Better Offline - CZM Rewind: The Academics That Think ChatGPT Is BS

Episode Date: August 13, 2025

In a paper released earlier this year, three academics from the University of Glasgow classified ChatGPT's outputs not as "lies," but as "BS" - as defined by philosopher Harry G. Frankfurt in "on BS" (and yes I'm censoring that) - and created one of the most enjoyable and prescient papers ever written. In this episode, Ed Zitron is joined by academics Michael Townsen Hicks, James Humphries and Joe Slater in a free-wheeling conversation about ChatGPT's mediocrity - and how it's not built to represent the world at all. Paper: https://link.springer.com/article/10.1007/s10676-024-09775-5Michael Townsen Hicks: https://www.townsenhicks.com/Joe Slater: https://www.gla.ac.uk/schools/humanities/staff/joeslater/ Original Air Date: 7.18.24 YOU CAN NOW BUY BETTER OFFLINE MERCH! Go to https://cottonbureau.com/people/better-offline and use code FREE99 for free shipping on orders of $99 or more. BUY A LIMITED EDITION BETTER OFFLINE CHALLENGE COIN! https://cottonbureau.com/p/XSH74N/challenge-coin/better-offline-challenge-coin#/29269226/gold-metal-1.75in --- LINKS: https://www.tinyurl.com/betterofflinelinks Newsletter: https://www.wheresyoured.at/ Reddit: https://www.reddit.com/r/BetterOffline/  Discord: chat.wheresyoured.at Ed's Socials: https://twitter.com/edzitron https://www.instagram.com/edzitronSee omnystudio.com/listener for privacy information.

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Hey everyone, it's me, Ed Zittron, and we're doing a rerun episode this week. Sadly, the in-studio recording we did with Ashman Rodriguez and Victoria's song, we had a technical fault, nothing we can do. It sucks, but we're doing a rerun this week. We're doing the academics that think chat GBT is BS. And this is one of my favorite episodes ever recorded. It changed how I do interviews are at large. It's with these three academics, Michael Towns and Hicks, James Humphreys and Joe Slater,

who wrote a paper using the actual Frank Furtian definition of bullshit to say that chat GBT bullshit. It's so much fun. It's one of my favorite episodes of recorded. I will have you a monologue this week as well. I do apologize for not having something new for you this week. You'll still get the monologue on Friday, though. Thank you for your time, your patience, and of course for listening to BetRofLine.

Hello and welcome to Better Offline. I'm your host, Ed Zedron. In early June, three researchers from the University of Glasgow published a paper in the Ethics of Information and Technology Journal called ChatGBT is bullshit. And I just want to be clear, this is a... great and thoroughly researched from 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 Humphreys, and Joe Slater to talk about chat GBT'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?

So you are bullshitting. If you are speaking without caring about the truth of why. 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. If 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. Right. And you define between, like, soft and hard bullshit. Can you also get into that? that as well. Can you also identify

yourselves as well? Sorry, yeah, I'm Joe. So the soft bullshit hard bullshit distinctions are very serious and technical distinction. Right. So we came up with this because bullshit is in the technical philosophical sense. Comes from

Harry Frankfurt, recently deceased, but a really great philosopher. And he talks about the amount of bullshit that there is in a popular culture and just in general discourse these days. Some of the way he talks about bullshit seem to suggest that it needs to be accompanied by a sort of malign intention. I'm doing something kind of bad. I'm intending to mislead you about the enterprise of what I'm doing.

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 why you're saying it.

That's what we call hard bullshit. And it's one of the things Frankfurt talked about. 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 chat GPT and other large language models,

they don't really have this intention to deceive because they're not people that 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. Well, I'm James, by the way. I suppose we strictly don't want to say that they aren't hard bullsheders. 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 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 they're 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 brocropper. Yes, that's nonsense. Yeah. But if they are, then they're hard bullshitters and minimally their soft bullshitters or their bullshit machines. 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 jail broke, chat GPT, listed all of the things it's prompted to do. Could prompting be considered intentional that Sam Altman, CEO of Open AI, could be intentionally bullshitting? I think he is. Yeah, and 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 proposive or teleological

attitude towards right, kind of 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 sort of wanted, I mean, it's a standard philosophical move, right? Just 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 to the sort of view that you're putting. I think you're kind of sympathetic to this as well, right? Yeah. So I'm Mike. There are a few ways that you can think of chat Chb-T is 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 intentions. 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? Right. 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, right? 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 read.

