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Speaker 1: This is Bloomberg Surveillance. I think there are some signs,

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Speaker 1: some early signs that manufacturing is rebounding, including in the US.

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Speaker 1: An investment outlook beyond three or four years, to me

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Speaker 1: is more barry, like a religion or a philosophy than

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Speaker 1: a forecast. This economy is just stuck there. Used to

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Speaker 1: be stuck above two percent. Now it seems to be

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Speaker 1: stuck in this one and three quarters to till in

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Speaker 1: a quarter type growth, right. Bloomberg Surveillance your link to

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Speaker 1: the world of economics, finance, and investment on Bloomberg Radio.

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Speaker 1: Good morning everyone, Michael McKee and Tom Keane Bloomberg Surveillance

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Speaker 1: barrier rid holds in for Mr McKee today. Maybe we'll

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Speaker 1: get them tomorrow as well and under Friday. It would

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Speaker 1: be an exciting week of very rid holes here if

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Speaker 1: we can, you know, because people people in that uh

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Speaker 1: Marcus on the move. Futures up, eleven down, futures up.

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Speaker 1: N Bloomberg Surveillance This morning brought you by co Resnick

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Speaker 1: Accounting Tax Advisory. To keep your business on top of

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Speaker 1: issues in the evolving renewable energy market, it takes dedicated

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Speaker 1: industry experts like Cone Resnick find out more at cone

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Speaker 1: Resnick dot com, CEO H N R. E Z and

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Speaker 1: I C. K. Cone Resnick uh dot com. Um, this

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Speaker 1: is gonna be an important discussion. We do economics, finance, investment,

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Speaker 1: and international relations, and what we really do in the

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Speaker 1: word that we use is insight. Unfortunately, there is the

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Speaker 1: illusion or I would even say the delusion of insight,

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Speaker 1: and that you've got to be careful and how you

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Speaker 1: interpret the insight. This, of course from the Daniel kahnman

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Speaker 1: Uh in his iconic work common in divers Key out

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Speaker 1: of Princeton with Warten Philip Tetlock, Edinburgh Professor on Democracy

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Speaker 1: and Citizenship, and particularly Philip Tetlock on how we communicate

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Speaker 1: in this digital overloaded world professor, good morning, good morning.

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Speaker 1: Tell me about the illusion of insight. We think we're

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

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Speaker 1: you know, it's really hard to tell whether someone knows

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

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Speaker 1: does this person have high status? We say, is this

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Speaker 1: person entertaining this personal equacious? Uh? There are a lot

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Speaker 1: of proxy queues, but typically I think, what what your

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Speaker 1: listeners care about the most is whether they have some

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Speaker 1: insights into the future and that could guide their decisions,

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Speaker 1: their business decisions. Uh. And the only way to ascertain

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Speaker 1: that is to keep rigorous score. And that is something

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Speaker 1: very two places do. We do it internally at Bloomberg.

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Speaker 1: It was invented by myself and Emily has God Soul

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Speaker 1: and Rachel Worstspan does it every day now in the

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Speaker 1: basic idea for us is to work off the classic

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Speaker 1: research of Edelman, Richard Edelman and the people there that

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Speaker 1: look at expert oology in good experts in bad experts.

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Speaker 1: We are drowning in that distinction right now in our

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Speaker 1: political debate and some would say in our business media debate.

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Speaker 1: How do you, as the pro discern between good experts

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

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Speaker 1: US intelligence community over the last several years involves um

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Speaker 1: having people participate in forecasting tournaments and asking them very

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Speaker 1: large numbers of questions over large spans of time, and

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Speaker 1: keeping rigorous score. One of the big mistakes people make

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Speaker 1: is they conclude that someone is a bad forecaster if

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Speaker 1: they make one bad call, if they're on the wrong

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Speaker 1: side of maybe on a big call Uh. And even

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Speaker 1: the very best forecasters are, of course, often on the

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Speaker 1: wrong side of maybe, so you need to keep it good.

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Speaker 1: Judgment is an aggregate thing and recuse a lot of patients. Uh.

