WEBVTT - Tetlock: discerning between good experts and bad experts

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<v Speaker 1>This is Bloomberg Surveillance. I think there are some signs,

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<v Speaker 1>some early signs that manufacturing is rebounding, including in the US.

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<v Speaker 1>An investment outlook beyond three or four years, to me

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<v Speaker 1>is more barry, like a religion or a philosophy than

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<v Speaker 1>a forecast. This economy is just stuck there. Used to

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<v Speaker 1>be stuck above two percent. Now it seems to be

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<v Speaker 1>stuck in this one and three quarters to till in

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<v Speaker 1>a quarter type growth, right. Bloomberg Surveillance your link to

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<v Speaker 1>the world of economics, finance, and investment on Bloomberg Radio.

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<v Speaker 1>Good morning everyone, Michael McKee and Tom Keane Bloomberg Surveillance

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<v Speaker 1>barrier rid holds in for Mr McKee today. Maybe we'll

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<v Speaker 1>get them tomorrow as well and under Friday. It would

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<v Speaker 1>be an exciting week of very rid holes here if

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<v Speaker 1>we can, you know, because people people in that uh

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<v Speaker 1>Marcus on the move. Futures up, eleven down, futures up.

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<v Speaker 1>N Bloomberg Surveillance This morning brought you by co Resnick

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<v Speaker 1>Accounting Tax Advisory. To keep your business on top of

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<v Speaker 1>issues in the evolving renewable energy market, it takes dedicated

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<v Speaker 1>industry experts like Cone Resnick find out more at cone

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<v Speaker 1>Resnick dot com, CEO H N R. E Z and

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<v Speaker 1>I C. K. Cone Resnick uh dot com. Um, this

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<v Speaker 1>is gonna be an important discussion. We do economics, finance, investment,

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<v Speaker 1>and international relations, and what we really do in the

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<v Speaker 1>word that we use is insight. Unfortunately, there is the

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<v Speaker 1>illusion or I would even say the delusion of insight,

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<v Speaker 1>and that you've got to be careful and how you

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<v Speaker 1>interpret the insight. This, of course from the Daniel kahnman

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<v Speaker 1>Uh in his iconic work common in divers Key out

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<v Speaker 1>of Princeton with Warten Philip Tetlock, Edinburgh Professor on Democracy

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<v Speaker 1>and Citizenship, and particularly Philip Tetlock on how we communicate

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<v Speaker 1>in this digital overloaded world professor, good morning, good morning.

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<v Speaker 1>Tell me about the illusion of insight. We think we're

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<v Speaker 1>getting smarter listening to Bloomberg surveillance. Are we fooling ourselves? Well,

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<v Speaker 1>you know, it's really hard to tell whether someone knows

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<v Speaker 1>what they're talking about, So we use proxies. We say, well,

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<v Speaker 1>does this person have high status? We say, is this

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<v Speaker 1>person entertaining this personal equacious? Uh? There are a lot

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<v Speaker 1>of proxy queues, but typically I think, what what your

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<v Speaker 1>listeners care about the most is whether they have some

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<v Speaker 1>insights into the future and that could guide their decisions,

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<v Speaker 1>their business decisions. Uh. And the only way to ascertain

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<v Speaker 1>that is to keep rigorous score. And that is something

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<v Speaker 1>very two places do. We do it internally at Bloomberg.

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<v Speaker 1>It was invented by myself and Emily has God Soul

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<v Speaker 1>and Rachel Worstspan does it every day now in the

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<v Speaker 1>basic idea for us is to work off the classic

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<v Speaker 1>research of Edelman, Richard Edelman and the people there that

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<v Speaker 1>look at expert oology in good experts in bad experts.

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<v Speaker 1>We are drowning in that distinction right now in our

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<v Speaker 1>political debate and some would say in our business media debate.

