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Speaker 1: Welcome to Stuff to Blow Your Mind, the production of iHeartRadio.

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Speaker 2: Hey you welcome to Stuff to Blow your Mind. My

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Speaker 2: name is Robert.

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Speaker 3: Lamb and I am Joe McCormick, and we're back with

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Speaker 3: part two in our series called The Devil You Know,

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Speaker 3: which is about ambiguity aversion. That's the observation that we

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Speaker 3: prefer risks with known probabilities over risks with unknown probabilities,

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Speaker 3: even if you have no reason for thinking that the

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Speaker 3: unknown risks will be worse. This preference is captured by

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Speaker 3: the folk saying, better the devil you know than the

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Speaker 3: devil you don't. For the most part, people don't like

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Speaker 3: taking bets when they don't know what the odds are,

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Speaker 3: and will pay up just to avoid having to deal

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Speaker 3: with ambiguity. And this is funny in a way because

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Speaker 3: almost all of the decisions that we make in our

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Speaker 3: actual lives are made with incomplete knowledge and some significant

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Speaker 3: amount of uncertainty about our likelihood of success. Very few

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Speaker 3: things in reality have clear objective odds, like a fair

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Speaker 3: coin flip or a dice roll. However, it's pretty well

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Speaker 3: established that most people, most of the time, do not

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Speaker 3: like making decisions under ambiguous conditions, and we will go

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Speaker 3: to great lengths to avoid taking risks with unknown probabilities.

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Speaker 3: So in the last episode, after we introduced the concept,

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Speaker 3: we talked a good bit about the original piece of

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Speaker 3: writing that made ambiguity aversion famous. This was a nineteen

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Speaker 3: sixty one paper by the American economist, anti war activist,

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Speaker 3: and whistleblower Daniel Ellsberg. The paper was called Risk Ambiguity

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Speaker 3: and the Savage Axioms, published in the Quarterly Journal of Economics,

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Speaker 3: and to briefly recap, this paper proposed the concept of

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Speaker 3: ambiguity aversion using a number of thought experiments where you

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Speaker 3: could take different bets based on like which color ball

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Speaker 3: you would draw by chance out of an urn. Elsberg's

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Speaker 3: point was that people would tend to prefer bets with

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Speaker 3: clear odds of winning, say a one in three chance,

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Speaker 3: over bets with unknown odds, where you could have anywhere

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Speaker 3: between a zero percent chance or a two out of

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Speaker 3: three chance. Elsberg's intuition here has been broadly supported by

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Speaker 3: real world experiments. There are a few exceptions, but most

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Speaker 3: of the time most people would rather take bets with

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Speaker 3: clear odds, even in ways that end up implying self

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Speaker 3: contradictory assumptions about the unknown odds. This was an important

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Speaker 3: discovery in the economic field known as decision theory because

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Speaker 3: it violated a framework known as Savage's axioms, which were

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Speaker 3: widely used to model how people make decisions in situations

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Speaker 3: of uncertainty or ambiguity, and this self contradictory behavior is

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Speaker 3: now known as the Ellsberg paradox. And then, finally, in

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Speaker 3: the last episode, after talking about the theoretical origins of

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Speaker 3: ambiguity aversion, we also talked about this phenomenon in practice

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Speaker 3: in the real world, and our main example here was

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Speaker 3: the negotiation strategy famously associated with the Nixon White House

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Speaker 3: known as madman theory, a strategy where you intentionally cultivate

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Speaker 3: a reputation for volatility and unpredictability. In essence, you make

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Speaker 3: your peers and your counterparties worry that you are a

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Speaker 3: madman who is capable of anything, and the idea here

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Speaker 3: we ended up talking about a lot of reasons for

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Speaker 3: thinking that this is actually not a good strategy, but

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Speaker 3: the idea here is that you will exploit their natural

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Speaker 3: ambiguity aversion to get them to make concessions that they

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Speaker 3: would not make otherwise, And then we did get into

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Speaker 3: some international relations research on Madman theory, like reasons why

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Speaker 3: it might not actually be a good strategy, especially for

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Speaker 3: achieving long term goals. In fact, I think in the

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Speaker 3: long term most experts seem to agree that it is

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Speaker 3: harmful to everyone involved, including the practitioner. But again, the

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Speaker 3: reason it may sometimes work for achieving short term wins

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Speaker 3: is by taking advantage of this fear people have of ambiguity,

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Speaker 3: the fact that a lot of people would rather just

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Speaker 3: take a bad deal than keep negotiating with somebody who

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Speaker 3: is highly unpredictable.