There is something very collegiate about the way it bullshits, though. It reminds me of when I was in college, went to Penn State and Abarist with two very different institutions. Right. Right. Both kind of in the middle of nowhere. Yeah, both very sad. But the one thing you saw with students who were doing, like, B-plus homework is they were using words they didn't really understand. They were putting things together in a way that it 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? I won't feel this because whenever Mike tells the story, you get sinus. version. We were in the pub winging about student essays. Perfect. Yeah, like, you were not long here, right? You were not long. I just started. Yeah, not long in post of a whole bunch of us that went to the pub on a notional let's, let's welcome our new members of staff sort of event. And inevitably, with it about two pints, we were all pissing and moaning. And I think it might have been Neil that

kind of prompted this. No, I don't think he was near. You know, okay, fair enough. We talked to him about it, though. We talked to him about it after, right? In any case, like, so it came up, we were talking about this sort of prevalence of chat GPT generated stuff and kind of, what said about how at least some students were kind of approaching the assessments. And I forget who someone sort of just went offhandly. Yeah, but it's all just Frank Furtian bullshit, though, isn't it? And we sort of collectively went, oh, hello. Because obviously all having a background in floss. We've all read on bullshit. You know, we all went, he, he, we get to say bullshit in a literally 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 Frank Fertian bullshit in a way that we'd, can probably get a paper ourselves. Yeah. And at that point, I think we were in the department meetings talking about how to deal with chat GPT 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. But not for essays. Right. That's the worry 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 worked,

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 just seemed like an obvious paper that someone was going to write and we thought that it better be us.

Eventually, people are going to see this connection. It's a great paper. 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, oh, yes, that's right. It's an interesting philosophical concept as well, because the way that people look at chat GPT 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? I mean, kind of his background, I do philosophy of science, but my thoughts about something like chat GPT are largely inspired by the fact that I also teach a class called understanding philosophy through science fiction.

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, are connected in some way to the external world, usually causation. We're perceiving things. Information is coming in. 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. It's just tracking external world things.

And it's a very important part of childhood development when you figure out how to it's semiotics, right? Daniel Chandler Averiswist with taught me semiotics. It's like a perception of the world. This is like theory of meaning stuff. So, yeah, semiotics is like theory of signs. How is it that a sign? A sign can be both the representation of the thing and the thing itself.

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 chat GPT 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. It's divorced from experience. Yeah. I mean, as far as I can tell, it doesn't have anything like.

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-sovenism, right? Aren't you just assuming that unless something runs on like meat, it can't be sentient? And this isn't something we get into into 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, 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, chat GPT just doesn't seem to meet any of them.

Like, kind of it's, if it does turn out that it's sapient, then chat GPT has got some profoundly serious executive function disorders. But of course, it's not sapien, right? So we don't have to worry about it, but 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 that's just bullshit. This is a classic case of bullshit. Yeah, 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 not accurately enough. Yeah, it's got various guidelines that allow to throw shit at the wall with a sort of reasonably high degree of action. No, you're right. I mean, one of things that a human bullshitter could at least be characterized as doing is they'd have to try and kind of judge their audience, right? They'd have to try and make the bullshit plausible to

the audience that they're speaking to. And chat GPT 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. Right. 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, right, kind of data and contexts in which... Yeah, probabilistic planning of, 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.

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 in 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 any room for in its architecture. This is something of Italian, 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... What does that mean just for? Not for me. I

definitely know. 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 we, it seems that we've got a grasp on this incredibly early on in a way that doesn't look like it's the ways, at least most of us, at taught language, right? We get quite harshly told off when we try and do explet it in fixation. Yes. So this, I think, would be one of those cases where you could do a sort of disanalogy by cases, right? You present chat GPT a sentence and insert the word fucking correctly in this sentence. And I don't think it would be very good at it.