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<v Speaker 1>How do you, as the pro discern between good experts

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<v Speaker 1>and bad experts? Well, the work I've been doing with

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<v Speaker 1>US intelligence community over the last several years involves um

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<v Speaker 1>having people participate in forecasting tournaments and asking them very

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<v Speaker 1>large numbers of questions over large spans of time, and

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<v Speaker 1>keeping rigorous score. One of the big mistakes people make

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<v Speaker 1>is they conclude that someone is a bad forecaster if

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<v Speaker 1>they make one bad call, if they're on the wrong

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<v Speaker 1>side of maybe on a big call Uh. And even

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<v Speaker 1>the very best forecasters are, of course, often on the

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<v Speaker 1>wrong side of maybe, so you need to keep it good.

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<v Speaker 1>Judgment is an aggregate thing and recuse a lot of patients. Uh.

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<v Speaker 1>And that doesn't lend itself to most media formats. So,

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<v Speaker 1>Professor I learned from your earlier work on on expert

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<v Speaker 1>political judgment that the average so called expert isn't an

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<v Speaker 1>especially good forecaster. And then you updated that work in

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<v Speaker 1>your most recent book, Super Forecasters, where you said, there

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<v Speaker 1>are some basic things all forecasters can do to become

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<v Speaker 1>better smarter prognosticators. Give us a few examples of what

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<v Speaker 1>those of us who toil in the markets and the

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<v Speaker 1>economy can do to think more intelligently about the future. Well,

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<v Speaker 1>I think you had. You had an interesting quote from

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<v Speaker 1>somebody at the very beginning of this piece in which

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<v Speaker 1>somebody he was saying that an investment, uh, with whose

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<v Speaker 1>claims they can see out four or five years, that's

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<v Speaker 1>essentially philosophy, it's not forecasting. And that's more or less

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<v Speaker 1>what my earlier work found. It was very, very hard

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<v Speaker 1>for even the very smartest people to do appreciably better

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<v Speaker 1>than chance. When you're looking at that farm, it is

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<v Speaker 1>possible though, for smart people who get a lot of

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<v Speaker 1>practice at it to make better probability judgments in the

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<v Speaker 1>several months range. Okay, we've got a bad connection right

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<v Speaker 1>now with Professor Tetlock. We're gonna reconnect. Ken Felio, who's

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<v Speaker 1>so good at this, is going to try to reconnect

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<v Speaker 1>and get a better signal. Barry, I think we need

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<v Speaker 1>to say without question that the way to get smarter

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<v Speaker 1>and this is a tough business, folks, It's not easy.

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<v Speaker 1>I mentioned Daniel Kaneman and Connon and Traversky, which changed

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<v Speaker 1>how all of us think day to day about behavioral

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<v Speaker 1>finance and how wrong we are in what we trust

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<v Speaker 1>and what we guess at. The modern book is Thinking

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<v Speaker 1>Fast and Slow by Professor kenn Yeah. I discussed that

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<v Speaker 1>with Professor Tetlock. He was our guest on Masters in

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<v Speaker 1>Business last weekend, and he told the story of having

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<v Speaker 1>met uh Danny Kahneman and discussing how when he began

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<v Speaker 1>to quantify experts, he really wasn't impressed with what he saw,

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<v Speaker 1>and Conman, just off the cuff said, I would imagine

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<v Speaker 1>the average expert is no better than a well read

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<v Speaker 1>New York Times person, and he turned out to be

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<v Speaker 1>right as we as we try to get Professor on

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<v Speaker 1>very one of the things that one of my gospel things.

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<v Speaker 1>And we do this folks every day in surveillance. And

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<v Speaker 1>thank you so much for your support. I love when

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<v Speaker 1>experts are wrong. I learned more from somebody's smart I

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<v Speaker 1>learned more from So well, let's bring professor lock back.