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Speaker 2: You know, I was thinking after our recording that another

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Speaker 2: often cited bit of supposed wisdom along these lines is

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Speaker 2: the idea in generally you'll see this reference out of context,

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Speaker 2: so someone will not be talking about actually going to prison.

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Speaker 2: They'll be talking about your first dai of new school

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Speaker 2: or something, and they'll jokingly say, well, you know what

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Speaker 2: you're supposed to do. You're supposed to go up to

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Speaker 2: the biggest person around and hit them with a steel chair,

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Speaker 2: And then everyone will be like, WHOA, that guy's crazy.

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Speaker 2: We better not mess with him. It seems to follow

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Speaker 2: similar logic, and also seem equally, if not more flawed

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Speaker 2: in its approach. It does not sound like a tactic

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Speaker 2: that would actually generate like, you know, long term benefits.

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Speaker 3: It's one of those pieces of advice that is probably

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Speaker 3: more often repeated because it's like memorable and funny and

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Speaker 3: makes for a good story because that many people would

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Speaker 3: think it's actually good advice, especially if you have relevant experience.

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Speaker 2: I don't know.

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Speaker 3: I mean, I don't know a lot about like prison strategy,

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Speaker 3: but that does seem like you could have some real downsides.

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Speaker 2: You know, it makes me think of that the you know,

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Speaker 2: the the this sense another bit of wisdom, another nugget

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Speaker 2: that's Offen dished out, and that is getting into the

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Speaker 2: philosophy of Nietzsche. Uh, you know that which doesn't kill

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Speaker 2: us makes us stronger. But I forget who it was

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Speaker 2: who did a spin on this and said, well that

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Speaker 2: that which doesn't kill us nearly kills us, and that

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Speaker 2: should be a reason to give us pause.

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Speaker 3: That's funny because that Nietzsche saying is also when I

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Speaker 3: know this has come up on the show before, I

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Speaker 3: know that like in huge number of cases that's not true. Yeah,

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Speaker 3: like sometimes it makes us stronger, like we do sometimes learn,

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Speaker 3: learn and grow and gain strength from adversity, but that's

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Speaker 3: like some subset of adversities. A lot of adversities leave

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Speaker 3: us much weaker and deeply shaken.

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Speaker 2: Yeah, shaken, or less trusting or just yeah, or just

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Speaker 2: completely weakened. And I know this may weaken us. We

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Speaker 2: survive it, but it's weakened our system and then we're

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Speaker 2: more susceptible to the next thing and so forth. So yeah,

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Speaker 2: I mean, it's great to take solace in some of

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Speaker 2: these sayings, but you can only take them so far, really, So.

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Speaker 3: Anyway, we're back today to talk about some more angles

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Speaker 3: on ambiguity aversion, and one of the first things I

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Speaker 3: want to get into is that in the last episode

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Speaker 3: we did talk a bit about the distinction that Daniel

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Speaker 3: Elsberg tried to make between ambiguity and risk. But I

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Speaker 3: think one thing that's really important to point out that

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Speaker 3: we didn't get into last time is the distinction between

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Speaker 3: ambiguity aversion and risk aversion. I think risk aversion is

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Speaker 3: a concept more people are probably familiar with, you know,

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Speaker 3: that comes up in conversation. Sometimes these are not the

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Speaker 3: same thing. One who is risk averse doesn't like to

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Speaker 3: make bets. They would prefer a sure thing, even if

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Speaker 3: the sure thing is statistically less valuable than the risk. So,

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Speaker 3: for example, imagine a fair coin flip game. We stipulate

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Speaker 3: that this is a fair coin. There's no cheating involved,

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Speaker 3: and on each round when I flip the coin, I

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Speaker 3: can either just give you forty dollars no matter how

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Speaker 3: the coin lands, or I could give you one hundred

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Speaker 3: dollars every time it lands heads and nothing every time

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Speaker 3: it lands tails.

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Speaker 2: So with the.

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Speaker 3: Gambling condition here, you will on average win fifty dollars

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Speaker 3: per round. It's a fifty to fifty chance of winning,

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Speaker 3: and the payout is one hundred dollars. So the odds

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Speaker 3: here are clear. If you play this game a thousand

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Speaker 3: times in a row, you will make more money by

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Speaker 3: gambling than by taking the guaranteed forty dollars every time.