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

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Speaker 1: Professor I learned from your earlier work on on expert

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Speaker 1: political judgment that the average so called expert isn't an

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Speaker 1: especially good forecaster. And then you updated that work in

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Speaker 1: your most recent book, Super Forecasters, where you said, there

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Speaker 1: are some basic things all forecasters can do to become

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Speaker 1: better smarter prognosticators. Give us a few examples of what

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Speaker 1: those of us who toil in the markets and the

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Speaker 1: economy can do to think more intelligently about the future. Well,

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Speaker 1: I think you had. You had an interesting quote from

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Speaker 1: somebody at the very beginning of this piece in which

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Speaker 1: somebody he was saying that an investment, uh, with whose

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Speaker 1: claims they can see out four or five years, that's

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

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Speaker 1: what my earlier work found. It was very, very hard

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Speaker 1: for even the very smartest people to do appreciably better

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

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Speaker 1: possible though, for smart people who get a lot of

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Speaker 1: practice at it to make better probability judgments in the

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

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

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Speaker 1: so good at this, is going to try to reconnect

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Speaker 1: and get a better signal. Barry, I think we need

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Speaker 1: to say without question that the way to get smarter

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

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Speaker 1: I mentioned Daniel Kaneman and Connon and Traversky, which changed

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Speaker 1: how all of us think day to day about behavioral

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Speaker 1: finance and how wrong we are in what we trust

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Speaker 1: and what we guess at. The modern book is Thinking

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Speaker 1: Fast and Slow by Professor kenn Yeah. I discussed that

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Speaker 1: with Professor Tetlock. He was our guest on Masters in

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Speaker 1: Business last weekend, and he told the story of having

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Speaker 1: met uh Danny Kahneman and discussing how when he began

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Speaker 1: to quantify experts, he really wasn't impressed with what he saw,

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Speaker 1: and Conman, just off the cuff said, I would imagine

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Speaker 1: the average expert is no better than a well read

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Speaker 1: New York Times person, and he turned out to be

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Speaker 1: right as we as we try to get Professor on

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Speaker 1: very one of the things that one of my gospel things.

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Speaker 1: And we do this folks every day in surveillance. And

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Speaker 1: thank you so much for your support. I love when

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Speaker 1: experts are wrong. I learned more from somebody's smart I

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

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Speaker 1: We're talking to your professor. Thank you for coming back

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Speaker 1: with us about the idea of somebody that I believe

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Speaker 1: is a good guest, a good expert. I learn more

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Speaker 1: when they're wrong than when they're right. Discussed that research. Oh,

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Speaker 1: I think there's a deep truth to that. Uh. Very

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Speaker 1: concrete example would be some of the controversy that surrounded

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Speaker 1: Nate Silver, who had, of course a great reputation from

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Speaker 1: some of the previous presidential and congressional races, and he

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Speaker 1: made he made the comment in the late summer of

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Speaker 1: that he thought the number of people who would take

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Speaker 1: Donald Trump's candidacy seriously would be roughly comparable to the

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Speaker 1: number of people who thought the moon landings were faked. Um,

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Speaker 1: so you put the probability somewhere between zero and five percent,

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Speaker 1: I believe, and a lot a lot of people would

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Speaker 1: jump jumped on d silver for that UM. Now, even

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Speaker 1: a perfectly calibrated forecaster, and I'll say in a minute,

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Speaker 1: what a perfectly calibrated forecaster is. Even a perfectly calibrated

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Speaker 1: forecaster is going to be wrong five percent of that

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Speaker 1: UH is going to be wrong at least five percent

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Speaker 1: of the time when when they when they say five

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Speaker 1: percent UM. So it's a it's a difficult thing for

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Speaker 1: people to appreciate. But you you can't judge the accuracy

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Speaker 1: of probability judgments based on the individual forecast. You can

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Speaker 1: only do that if the forecaster is really reckless and

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Speaker 1: says hudd percent and it doesn't happen, or zero percent

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Speaker 1: and it does. And in that case, you know the

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Speaker 1: forecast a slat out wrong and forli forecast is taking

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Speaker 1: a big reputational risk and it is lost um. But

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

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Speaker 1: And that's that's the tricky thing that people have our

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Speaker 1: time wrapping their heads around. So so what should those

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Speaker 1: of us who who think about the economy, you think

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Speaker 1: about markets, and are occasionally called upon to make a