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<v Speaker 1>We're talking to your professor. Thank you for coming back

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<v Speaker 1>with us about the idea of somebody that I believe

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<v Speaker 1>is a good guest, a good expert. I learn more

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<v Speaker 1>when they're wrong than when they're right. Discussed that research. Oh,

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<v Speaker 1>I think there's a deep truth to that. Uh. Very

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<v Speaker 1>concrete example would be some of the controversy that surrounded

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<v Speaker 1>Nate Silver, who had, of course a great reputation from

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<v Speaker 1>some of the previous presidential and congressional races, and he

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<v Speaker 1>made he made the comment in the late summer of

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<v Speaker 1>that he thought the number of people who would take

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<v Speaker 1>Donald Trump's candidacy seriously would be roughly comparable to the

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<v Speaker 1>number of people who thought the moon landings were faked. Um,

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<v Speaker 1>so you put the probability somewhere between zero and five percent,

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<v Speaker 1>I believe, and a lot a lot of people would

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<v Speaker 1>jump jumped on d silver for that UM. Now, even

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<v Speaker 1>a perfectly calibrated forecaster, and I'll say in a minute,

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<v Speaker 1>what a perfectly calibrated forecaster is. Even a perfectly calibrated

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<v Speaker 1>forecaster is going to be wrong five percent of that

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<v Speaker 1>UH is going to be wrong at least five percent

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<v Speaker 1>of the time when when they when they say five

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<v Speaker 1>percent UM. So it's a it's a difficult thing for

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<v Speaker 1>people to appreciate. But you you can't judge the accuracy

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<v Speaker 1>of probability judgments based on the individual forecast. You can

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<v Speaker 1>only do that if the forecaster is really reckless and

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<v Speaker 1>says hudd percent and it doesn't happen, or zero percent

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<v Speaker 1>and it does. And in that case, you know the

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<v Speaker 1>forecast a slat out wrong and forli forecast is taking

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<v Speaker 1>a big reputational risk and it is lost um. But

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<v Speaker 1>in the other cases, it's going to require some more nuance.

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<v Speaker 1>And that's that's the tricky thing that people have our

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<v Speaker 1>time wrapping their heads around. So so what should those

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<v Speaker 1>of us who who think about the economy, you think

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<v Speaker 1>about markets, and are occasionally called upon to make a

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<v Speaker 1>prediction out six months or a year, what should we

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<v Speaker 1>do to improve that process to become better forecasters. I

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<v Speaker 1>think you want people to feel accountable. Uh. So insofar

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<v Speaker 1>as the people who come on a shows use vague verbue,

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<v Speaker 1>make vague verbuge forecast and they think that they say,

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<v Speaker 1>I think there's a distinct possibility the market's going to

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<v Speaker 1>go over Bible blup. Uh. People may who make those

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<v Speaker 1>kinds of claims they sound meaningful, but in close inspection

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<v Speaker 1>they're very close to meaning less because distinct possibility is

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<v Speaker 1>one of those things you can you can you've got

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<v Speaker 1>a perfect hedge. If it happens, you can say, hey,

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<v Speaker 1>I told you distinct possibility. If it doesn't happen, you

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<v Speaker 1>can say, hey, I just said it was possible. So

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<v Speaker 1>it sounds meaningful. Uh. People not They think they've learned something,

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<v Speaker 1>but on close inspection, there's absolutely no way to monitor

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<v Speaker 1>keep track. So a better way to go is to

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<v Speaker 1>pressure people to make more precise estimates. Even though it hurts,

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<v Speaker 1>it's hard, it's potentially embarrassing, but best it's the best

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<v Speaker 1>way to learn. Beware weasel words. Speaking speaking of potentially embarrassing,

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<v Speaker 1>let's come back and talk to the professor about our

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<v Speaker 1>presidential derby. It has been sports Philip tet Luck with

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<v Speaker 1>this Anneburg professor university professor in Democracy and Citizenship at Wharton,

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<v Speaker 1>And uh, somebody has written some very important books on

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<v Speaker 1>thinking about really what do we do about certitude? And

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<v Speaker 1>is Mark Mark Twain. John Tucker was one of our

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<v Speaker 1>first guests and Bloombergunny Economy. It was a few years.