I think it would be. I think it would. You reckon? I mean, we probably could test this. We could. But we shouldn't. Not right now. 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. You know, 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 chat GPT would understand those. That's another Chomsky example. So, you know, Chomsky has this example that's like, what is it?

The colorless green. Green wuzzles sleep furiously? It's colorless green ideas, I think, sleep curiously, right? And that's a meaningless sense. but it's grammatically well-formed. And we can understand that it's grammatically well-formed, but also that it's meaningless. Because ChatGBT-T 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 I differentiate between grammaticality and meaninglessness. Another podcast from some SNL late-night comedy guy. Not quite. Unhumor me with Robert Smygel and friends. Me and hilarious guests from Jim Gaffigan to Bob Odenkirk to David Letterman, help make you funnier.

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and I would say 50% of the time it got it right and it did man that's fucking crazy man that's crazy fucking man that's fucking crazy my favorite is man comma that's crazy comma fucking to be fair

I think you're right very unreliable you take the commas out of that last one and you've got a grammatical sentence of course in Glasgow you can also start with fucking man that's crazy West London as well but the thing is though

it doesn't know what correct means there. Yeah, no. 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. Yeah. Yeah, exactly. There's a, I don't know if you have already talked to somebody about this, but there's a, you know, a classic argument from Chomsky against behaviorism. Right. Behaviorism is the view that we learn everything through stimulus and response.

That's not exactly that. 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's been some papers arguing that ChatsyPT 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, right? So Chomsky's argument was we don't get enough stimulus. And Chatsy-B-T 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 learning. Which is kind of interesting. And it still can't do something as basic as putting the word fuck into it. Right.

It doesn't even see, and it doesn't have the knowledge to say, request more content. because it doesn't perceive context. And that's kind of the interesting thing. So there was another paper out of Oxford, I think, that's talking about cognition and chat GPT and all this thing. And it's just, it doesn't feed, chat GPT 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 Marvel question, which is you don't like the two. term hallucination. Why is that? 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 be, right? Imagine I hallucinate, there's a red balloon in front of me. I still see my, 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 I, and this is the way I usually get knowledge about the world. Right. This is a pretty reliable process for me. Being stuff and learning from it, right? And representing the world in this way. So we talk about hallucinations. This suggests that chaty PT 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 like 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 CHAPT is doing every time it produces an output. So this is why we think bullshit is a better way of thinking about this. But one of the reasons why we think bullshit is a better way to think about it.

I also kind of think that some of the ways we talk about chat CHAPT, 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. And it has perception.

Yeah, exactly. It has perceived something and like, oh, no, it's taken some computer acid and now it's hallucinating, like, imaginary things. And yeah, just as you say. And that's 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 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. Yeah, just to sort of cap that off if I can. One of the response to some corners has been to say, of us, look, you whinge about people anthropomorphizing chat GPT, but look, if you call it a bullshit, 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. And 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 chat GPT 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. 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 anthropomize living things, but also when we communicate with something, language is life. And so it probably works out really fucking well for them. Sam Alton was saying a couple 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 con. 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 in AI. FATE consciousness. Yeah, yeah. But I had thought about like how this might have been caused by just like deep misunderstandings of the Turing test. Right, go ahead. No, I want to hear this one.

Yeah, yeah. So 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 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 all of us think that. I think it's possible. Great. Yeah. I didn't know if they thought it was possible because not everybody thinks it's possible.

It's possible. I just don't know how. Yeah, exactly. So Turing was kind of, you know, 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 be the Turing test, right? And popularizations of these attempts and run-throughs of the Turing test

the talk as if, oh, if a computer finally beats the Turing test, I should say what the Turing test is, right? Yeah. 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. Right. And if the judge can't tell which of the people he's chatting with is a human, then the computer's won. Right. Right.