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Speaker 1: prediction out six months or a year, what should we

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Speaker 1: do to improve that process to become better forecasters. I

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Speaker 1: think you want people to feel accountable. Uh. So insofar

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Speaker 1: as the people who come on a shows use vague verbue,

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Speaker 1: make vague verbuge forecast and they think that they say,

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Speaker 1: I think there's a distinct possibility the market's going to

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Speaker 1: go over Bible blup. Uh. People may who make those

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Speaker 1: kinds of claims they sound meaningful, but in close inspection

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Speaker 1: they're very close to meaning less because distinct possibility is

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Speaker 1: one of those things you can you can you've got

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Speaker 1: a perfect hedge. If it happens, you can say, hey,

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Speaker 1: I told you distinct possibility. If it doesn't happen, you

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Speaker 1: can say, hey, I just said it was possible. So

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

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Speaker 1: but on close inspection, there's absolutely no way to monitor

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Speaker 1: keep track. So a better way to go is to

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Speaker 1: pressure people to make more precise estimates. Even though it hurts,

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Speaker 1: it's hard, it's potentially embarrassing, but best it's the best

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Speaker 1: way to learn. Beware weasel words. Speaking speaking of potentially embarrassing,

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Speaker 1: let's come back and talk to the professor about our

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Speaker 1: presidential derby. It has been sports Philip tet Luck with

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Speaker 1: this Anneburg professor university professor in Democracy and Citizenship at Wharton,

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Speaker 1: And uh, somebody has written some very important books on

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Speaker 1: thinking about really what do we do about certitude? And

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Speaker 1: is Mark Mark Twain. John Tucker was one of our

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Speaker 1: first guests and Bloombergunny Economy. It was a few years.

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Speaker 1: It was a book tour. I was like, it wasn't

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Speaker 1: Huncle Berry Finn, it was something else. But as Mr

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Speaker 1: Twain would say, the certitude of the second rate, maybe

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Speaker 1: that's a gospel of surveillance. As we listen with respected

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Speaker 1: Professor Tetlock, will return with Philip Tetlock, and uh look

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Speaker 1: forward to um. Some of the political certitude that is

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Speaker 1: out there very reminds me of the rule of thirty

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Speaker 1: which is abused every single day. We take a sample

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Speaker 1: size of four and say we believe, and uh, it

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

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Speaker 1: features up one oh one. Janet Yellen still influence, influencing

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Speaker 1: the market with yields set lower from twelve noon yesterday,

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Speaker 1: Oil thirty eight seventy seven the American barrel And now

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

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Speaker 1: thank you very much. The US is trying to give

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Speaker 1: support to allies in Eastern Europe who are increasingly concerned

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Speaker 1: about a more aggressive Russia. The Army plans to announce

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Speaker 1: today the deployment of an armored combat brigade along with

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Speaker 1: their equipment, to Eastern Europe next February, as part of

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Speaker 1: the ongoing effort to rotate troops in and out of

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Speaker 1: the region. The three Republican presidential candidates now saying they

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Speaker 1: won't commit to support whoever the party nominates in September,

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Speaker 1: Donald Trump, Ted Crews and John Kasi said they would

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Speaker 1: pledge their support. A federal judge in Oakland, California, has

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Speaker 1: scheduled to hear arguments today over whether to block a

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Speaker 1: new federal law that requires sex offenders to have unique

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Speaker 1: identifiers in their passports. Global News twenty four hours a day,

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Speaker 1: powered by our twenty four hundred journalists more than one

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Speaker 1: hundred fifty news bureaus from around the world. I am

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Speaker 1: Michael Barr, Tom and Michael, thanks so much again. I

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Speaker 1: remove the market. Finally, the bond market pauses, but the

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Speaker 1: two year yield point seven eight four three Genet yell

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Speaker 1: and are really moving uh markets yields lower, bond prices

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Speaker 1: higher over the last eighteen hours. They rid Alds Toime

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Speaker 1: Keene with Philip Block of Wharton Bloomberg Surveillance, Surveillance MUTI

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Speaker 1: by n y c B asking about their my community

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Speaker 1: interest checking but free n y c B online and

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Speaker 1: mobile banking. Earn more, get more. Visit n y CP

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Speaker 1: family dot com for details. Global business news twenty four

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Speaker 1: hours a day at Bloomberg dot com, the Radio plus

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Speaker 1: Mobile Act and on your radio, this is a Bloomberg

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Speaker 1: Business Flash. And I'm Karen Moscow roiking economic news. Crossing

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Speaker 1: the Bloomberg. Here's at Vinny down Judas with the latest

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Speaker 1: Vinny ran on the Labor Park labor market. The ADP

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Speaker 1: National Employment Report showing a gain of two hundred thousand,

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Speaker 1: and March again at two hundred thousand, topping Wall Street forecast.