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<v Speaker 1>It was a book tour. I was like, it wasn't

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<v Speaker 1>Huncle Berry Finn, it was something else. But as Mr

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<v Speaker 1>Twain would say, the certitude of the second rate, maybe

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<v Speaker 1>that's a gospel of surveillance. As we listen with respected

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<v Speaker 1>Professor Tetlock, will return with Philip Tetlock, and uh look

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<v Speaker 1>forward to um. Some of the political certitude that is

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<v Speaker 1>out there very reminds me of the rule of thirty

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<v Speaker 1>which is abused every single day. We take a sample

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<v Speaker 1>size of four and say we believe, and uh, it

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<v Speaker 1>really doesn't work all that well. Futures up eleven down,

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<v Speaker 1>features up one oh one. Janet Yellen still influence, influencing

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<v Speaker 1>the market with yields set lower from twelve noon yesterday,

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<v Speaker 1>Oil thirty eight seventy seven the American barrel And now

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<v Speaker 1>to the news in New York. Here's Michael Barr, Tom Berry,

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<v Speaker 1>thank you very much. The US is trying to give

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<v Speaker 1>support to allies in Eastern Europe who are increasingly concerned

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<v Speaker 1>about a more aggressive Russia. The Army plans to announce

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<v Speaker 1>today the deployment of an armored combat brigade along with

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<v Speaker 1>their equipment, to Eastern Europe next February, as part of

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<v Speaker 1>the ongoing effort to rotate troops in and out of

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<v Speaker 1>the region. The three Republican presidential candidates now saying they

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<v Speaker 1>won't commit to support whoever the party nominates in September,

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<v Speaker 1>Donald Trump, Ted Crews and John Kasi said they would

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<v Speaker 1>pledge their support. A federal judge in Oakland, California, has

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<v Speaker 1>scheduled to hear arguments today over whether to block a

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<v Speaker 1>new federal law that requires sex offenders to have unique

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<v Speaker 1>identifiers in their passports. Global News twenty four hours a day,

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<v Speaker 1>powered by our twenty four hundred journalists more than one

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<v Speaker 1>hundred fifty news bureaus from around the world. I am

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<v Speaker 1>Michael Barr, Tom and Michael, thanks so much again. I

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<v Speaker 1>remove the market. Finally, the bond market pauses, but the

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<v Speaker 1>two year yield point seven eight four three Genet yell

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<v Speaker 1>and are really moving uh markets yields lower, bond prices

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<v Speaker 1>higher over the last eighteen hours. They rid Alds Toime

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<v Speaker 1>Keene with Philip Block of Wharton Bloomberg Surveillance, Surveillance MUTI

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<v Speaker 1>by n y c B asking about their my community

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<v Speaker 1>interest checking but free n y c B online and

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<v Speaker 1>mobile banking. Earn more, get more. Visit n y CP

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<v Speaker 1>family dot com for details. Global business news twenty four

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<v Speaker 1>hours a day at Bloomberg dot com, the Radio plus

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<v Speaker 1>Mobile Act and on your radio, this is a Bloomberg

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<v Speaker 1>Business Flash. And I'm Karen Moscow roiking economic news. Crossing

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<v Speaker 1>the Bloomberg. Here's at Vinny down Judas with the latest

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<v Speaker 1>Vinny ran on the Labor Park labor market. The ADP

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<v Speaker 1>National Employment Report showing a gain of two hundred thousand,

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<v Speaker 1>and March again at two hundred thousand, topping Wall Street forecast.

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<v Speaker 1>That sets the stage for Friday's government employment report. Economists

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<v Speaker 1>they're also looking for in the neighborhood at two hundred thousand.

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<v Speaker 1>Again the a P report Private payrolls march up two

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<v Speaker 1>hundred thousand. Karen, back to you, all right, thank you,

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<v Speaker 1>Vinnie del Judas. Let's go to the first word Breaking

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<v Speaker 1>News Desk Now for today's morning call, and here's Bill Maloney.

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<v Speaker 1>Good morning, Bill, Good morning Karen. Futures are adding to

0:13:11.760 --> 0:13:14.800
<v Speaker 1>yesterday's gains. Doubt youre just currently hired by a hundred

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<v Speaker 1>one point says he's gain eleven and as a futures

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<v Speaker 1>rise by thirty two. The U S tenual at one

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<v Speaker 1>point eight three per cent. Up of markets are also rising,

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<v Speaker 1>led by one point nine percent gains in France after

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<v Speaker 1>develops Night Restoration Hardware Queen at JESSEPS and revenue trailed

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<v Speaker 1>estimates and very que for jesse EPs missed estimates Shares

0:13:35.600 --> 0:13:39.360
<v Speaker 1>a down fourteen percent pre market regarding earnings this morning.

