 Now, we've spoken about the availability heuristic, but there's another heuristic I really like called representativeness. Now, Denny Kahneman already introduced us to this character called Linda the bank teller. And Linda is described as very outgoing and bright as a student. She was really passionate about social justice issues and discrimination and she even participated in anti-nuclear demonstrations. Now, when you ask people, is Linda a bank teller or a feminist bank teller? People are way more likely to report that Linda is a feminist bank teller. Even though just thinking about the base rates and the probability, there are way more bank tellers than there are feminist bank tellers. So what the Linda example sets up is a kind of conflict between probability and base rates on one hand, what is actually true versus representativeness on the other. And so those two things conflict and representativeness wins. So the description of Linda being so representative of a feminist sort of pushes the probability down and we're more likely to respond that Linda is a feminist bank teller. And this works not only for kind of toy scenarios like the Linda problem, but it's kind of, it's broader than that. And so it's kind of more general in terms of category learning. And so if you think, for example, about fruit. So when I say fruit, what's the first thing kind of that comes to mind? It's probably an apple or an orange or something, not a tomato or, you know, pumpkin, right? Which are also fruits, but they're probably not the first thing you'd think of. You do the same thing with, I don't know, a grocery store clerk, right? We have these ideas about the way that things are supposed to work. And when you walk into a grocery store, for example, you have an idea about who works there and who doesn't, right? And I've made this mistake in the past, you know, I've walked into a grocery store and I asked somebody where the lime juice was, you know, those little containers of lime juice. So I walk in, where's this, where does this belong? And the guy says, I don't actually work here. But he had a clipboard, right? That's what gets me. The guy had a clipboard, who walks around, you know, the grocery store with a clipboard. But, you know, he doesn't have, he didn't fit, he totally fit the mold of somebody who worked in the store because he had a clipboard and he was walking or he even had a tie, right? So I was confused. But for the most part, I mean that kind of example demonstrates that for the most part it gets us by. When I walk into a store, I can always tell who works there 99% of the time. And so this idea of representativeness, of relying on prototypes, gets us by most of the time. But we can kind of create these sort of scenarios where we don't operate, you know, with 100% accuracy. And so Danny Kahneman and Amos Tversky had to create this sort of Linda problem, so she really fit the mold of a feminist bank teller to kind of trick people in a sense to fall into this sort of mistake. And what we're going to do now is present another example, one from, again, Danny Kahneman and Amos Tversky that they came up with, where we talk about Rudy, who's in a similar sort of vein as the Linda, the famous feminist bank teller. So let's see if people still make the same sort of error when it comes to Rudy.