Warren Hatch
speaker
48 appearances
1 recordings
1 series
first heard Dec 2024
last heard Dec 2024
Warren Hatch’s voice in public audio — every appearance, attributed to the second.
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Appearances
What Daniel Kahneman calls the outside view to get a sense of,
what history can tell us what are the comparison classes out in the world where we can begin our forecasting where we can anchor ourselves most people will get anchored that's what happens so you want to anchor in the best possible place and then incrementally update from there so if you're thinking about schools and what the career trajectories are
You'd want to go and take a look at all the data for comparable schools and see what the history of graduation rates and the like have been, and then go narrower and narrower into what Kahneman calls the inside view to make the decision itself.
That's actually step one is defined. Another word for that is base rate. How do things like this usually go? And by going to a base rate or outside view, that was basically synonyms, you'll get an immediate boost just by doing that compared to the rest of the crowd.
Another good one for anyone to have on their checklist is to make a comment. When you've come up with an estimate about the future, jot down your rationale. One reason for that is it crystallizes your thinking. It also allows you to, in the future, look back and say, was I right for the right reasons or did I miss something? And it also allows you to share information with others.
And that's how you get a high quality forecast from a crowd. Most wisdom of the crowd approaches. You ask everybody. Then you take an average and you're done. That's where we start.
And what we'd like to do is have everyone make a comment and then exchange those ideas and see if somebody had a point that maybe I missed and then make an update, which is the next very crucial thing is expect to change your view, make an update. And you just do those few things. You're going to end up with a better number. Start with a base rate, make a comment, exchange views, update.
One area where we learned a lot was during the pandemic. We were talking about experts earlier. And one thing about experts as well as artificial intelligence is they have models. That's the way they work. And if you have a model, then you're using backward-looking data to build your model. And that works great when we're in moments of relative equilibrium.
But when things get upended and there is a lot of flux, those models don't work so well. And almost by definition, the experts are going to be slower to recognize that because their models will be filtering out the subtle changes that are eroding their models. And an excellent example of that was when COVID began to go global.
And many of the experts with their models were downplaying the significant, not all of them, but many of them. I think even most of them were saying that this thing will be contained. And instead, of course, it became something much more significant.
Our forecasters who were not bound by a particular model and were skilled at identifying these subtle shifts did much better at identifying how quickly the pandemic would spread They also did very well at identifying when a vaccine would become available. They saw it becoming available far sooner than the experts did.
And that, of course, getting those two pieces has enormous implications for public policy, for investing, and for personal life decisions. So for us, that was a really critical example where we could also contribute to the public discourse on an important issue of about how to think about applying this process in real world situations, especially when there's a lot of flux going on.
That's where this kind of a process can really shine is when things get upended, when there's more uncertainty than we recognized.
it's a process that can be useful in everyday decision-making, but I think where it really stands out relative to other ways of thinking about the world is when there is a lot of flux and maybe not so much dark black swans as very dark gray swans. Because some of these things may be small probability, but high impact.
And somehow getting those small probability items on your radar can help you be better prepared. And in the case of the pandemic, there were some people who were identifying that as a possibility, not something that they were attaching high probabilities to, but it was definitely on their radar. And I think identifying those kinds of dark gray swans
is part of a good, successful forecasting process. But once it hits, you're absolutely right. Now it's here. Now what do we do? Well, one thing we should do is discount how much reliance we have on the static models. We don't want to get rid of them completely, but the importance and the reliance we've previously had on them should be discounted.
And we should instead factor in more weight to probabilistic judgment from people who are recognizing the small subtle factors that will eventually lead to new models.
One is, yeah, another pandemic could be a dark gray swan, wildfires. has become such a thing where the frequency is much higher than it was. But where are they going to hit? That's the challenge. I think a lot of the AI developments can also fall into that category, what some of those risks might look like. And also possible global conflicts. One that we're looking at more is in Korea.
We started looking at this a couple of months ago because there have been some changes. There have been some changes to North Korea's doctrine. North Korea sent troops to fight on Russia's behalf around Kursk. These are, in the global scheme of things, small but significant. So we're paying much more attention to how events on the Korean Peninsula may unfold as a possible dark, gray swan.
And tariffs, there's an incoming administration with a wish list, and that's high on the wish list. So some sort of tariffs seems in the bag. But the more significant question, certainly for people who are asking us for our forecast, is where, on what categories of goods, which countries are some of them gonna get exempted, or will it be an across the board thing? Exactly what does that look like?
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