0:13:39.400 --> 0:13:42.000
<v Speaker 1>Lul Lemon Hire by five point seven percent pre market

0:13:42.080 --> 0:13:46.680
<v Speaker 1>after its results, while Paychecks EPs was in line until

0:13:46.760 --> 0:13:49.280
<v Speaker 1>New Stage Street degrees to buy g e St Management

0:13:49.320 --> 0:13:52.040
<v Speaker 1>for up to four hundred eighty five million in cash.

0:13:52.600 --> 0:13:56.560
<v Speaker 1>Also another news, Valiant launches credit line amendment repeats following

0:13:56.600 --> 0:14:00.960
<v Speaker 1>plans and says comfortable with current liquidity position in family

0:14:01.000 --> 0:14:04.080
<v Speaker 1>some of your wallsheet upgrades and downgrades. Compass Meneral cut

0:14:04.080 --> 0:14:06.720
<v Speaker 1>the hold at BB and T, Apple raised out performer

0:14:06.800 --> 0:14:10.160
<v Speaker 1>cown price target one thirty five Varian Systems cut down

0:14:10.240 --> 0:14:12.439
<v Speaker 1>perform at Credit Suite, A I G raised to buy

0:14:12.440 --> 0:14:15.960
<v Speaker 1>a Janny and all scripts raised overweight over at Morgan

0:14:16.120 --> 0:14:19.200
<v Speaker 1>Stanley Live in the First Breaking News Desk on Bill Maloney.

0:14:19.280 --> 0:14:22.000
<v Speaker 1>Karen thanks Bill to hear live breaking news over your

0:14:22.000 --> 0:14:24.960
<v Speaker 1>Bloomberg type squawk go on your terminal. Let's ask you

0:14:25.040 --> 0:14:27.800
<v Speaker 1>you a w K go and that's a Bloomberg business flash.

0:14:27.840 --> 0:14:31.000
<v Speaker 1>Tom and Barry un thanks so much. Appreciate that. This

0:14:31.080 --> 0:14:35.280
<v Speaker 1>morning Bloomberg Surveillance Bunch by Investco. Do the day's headlines

0:14:35.320 --> 0:14:39.200
<v Speaker 1>have you searching for more investment views? Investco's experts can

0:14:39.240 --> 0:14:42.440
<v Speaker 1>help find out the latest thought leadership and Investco blog.

0:14:42.920 --> 0:14:46.960
<v Speaker 1>Visit investco dot com slash us to subscribe. At a

0:14:46.960 --> 0:14:51.360
<v Speaker 1>wonderful time with Investco yesterday, learned a lot about value

0:14:51.520 --> 0:14:55.320
<v Speaker 1>dividends and this this interesting phrase deep value from Keith

0:14:55.360 --> 0:14:59.160
<v Speaker 1>Holding the Value team UH at Investo and thank them

0:14:59.240 --> 0:15:03.000
<v Speaker 1>for their UH continued support of Bloomberg's surveillance and what

0:15:03.040 --> 0:15:07.040
<v Speaker 1>Michael and I do every day. Very results with us, Phillips,

0:15:07.240 --> 0:15:09.920
<v Speaker 1>luck with us who long ago and far away not

0:15:10.120 --> 0:15:13.840
<v Speaker 1>fifty two years ago? Read the medium is the message

0:15:14.440 --> 0:15:18.360
<v Speaker 1>understanding media the extensions of Van Marshall McLuhan. Have we

0:15:18.480 --> 0:15:21.520
<v Speaker 1>jumped to shark Professor Tutlock? Are we are we at

0:15:21.520 --> 0:15:23.960
<v Speaker 1>the point where the medium is the message and it

0:15:24.200 --> 0:15:32.320
<v Speaker 1>completely reforms and restructures our presidential politics day to day? Well, Uh,

0:15:32.680 --> 0:15:37.400
<v Speaker 1>that's a that's a big question. Um. So the conventional

0:15:37.400 --> 0:15:41.640
<v Speaker 1>wisdom's obviously been really rattled by the Donald Trump phenomenon.