Because it's only distinguishable from a human, right? So people have taken this, and it's been popularized as a way of determining sort of, with 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 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 it's internal functioning. 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 DeVoy Kampf in Do Androids Tune with Electric Sheep, right? Plenty of humans would fail the Turing test.

Yeah, right? Yeah, it is a piece of evidence, but it was never, as Mike says, it was supposed to be constituent. It wasn't like, if you can do this thing, your conscious kind of full stops. It was supposed to be, here is a thing that might indicate that being you're talking to is conscious. Happily, as much sense, we've got loads and loads of other evidence. So these guys have made a machine that's just designed to do one thing, and that's past the Turing test. 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 with 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. 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 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, you know, capable of applying

reasoning to multiple kinds of different and disanalogous cases. On the one hand, it does seem a little bit like the guy flipping the table and go, oh, for fuck's sake, now you've one, 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, like, you know, like activate certain chivalets, 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. Is the same with ChatGPT. It's built to resemble intelligence and resemble consciousness and resemble these things, but it isn't. It's almost like it's meaningless on a very high-end philosophical

level. I find the whole generative AI, I think, deeply nihilistic. 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 Chat GPD is very bad at doing reasoning if it has to be, you know, sort of an extended argument or a proof or something like that. It's, it's very bad at it. I think also that if there's one thing kind of we learn from chat GPT, it's that this is not the way to get to artificial general intelligence. I was going to ask, do you think that this is getting to that? No, partially because it's so subject specific, right? It's one, it's trained to do one task. And it takes, 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. 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, when you have with these kind of big basements models is something that is really good. 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 will 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. 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 Uncena University, and he 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 shot of philosophy lecture is there, basically what intelligent things do is go, you can't have meant that, you must have meant this, right? Chat, GPD goes, uh, I will take a question as read. I mean, of course, it doesn't have an eye. There's nothing in the rest. Like, I've just answered 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. Another podcast from some SNL late-night comedy guide, not quite. Unhumor me with Robert Smigel and Friends. Me and hilarious guests from Jim Gaffigan to Bob Odenkirk, to David Letterman, help make you funnier. This week, my guest, SNL's Mikey Day and head writer Streeter Seidel,

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So have you found a lot of students using Chat, GPD? Because this is a hard problem to quantify. it all the time? I mean, it's a lot. I wouldn't say it all the time. Jay, you thought you thought you thought there were more season. Yeah. 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 have the 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. So it's suspicion? Yes.

We suspect that a lot of them are very, I'm 100% on some of them. I just know. What are the clues? I want to hear from all of you on this one. Like, what are the signs? It's the uncanny value. Like I will not shut up about this, right? You know that, like you, of course, would be I imagine a lot of here kind of,

this really would be 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 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 trusting it. 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. Yeah, right. And chat GPT 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,

but it can 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. Chat GPP spells everything correctly and doesn't know what, like, subject-object agreement is. It's, like, it's bad. So can you just define that, please? Subject-object. The beer that I drink, right?

Not the drink that I beer. 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. I mean, for me, like, it's very good at summarizing,

but when it responds, it responds in really trite and repetitive ways. So it'll 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. Yeah. And that's pretty common. It also does lists. It formats things in kind of like a list. And even if the students don't make it look less like a list, the paper still reads like a list. Oh, because someone has asked,

give me a few thoughts on X. Yeah. Yeah. That's very depressing. What about you? Things like the introductions you get. Oh, no, yeah. This is an interesting and,

complex question that class members have asked you 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. It's a world of contrast. 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 instruction. I also, I had some papers that I suspected were chat GPT this year, but they were already failing. So I didn't think, yeah, I didn't think it was

worth it to pursue them, you know, as a plagiarism or chat GPT case. So it's never good papers then. It's never like an eight, like a first. Oh, no, absolutely not. So I think that part of what goes on is you can get a passing grade with the chat GPT 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 U.S., like third and fourth year. I've got a first to have a wrist with. Oh, no. Yeah, exactly. Great. Well done. Well done. You would not have gotten it with chat GPT 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 you go from writing a kind of C-grade passing paper to your F-grade paper, and it's also more obvious because the papers are longer, and Chat-GPT can write long text, but it gets very repetitive and noticeably repetitive, right? 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. And very clearly, a person just had no way of writing. That's insightful. That's

