 I think the availability heuristic is playing a really large role in people's decisions about whether to vaccinate or not, especially if you're from the developed world. So my impression about a disease such as measles is there's a red rash on my skin or I have dots over my body, but I think in Afghanistan over 50,000 people a year die from measles. But because I grew up in the developed world and vaccines have cured or eradicated many of these diseases, the deadliness of that disease just does not come to mind. It's not available for me to retrieve when thinking about these problems about whether to vaccinate or not. There's another thing that's going on as well, which we've discussed previously, which is the confirmation bias and one-sided events. So if you're vaccinating your child, that's something that you do. It's an act, it's an act of commission. And if something bad happens to your child after you vaccinate, that's your fault. That's something that you did. On the other hand, not vaccinating your child is doing nothing. It's an act of omission. And in general, people feel much more comfortable about something bad happening after doing nothing and something bad happening after doing something. Yeah, that's right. And I think availability is playing a massive part in this idea of immunization and vaccination. Another thing that we talked to Ian about during that interview was this idea of cancer clusters. Now, it's such a good topic from the perspective of this course because everything that we've been talking about here is operating in it. Everything that we've been discussing, heuristics, biases, everything. So let's take a couple of examples. There's one really salient example that we've seen right here in Brisbane at the Australian Broadcasting Corporation. This is a cancer cluster. What do we mean by that? Well, I think it started out there were about six or eight women who were diagnosed with breast cancer who worked at the ABC. The number just kept growing. So it went from six to eight to 10 to 12. I think in the end, they counted about 15 women who were diagnosed with cancer. And they pinpointed it to a single desk at the ABC where each of the women were working or maybe night shift, right? There were a bunch of things that were operating that they were trying to isolate what it was. And so they started looking at, well, they walked off the job, first of all. And they said, this is it. I'm not going to be part of this anymore. They walked out and they came back and they worked for a little longer. They said, we want out of this building. This is a death trap and on and on. I mean, there was a lot of media around it, partly because they are the media, which is availability. That's operating as well. And then this idea of availability cascade that Kahneman talks about, that was operating. Also looking for a common cause, which we've talked about a fair bit. But so we have 15 women who've been diagnosed. And imagine it from their perspective. You couldn't help in the interview that we talked with Kahneman about. Tom Gilovich. Tom Gilovich, that's right. He mentioned the case with Carl Sagan. If I had a dream about my grandfather dying, wake up the next morning, you would never convince him that it was a dream, right? And then the same thing is operating here. You see these two things, this cluster that's operating. This diagnosis, the salient event, this very personal event that you have. And all of the other people around you're finding a pattern that may or may not exist. But we also have 15 women who've been diagnosed. Is that a lot? I mean, this is 15 women compared to what? How many people to work at the ABC? Is it 20? That would be an enormous number, right? Is it 200 or 2000 or 20,000? Well, it depends. What do we mean by how many people have set foot in the building? Is that a fair comparison? Are we taking full-time workers, part-time contractors, construction workers? How many people do we consider in that equation? For how long? Do we go back a week? Do we go back five years? 50 years? So where you draw the circle around, what do you compare those 15 women to when you draw that circle? Exactly. So who are we comparing the 15 women to? And that's what they did in the epidemiological reports when they did the analysis to see if something fishy was going on at ABC studios. These are the sort of equations that they were doing. But I mean, another problem is what we talked about with the birthday problem. Is it odd? Is it weird to have a workplace with 15 women who have the same diagnosis? Well, it is weird in a sense, but it's not weird with respect to any workplace in the entire country. It would be weird not to have a cluster, a lump. Chance is lumpy. It would be very strange not to have a group of 15 women in any workplace across Australia with the same diagnosis. And so you need to do interesting things like look at the nature of the tissue, the breast tissue, to see if there's a common cause. And in fact, there wasn't. It turns out that it was probably due to chance. It was probably due to something other than an official cluster, if you will. So an illusory correlation. An illusory correlation, that's right. But I mean, think about it with respect to opinion change, as we talked about as well. Imagine having a diagnosis like that and seeing your colleagues work right beside you, also having the same diagnosis. You're not going to be convinced that it's just coincidence, that it's chance. And trying to convince them otherwise would almost, I couldn't be convinced. There's no way. And so when you're presented with formal data, how do you treat this information? It's a very tricky sort of scenario. And I think, I mean, as we said, there's a lot of things that are operating here. And I hope people will apply everything that we've been learning about. See how all of these heuristics and biases are operating here. Because they are, to this health claim and others that we're dealing with, that we haven't had a chance to talk about in this episode. Yep. So we've dealt with health claims this week. Last week, we dealt with extraordinary claims. And next week, we're going to deal with applied claims. So we're going to tackle some pretty big issues. One of them is belief in climate change. And another one is some of our work, actually, on fingerprints and DNA and forensic science in the courtroom.