0:15:41.960 --> 0:15:46.720
<v Speaker 1>I guess that's what you're probably referring to. Um. Yeah,

0:15:46.800 --> 0:15:50.040
<v Speaker 1>I thinks things have changed a lot. Uh. Trump was

0:15:50.080 --> 0:15:53.280
<v Speaker 1>able to tap into deep resentment. He was able to

0:15:53.320 --> 0:15:58.120
<v Speaker 1>get away with really pretty primitive debating tactics and wasn't

0:15:58.280 --> 0:16:02.960
<v Speaker 1>punished for them. U. Um. Donald Trump's style of debating

0:16:03.080 --> 0:16:05.800
<v Speaker 1>is pretty much the opposite end of the continuum from

0:16:05.800 --> 0:16:10.360
<v Speaker 1>the style of debating we try to encourage and forecasting tournaments, uh,

0:16:10.440 --> 0:16:15.320
<v Speaker 1>which value precision questioning and precision estimates. And who's that

0:16:16.280 --> 0:16:21.360
<v Speaker 1>you different universe? Who is the adult in the room

0:16:21.720 --> 0:16:27.360
<v Speaker 1>that's going to get us back to a better discourse? Um?

0:16:27.520 --> 0:16:31.520
<v Speaker 1>Who is he? Adntal boy boy? You asked tough questions, Tom.

0:16:34.880 --> 0:16:37.360
<v Speaker 1>People in the GOP are pointing to Paul Ryan and

0:16:37.480 --> 0:16:41.280
<v Speaker 1>John Kass as the presumptive adults in the room. Uh,

0:16:41.360 --> 0:16:44.920
<v Speaker 1>in in in that political party right now? Well, clearly

0:16:45.040 --> 0:16:48.000
<v Speaker 1>John kask at least on the debate stage, had has

0:16:48.040 --> 0:16:52.840
<v Speaker 1>appeared like the adults. The problem is he's been rewarded

0:16:53.360 --> 0:16:57.000
<v Speaker 1>for that with a third place finish everywhere outside his

0:16:57.040 --> 0:17:01.600
<v Speaker 1>home state. Are we looking of politics? Are we looking

0:17:01.600 --> 0:17:06.600
<v Speaker 1>in the wrong place for adult discussions about important issues?

0:17:09.119 --> 0:17:13.159
<v Speaker 1>Probably perhaps so at the moment um. But when you

0:17:13.200 --> 0:17:17.960
<v Speaker 1>look at the bigger picture, are the best forecasters, for example,

0:17:18.080 --> 0:17:21.440
<v Speaker 1>in our tournaments are putting close to a seventy percent probability?

0:17:21.480 --> 0:17:24.159
<v Speaker 1>Now and Hillary being the next president of the United States,

0:17:24.720 --> 0:17:28.040
<v Speaker 1>so once she's sworn in, this will look this will

0:17:28.080 --> 0:17:31.000
<v Speaker 1>be a distant memory. Uh, And the question will be

0:17:31.480 --> 0:17:34.720
<v Speaker 1>what have what? What has the Republican Party in particular

0:17:34.960 --> 0:17:40.280
<v Speaker 1>learned from its experience? Um? Now, of course, uh, the

0:17:40.400 --> 0:17:44.080
<v Speaker 1>very best forecasters, like Nate Silver was was was somewhat

0:17:44.080 --> 0:17:46.119
<v Speaker 1>off the mark early on, and then the and and

0:17:46.160 --> 0:17:48.879
<v Speaker 1>the best forecasters in our tournament maybe off the mark. Also,

0:17:49.240 --> 0:17:52.120
<v Speaker 1>when you say seventy percent probability, that means the percent

0:17:52.160 --> 0:17:55.640
<v Speaker 1>probability of other things. Uh. So let's talk about that

0:17:55.720 --> 0:17:59.439
<v Speaker 1>with more important issues than politics. What I what I

0:17:59.480 --> 0:18:03.720
<v Speaker 1>find fast sitting about your work is how the intelligence

0:18:03.920 --> 0:18:07.520
<v Speaker 1>community has sort of thrown aside their old way of

0:18:07.560 --> 0:18:10.560
<v Speaker 1>doing things and approached you to say, we need better

0:18:10.600 --> 0:18:14.680
<v Speaker 1>ways to think about uncertain events. So let's talk about that.

