolds (60:27)

Yeah. I'm sure he really understands the value of a secondary.

Ed Zitron (60:30)

He's like, I got to write all these fucking essays anyway.

Ryan Reynolds (60:33)

Maybe he was thinking, I would have loved to have a computer write my essays. I'll devote my life. But I mean, I'm sure that they, like, recognize these bad use cases. Right. But they're doing nothing to mitigate them, as far as I can see. And like, another one that's very related is like, you know, I'm sure you've heard of this Ed Phishing, right? A lot of, you know, corporations get attacked and get hacked not by someone cleverly figuring out a back door to their system, but by somebody sending social engineering. Yeah, yeah. Asking for the password of somebody else. And one of the biggest barriers to that is that a lot of the people who are engaging in phishing aren't from the same country as the company they're targeting. Right. So they're not able to write a convincing email or make a phone call that sounds like that person's supervisor. But with a tool like this, you could 100% write that email. Right. It's going to make it a lot easier for these kinds of illicit schemes to work.

Ed Zitron (61:32)

There has been a market increase, according to CNBC, which you just brought up, so 1,265 increase in malicious phishing emails since the launch of Chat GPT. Great stuff.

Ryan Reynolds (61:41)

I mean, if I could have thought.

Ed Zitron (61:42)

Of that, imagine what a criminal could do.

Ryan Reynolds (61:46)

Right? But also, weren't the people at OpenAI thinking about that, like they don't care? Yeah, yeah.

James Humphries (61:52)

We've all seen Jurassic park, right?

Ryan Reynolds (61:54)

Yeah, yeah.

James Humphries (61:55)

They were so busy thinking about what they could do, then everything about whether they should.

Ryan Reynolds (61:58)

Yeah. This is the kind of problem with the move fast and break things mentality. Like they're obvious. I mean, I think I might be the only person who was raised in the us, but we had future problem solvers where you, you know, you think about a future problem and what bad consequences there could be of some technology and how to solve them, usually through social cues. If I could do that in fifth grade, I would expect these people to have thought through some of the bad consequences of the technology they're putting out. And some of those are cheating on tests and they don't seem to have worried about that. And another one is phishing, they don't seem to have worried about that.

James Humphries (62:37)

Biases in algorithms. Right. So this again comes as no surprise to you, Edward. It turns out. So with a lot of the facial recognition systems, they were incredibly racist.

Ed Zitron (62:46)

They were going back to Microsoft's Kinect. They could not see black people and.

James Humphries (62:51)

CCTV stuff that basically just sort of, unless it was presented with a blindingly white Caucasian, went, I don't know. Right. But like the sort of stuff where these large language models are trained on certain sets of data and they're trained on certain assumptions and like shit in, shit out. Particularly if people think that it's actually doing any kind of thinking and if they kind of cargo cult it, we again get a kind of social problem multiplied by technology feeding back into a social problem. And it's the, sorry, these guys have heard me whinge about it so much, I love it here or so. But I'm profoundly skeptical of technology's ability to solve anything unless we know exactly the respect in which we want to solve it and how that technology is going to be applied. You know, like sure, experiment with bring back dinosaurs, but like, don't tell me that it's going to save the health care system unless you can demonstrate it to me step by step how that big old T Rex run around on Island Newblade is going to save anything and they just try and blind people.

Joe Slater (63:55)

Actually bringing back dinosaurs would be just good in itself.

Ryan Reynolds (63:58)

That would be great.

James Humphries (63:59)

All right, this isn't the best example, but I already had. I had Jeff Goldblum in my head and I had to go to the Jurassic park example.

Ed Zitron (64:07)

Fellas, this has been such a pleasure.

Ryan Reynolds (64:09)

Oh, right, are we out of.

Ed Zitron (64:11)

Don't put that in the recording. That's right, we won't edit it in post. Can you all give us your names?

Ryan Reynolds (64:19)

I'm Mike Hicks, but my papers are written by Michael Townsend Hicks and I'm a lecturer at the University of Glasgow. My website is Townsend Hicks.