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Speaker 1: That sets the stage for Friday's government employment report. Economists

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

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Speaker 1: Again the a P report Private payrolls march up two

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Speaker 1: hundred thousand. Karen, back to you, all right, thank you,

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Speaker 1: Vinnie del Judas. Let's go to the first word Breaking

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

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Speaker 1: Good morning, Bill, Good morning Karen. Futures are adding to

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Speaker 1: yesterday's gains. Doubt youre just currently hired by a hundred

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Speaker 1: one point says he's gain eleven and as a futures

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Speaker 1: rise by thirty two. The U S tenual at one

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Speaker 1: point eight three per cent. Up of markets are also rising,

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Speaker 1: led by one point nine percent gains in France after

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Speaker 1: develops Night Restoration Hardware Queen at JESSEPS and revenue trailed

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Speaker 1: estimates and very que for jesse EPs missed estimates Shares

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Speaker 1: a down fourteen percent pre market regarding earnings this morning.

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Speaker 1: Lul Lemon Hire by five point seven percent pre market

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Speaker 1: after its results, while Paychecks EPs was in line until

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Speaker 1: New Stage Street degrees to buy g e St Management

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Speaker 1: for up to four hundred eighty five million in cash.

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Speaker 1: Also another news, Valiant launches credit line amendment repeats following

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Speaker 1: plans and says comfortable with current liquidity position in family

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Speaker 1: some of your wallsheet upgrades and downgrades. Compass Meneral cut

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Speaker 1: the hold at BB and T, Apple raised out performer

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Speaker 1: cown price target one thirty five Varian Systems cut down

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Speaker 1: perform at Credit Suite, A I G raised to buy

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Speaker 1: a Janny and all scripts raised overweight over at Morgan

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Speaker 1: Stanley Live in the First Breaking News Desk on Bill Maloney.

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Speaker 1: Karen thanks Bill to hear live breaking news over your

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Speaker 1: Bloomberg type squawk go on your terminal. Let's ask you

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Speaker 1: you a w K go and that's a Bloomberg business flash.

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Speaker 1: Tom and Barry un thanks so much. Appreciate that. This

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Speaker 1: morning Bloomberg Surveillance Bunch by Investco. Do the day's headlines

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Speaker 1: have you searching for more investment views? Investco's experts can

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Speaker 1: help find out the latest thought leadership and Investco blog.

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Speaker 1: Visit investco dot com slash us to subscribe. At a

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Speaker 1: wonderful time with Investco yesterday, learned a lot about value

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Speaker 1: dividends and this this interesting phrase deep value from Keith

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Speaker 1: Holding the Value team UH at Investo and thank them

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Speaker 1: for their UH continued support of Bloomberg's surveillance and what

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Speaker 1: Michael and I do every day. Very results with us, Phillips,

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Speaker 1: luck with us who long ago and far away not

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Speaker 1: fifty two years ago? Read the medium is the message

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Speaker 1: understanding media the extensions of Van Marshall McLuhan. Have we

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Speaker 1: jumped to shark Professor Tutlock? Are we are we at

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Speaker 1: the point where the medium is the message and it

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Speaker 1: completely reforms and restructures our presidential politics day to day? Well, Uh,

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Speaker 1: that's a that's a big question. Um. So the conventional

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Speaker 1: wisdom's obviously been really rattled by the Donald Trump phenomenon.