insane at that stage. Yeah. I mean, it's bonkers. I mean, one of the things that we get told about is like, oh, our students have got to learn how to use, you know, 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? Like, 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, or I don't know how to write, tough shit. You're never going to know how to write. That doesn't seem to be a positive use of any of this. Well, that's the thing. Writing is also reading, the consumption of information and then

bouncing the ideas off of your brain, allegedly. Yeah, I worry about, like, because chat GPT 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. Yeah. 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. 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. Yeah. There's some evidence that reading physical

copies makes you engage more. Sorry, I'm very old-fashioned. But no, it's true, though, but also reading that, I wouldn't have really, on a 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 chat GPT for these reasons. It doesn't seem to do anything that's useful for them. I don't have, no, I don't actually have any use for chat GPT 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. 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 chat chbt is not good at, right? But it's also something that will give them critical reading skill, 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 put themselves in a worse 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 in their parents, they're going to get with their college degree, right? He 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 going to print this paper out and you're going to undone, align 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 chat GPT to half ask our essays, but at the same time, human beings are lazy. 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 with all the papers that I read and then written my letter. notes in, you guys can see in my office, they're just piled around. Like, you can't see this ed. That's academia. Yeah, but I just have piles of paper with empty coffee bugs 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. to do that. No, you started with the correct answer, which is don't use chat GPT. 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 chat GPT

started pissing all over our doorstep so they don't get to claim that as being a benefit there was the whole Wikipedia panic when I was in school yeah yeah the thing about Wikipedia right it's like I used to say this to my students actually one of the best resources it's absolutely fine as a starting point for research yeah absolutely no problem with it whatsoever but if you're turning in an honours level essay I want you to go and read the fucking things it's referencing yeah that's right um yeah I think these things are often great as sources.

My worry about chat GPT is that it's not great as a source. It's just, we've been saying it often gets things wrong, and it often will make up sources, whereas Wikipedia will never do that. There are some famous hoaxes. Yeah, it gets edited out fast. They get caught, yeah. Joe, have you got any positive things to say about chat GPT?

Positive things to say about that. Big fan. 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 still bullshit, and it bullshit is very convincingly, which makes it very difficult to use for this kind of purpose. But it can do some interesting and cool things. You know, I think some people in that sort of field have found useful. And also, we've mentioned this before, like if you want Chapter of

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 like coding. Data processing. Doing certain things. 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 chat GPT, 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 push through reading it to get the good idea, which is often really there and quite 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 if they can develop the language skills. They often get really good by the end. Yeah, what are you going to say, James?

I want to say, yeah, you can see me getting agitated. I think it might's correct about that this is a kind of possible use, but I think this, and this is why I'm getting visibly agitated here, that 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 explanations or a number of kind of response, right? One response is that, like, Glasgow isn't English teaching university.

if someone's English isn't good enough to be taking a degree, then plausibly it shouldn't have been let in, and why have they been letting well because of money. Or alternatively, if someone's having problems with English, for like whatever reason at all, there should be supported, 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. It doesn't happen anyway. it doesn't have anyone in the extent it would have to happen in order for this to be a general policy, right? 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 send students to. But 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. Yeah. To, for example, to try through with your supervisor. 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 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 they're already not given the quality of papers. 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, this is philosophy and not the quality of age. Right.

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. Yeah, sure. So then again, that becomes a problem about what people are checking for, not let's take this arse backwards approach to marking, which is like how fancy is you're in? English. Ah, fancy English is good English, have an A, but rather we should be kind of jacking

for different things. So again, the blame relies differently in that case, but it still becomes a question that's not solved technologically. Yeah. Almost feels like large language models are taking advantage of a certain kind of organizational failure. Oh, yes. What an idea. Crazy that, the tech industry manipulating a part of society that was weak. Yeah, I have a kind of related tangent here, which is like what are the use cases that, those are. Open AI was expecting, but didn't want to emphasize. Because for everybody in university, as soon as this came out, the first thought was, students are going to use this to cheat.