Ed Zitron (64:28)

It'll be in the podcast profile. Don't you worry, you'll get that.

Ryan Reynolds (64:31)

Great. Just plug in my.

Ed Zitron (64:33)

Plug your stuff.

Ryan Reynolds (64:33)

Plug in my page.

Ed Zitron (64:34)

Plug it.

Joe Slater (64:35)

My name is Joe Slater. I'm a university lecturer in moral and political philosophy at Glasgow.

James Humphries (64:41)

I'm James Humphries. I'm a lecturer in political theory at the University of Glasgow. And even if I wanted to, I couldn't give you my website because I don't have one.

Ed Zitron (64:50)

Everyone, you've been listening to Better Offline. Thank you so much for listening. Everyone, guys, thank you for joining me.

James Humphries (64:55)

Thanks for having us.

Ryan Reynolds (64:56)

Cheers. Cheers.

Ed Zitron (65:06)

Thank you for listening to Better Offline. The editor and composer of the Better Offline theme song is Mattasowski. You can check out more of his music and audio projects@matasowski.com m a t t o s o w s k-I.com you can email me at ezetteroffline.com or visit betteroffline.com to find more podcast links and of course, my newsletter. I also really recommend you go to chat where's your ed at? To visit the Discord and go to R betteroffline to check out our Reddit. Thank you so much for listening. Better Offline is a production of Cool Zone Media.

iHeart Podcast (65:41)

For more from Cool Zone Media, visit.

Ryan Reynolds (65:43)

Our website coolzone media.com or check us out on the iHeartRadio app, Apple Podcasts.

iHeart Podcast (65:49)

Or wherever you get your podcasts.

Ed Zitron (66:11)

Say you've always wanted to get those new audiophile grade speakers. Here's the thing, if you invest well, you could get things like that. With Empower, you can get money working for you so you can go out and live a little Isn't that why we work so hard to splurge sometimes, like on a massive high res TV? Because the 65 inch one just isn't quite big enough? So use Empower to help get good at money so you can be a little bad. Join their 19 million customers today@empower.com not an Empower client, paid or sponsored.

Michael Townsend Hicks (66:38)

Hello, I'm John Lithgow.

Ryan Reynolds (66:40)

We choose to go to the moon.

Michael Townsend Hicks (66:41)

I want to tell you about my new fiction podcast about Buzz Aldrin, one of the true podcasts pioneers of space.

Ryan Reynolds (66:50)

You're a great pilot, Buzz.

Michael Townsend Hicks (66:52)

That's the story you think you know. This is the story you don't. Buzz starring me, John Lithgow on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

James Humphries (67:09)

It's Black Business Month and Money and wealth podcast with John Hope Bryant is tapping in.

Ryan Reynolds (67:13)

I'm breaking down how to build wealth.

James Humphries (67:16)

Create opportunities, and move from surviving to thriving. It's time to talk about ownership, equity, and everything in between. Black and brown communities have historically been last in line. Let me just say this AI is moving faster than civil rights legislation ever did. Listen to Money and wealth from the Black Effect podcast network on iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

Ryan Reynolds (67:38)

I'm Jeff Perelman.

James Humphries (67:39)

And I'm Rick Jervis. We're journalists and hosts of the podcast Finding Sexy Sweat. At an internship in 1993, we roomed with Reggie Payne, aspiring reporter and RA.

Ed Zitron (67:48)

Who went by Sexy Sweat a couple years ago. We set out to find him, but.

James Humphries (67:52)

In 2020, Reddy fell into a coma after police pinned him down and he never woke up.

Ryan Reynolds (67:56)

But then I see my son's not moving.

Ed Zitron (67:58)

So we started digging and uncovered city.

James Humphries (68:00)

Officials bent on protecting their own. Listen to Finding Sexy Sweat on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

iHeart Podcast (68:08)

This is an iheart pod.