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Speaker 1: I guess that's what you're probably referring to. Um. Yeah,

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Speaker 1: I thinks things have changed a lot. Uh. Trump was

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Speaker 1: able to tap into deep resentment. He was able to

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Speaker 1: get away with really pretty primitive debating tactics and wasn't

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Speaker 1: punished for them. U. Um. Donald Trump's style of debating

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Speaker 1: is pretty much the opposite end of the continuum from

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Speaker 1: the style of debating we try to encourage and forecasting tournaments, uh,

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Speaker 1: which value precision questioning and precision estimates. And who's that

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Speaker 1: you different universe? Who is the adult in the room

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Speaker 1: that's going to get us back to a better discourse? Um?

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Speaker 1: Who is he? Adntal boy boy? You asked tough questions, Tom.

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Speaker 1: People in the GOP are pointing to Paul Ryan and

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Speaker 1: John Kass as the presumptive adults in the room. Uh,

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Speaker 1: in in in that political party right now? Well, clearly

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Speaker 1: John kask at least on the debate stage, had has

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Speaker 1: appeared like the adults. The problem is he's been rewarded

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Speaker 1: for that with a third place finish everywhere outside his

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Speaker 1: home state. Are we looking of politics? Are we looking

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Speaker 1: in the wrong place for adult discussions about important issues?

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Speaker 1: Probably perhaps so at the moment um. But when you

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Speaker 1: look at the bigger picture, are the best forecasters, for example,

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Speaker 1: in our tournaments are putting close to a seventy percent probability?

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Speaker 1: Now and Hillary being the next president of the United States,

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Speaker 1: so once she's sworn in, this will look this will

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Speaker 1: be a distant memory. Uh, And the question will be

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Speaker 1: what have what? What has the Republican Party in particular

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Speaker 1: learned from its experience? Um? Now, of course, uh, the

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Speaker 1: very best forecasters, like Nate Silver was was was somewhat

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Speaker 1: off the mark early on, and then the and and

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Speaker 1: the best forecasters in our tournament maybe off the mark. Also,

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Speaker 1: when you say seventy percent probability, that means the percent

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Speaker 1: probability of other things. Uh. So let's talk about that

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Speaker 1: with more important issues than politics. What I what I

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Speaker 1: find fast sitting about your work is how the intelligence

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Speaker 1: community has sort of thrown aside their old way of

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Speaker 1: doing things and approached you to say, we need better

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Speaker 1: ways to think about uncertain events. So let's talk about that.

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Speaker 1: What is the intelligence community learning from the mistakes that

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Speaker 1: have been made in the past. Well, the intelligence community

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Speaker 1: works at ground zero in the blame game political culture.

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Speaker 1: So if they make a wrong call, they're gonna get

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Speaker 1: They're gonna get blasted one way or the other. And

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Speaker 1: the wrong calls can take one of two forms. They

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Speaker 1: can have a catastrophic um false negative such as nine

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Speaker 1: eleven UH, They'll be totally condemned. They'll be roundly condemned

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Speaker 1: for it. There'll be presidential commission, will be congressional investigations.

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Speaker 1: And the one lesson that an intell intelligence intelligence officer

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Speaker 1: would learn from that experiences whatever mistake I'm going to make,

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Speaker 1: don't make the mistake I just made, which means don't

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Speaker 1: make a false negative. That sets you up for making

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Speaker 1: the opposite mistake a false positive. Now, they made a

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Speaker 1: false positive mistake with weapons of mass destruction in Iraq. Uh.

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Speaker 1: They got blasted for that, and there are investigations and

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Speaker 1: commissions and what does an intelligent, intelligent officer intelligence officer

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Speaker 1: conclude from all that, Well, whatever mistake I'm gonna make,

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Speaker 1: don't make the mistake I made last. So they get

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Speaker 1: caught up in this kind of blame game ping pong um,

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Speaker 1: which is not really learning. It's it's threshold shifting. It's

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Speaker 1: it's shifting my tolerance from making one mistake or other

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Speaker 1: rather than learning in a deep and a methodical way

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Speaker 1: from history. The way to learn in a deep and

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Speaker 1: methodical way from history is to make explicit judgments the

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Speaker 1: domains in which are well calibrated not and proceed that way.

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Speaker 1: And professor, thank you so much for being us with

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Speaker 1: us today. Phil Tetlock is from Warton super Forecasters is

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Speaker 1: a hugely successful book on the experts. We really appreciate

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Speaker 1: his perspective as we try to find you the best

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