0:18:15.280 --> 0:18:19.040
<v Speaker 1>What is the intelligence community learning from the mistakes that

0:18:19.119 --> 0:18:22.960
<v Speaker 1>have been made in the past. Well, the intelligence community

0:18:23.960 --> 0:18:27.560
<v Speaker 1>works at ground zero in the blame game political culture.

0:18:28.000 --> 0:18:31.480
<v Speaker 1>So if they make a wrong call, they're gonna get

0:18:31.680 --> 0:18:34.200
<v Speaker 1>They're gonna get blasted one way or the other. And

0:18:34.400 --> 0:18:36.960
<v Speaker 1>the wrong calls can take one of two forms. They

0:18:37.000 --> 0:18:42.040
<v Speaker 1>can have a catastrophic um false negative such as nine

0:18:42.119 --> 0:18:46.600
<v Speaker 1>eleven UH, They'll be totally condemned. They'll be roundly condemned

0:18:46.640 --> 0:18:49.879
<v Speaker 1>for it. There'll be presidential commission, will be congressional investigations.

0:18:50.040 --> 0:18:54.119
<v Speaker 1>And the one lesson that an intell intelligence intelligence officer

0:18:54.160 --> 0:18:56.680
<v Speaker 1>would learn from that experiences whatever mistake I'm going to make,

0:18:56.720 --> 0:19:00.200
<v Speaker 1>don't make the mistake I just made, which means don't

0:19:00.240 --> 0:19:03.000
<v Speaker 1>make a false negative. That sets you up for making

0:19:03.000 --> 0:19:05.359
<v Speaker 1>the opposite mistake a false positive. Now, they made a

0:19:05.359 --> 0:19:10.360
<v Speaker 1>false positive mistake with weapons of mass destruction in Iraq. Uh.

0:19:10.480 --> 0:19:13.639
<v Speaker 1>They got blasted for that, and there are investigations and

0:19:13.720 --> 0:19:18.520
<v Speaker 1>commissions and what does an intelligent, intelligent officer intelligence officer

0:19:18.640 --> 0:19:21.560
<v Speaker 1>conclude from all that, Well, whatever mistake I'm gonna make,

0:19:21.600 --> 0:19:23.840
<v Speaker 1>don't make the mistake I made last. So they get

0:19:23.840 --> 0:19:27.520
<v Speaker 1>caught up in this kind of blame game ping pong um,

0:19:27.600 --> 0:19:30.920
<v Speaker 1>which is not really learning. It's it's threshold shifting. It's

0:19:30.960 --> 0:19:33.960
<v Speaker 1>it's shifting my tolerance from making one mistake or other

0:19:34.200 --> 0:19:36.440
<v Speaker 1>rather than learning in a deep and a methodical way

0:19:36.520 --> 0:19:38.600
<v Speaker 1>from history. The way to learn in a deep and

0:19:38.640 --> 0:19:42.280
<v Speaker 1>methodical way from history is to make explicit judgments the

0:19:42.359 --> 0:19:45.840
<v Speaker 1>domains in which are well calibrated not and proceed that way.

0:19:46.119 --> 0:19:48.399
<v Speaker 1>And professor, thank you so much for being us with

0:19:48.480 --> 0:19:52.119
<v Speaker 1>us today. Phil Tetlock is from Warton super Forecasters is

0:19:52.240 --> 0:19:56.480
<v Speaker 1>a hugely successful book on the experts. We really appreciate

0:19:56.520 --> 0:19:59.200
<v Speaker 1>his perspective as we try to find you the best

0:19:59.359 --> 0:20:06.639
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