And certainly, like, the people in Open AI went to college, right? And that's what I hear about them. So they must know. Well, Sam Olman dropped out. Yeah, I'm sure he really understands the value of a secondary. He's like, I've got to write these fucking essays. Anyway, 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, fishing, 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 it. Social engineering. Yeah. Asking for the password to somebody else. And one of the biggest barriers to that is that a lot of the people who are engaging in fishing

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 supervising. 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. There has been a marked increase according to CNBC, which you just brought up. So 1,265% increase in malicious fishing email since the launch of Chat, GPT. Great stuff.

I mean, if I could have thought of that. Imagine what a criminal could do. Right, but also, weren't the people at Open AI thinking about that? They don't care. Yeah, yeah. We've all seen Jurassic Park, right? Yeah, yeah. They were so busy thinking about what they could do.

They never thought about whether they should. 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 U.S., 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, you know, some of those are cheating on tests,

and they don't seem to have worried about that. And another one is fishing. They don't seem to have afraid about that, you know. And biases in algorithms, right? Yeah, yeah. This again is a, you know, I'll come as a nice surprise to you, Edward, it turns out. So with a lot of the facial recognition systems, they were incredibly racist. They were going back to Microsoft's Connect. They could not see Black.

Yeah, yeah, yeah. And kind of CCTV stuff that basically just sort of, unless it was presented with a blindingly white Caucasian, went, I don't know, right? Right. Right on. The sort of stuff where these, like, language models are trained on certain sets of data and they're trained on certain assumptions and, you know, like, shitting shit out, right? And 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 when you about it so much. Oh, I love it. A year 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. Sure, experiment with bringing back dinosaurs, but don't tell me that it's going to save the healthcare system unless you can demonstrate it to be step by step how that big old T-Rex run around on Ila-Nublaid is going to save anything.

And they just tried blind people. Actually, bringing back dinosaurs would be just good in itself. That would be great. All right, this isn't the best example, but I already had Jeff Gobble in my head, and I had to go to the drastic fuck, for example. Fellas, this has been such a pleasure. Oh, right, are we on it? Don't put that in the recording.

That's fine. We won't edit it in post. And you will give us your names? 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. It'll be in the podcast profile, don't you worry. You'll get that.

All right. Just plug in my... Plug your stuff. Plug it. Plug it. My name is Joe Slater. I'm a university lecturer in moral and political philosophy at Glasgow. I'm James Humphreys.

I'm a lecturer in political theory at the University of Glasgow. And even if I wanted to or can give you my website, because I don't have all. Fuck you. Everyone you've been listening to Vetter Offline. Thank you so much for listening, everyone. Guys, thank you for joining me. Thanks, having us. See, yeah.

Cheers. Cheers. Thank you for listening to Better Offline. The editor and composer of the Better Offline theme song is Mattosowski. You can check out more of his music and audio projects at Mattisowski.com. M-A-T-T-O-S-O-S-K-I.com. You can email me at E-Z at Better Offline.com or visit Better Offline.com to find more podcast links and, of course, my newsletter. I also really recommend you go to chat.

Where's Your Ed dot at to visit the Discord and go to R-S-Better-O-Line to check out our Reddit. Thank you so much for listening. Better Offline is a production of Cool Zone Media. For more from Cool Zone Media, visit our website, coolzonemedia.com, or check us out on the IHeartRadio app, Apple Podcasts, or wherever you get your podcasts. Another podcast from some SNL late-night comedy guy, not quite. Unhumor me with Robert Smygel and friends.

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I'm Tab Ramos. I'm Tom Boke. On our podcast, Inside American Soccer, you'll get the real storyline. the biggest decisions, and the truth about the U.S. national team. It wouldn't be a huge surprise if our team ends up in the quarterfinals or potentially a great run into the semifinals. Listen, Inside American Soccer with Tom Bogart and Tabramos on the IHeart Radio app, Apple Podcasts, wherever you get your podcast.

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