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Speaker 3: It's statistically all but a sure thing. But still some

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Speaker 3: people would rather just take the actual sure thing. They

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Speaker 3: would rather just take the forty dollars, and that is

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Speaker 3: risk aversion. It is a psychological tendency to dislike and

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Speaker 3: avoid taking a stake in uncertain outcomes, even if you

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Speaker 3: know the exact odds of those outcomes and potentially even

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Speaker 3: if those odds will statistically bring you more benefit than

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Speaker 3: the sure thing. And another way of thinking about risk

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Speaker 3: aversion is that sometimes to some people, the feeling of

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Speaker 3: security that you get from taking the sure thing is

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Speaker 3: actually more valuable than the money. It's more valuable than

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Speaker 3: the extra money that you would take home on average

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Speaker 3: by placing a bet with a higher expected value. And

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Speaker 3: this emphasizes something that is true in decision theory and economics.

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Speaker 3: Value isn't just about getting or keeping money. We use

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Speaker 3: money because it's an easy way to quantify value and experiments.

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Speaker 3: But sometimes we would pay money just to feel certainty

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Speaker 3: and comfort. That feeling is of higher value to us

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Speaker 3: than the money is. But then, of course again, other

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Speaker 3: people at other times would not pay that. Some people

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Speaker 3: love the feeling of risk. I mean people gamble for pleasure.

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Speaker 2: Yeah, absolutely, but yeah, but other times it's like I

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Speaker 2: just don't want to take a chance on this. I'd

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Speaker 2: rather just go for what's going to be straightforward and guarantee, right.

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Speaker 3: So that's risk and risk aversion. Ambiguity a version is

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Speaker 3: different from risk aversion because it is not about a

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Speaker 3: dislike of risk, but specifically a desire to avoid ambiguous

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Speaker 3: risks with unclear odds. You might love gambling on a

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Speaker 3: fifty to fifty coin toss, but you might not want

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Speaker 3: to play the game where you have to guess how

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Speaker 3: many black balls or yellow balls there are and there's

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Speaker 3: no way to know. So a person could technically be

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Speaker 3: not very risk averse at all, but highly averse to

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Speaker 3: ambiguity the interaction. The more I thought about it, the

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Speaker 3: more I thought that the interaction between these two tendencies

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Speaker 3: in real life is interesting because I think to many

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Speaker 3: of us, it's not always if a fear or a

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Speaker 3: hesitancy we're experiencing about making a decision is rooted in

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Speaker 3: risk aversion or ambiguity aversion. For instance, this came up

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Speaker 3: because I was trying to think of examples of risk aversion,

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Speaker 3: and I thought of the idea of what to do

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Speaker 3: with savings. Imagine you save up a little bit of

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Speaker 3: extra money at work from your paycheck, and you want

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Speaker 3: to put that toward retirement, and you have multiple options

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Speaker 3: of what to do with that money. Imagine a person's

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Speaker 3: in that scenario and they discover that they would really

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Speaker 3: feel better just keeping the money in a bank account,

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Speaker 3: earning a relatively low rate of interest, rather than investing

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Speaker 3: it in like a stock market index fund, where with

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Speaker 3: the index fund, it is commonly assumed it is standard

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Speaker 3: financial wisdom that the balance will grow at a faster

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Speaker 3: rate than it will just sitting in a savings account,

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Speaker 3: and you will end up with more money years down

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Speaker 3: the road if you put it in the index fund.

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Speaker 3: This pattern of behavior could be taken as an example

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Speaker 3: of risk aversion, because it's like, I would choose to

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Speaker 3: probably end up with less money just so I can

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Speaker 3: avoid taking risks with what I have. But then I thought, well, no,

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Speaker 3: not necessarily. What if that same impulse is actually a

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Speaker 3: better example of ambiguity a version than risk aversion, Because

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Speaker 3: how do we actually know that a stock market index

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Speaker 3: fund will grow more over time than the balance of

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Speaker 3: a savings account. The answer is historical patterns. It's like

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Speaker 3: statistically true over the last one hundred years or so,

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Speaker 3: you know, within certain economies in living memory. But it's

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Speaker 3: not actually like a fixed odds casino game or a

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Speaker 3: lab experiment where the odds of winning are fair axiomatically

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Speaker 3: in the real world. As the fine print always says,

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Speaker 3: investing involves risk, including loss of principle, and past performance

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Speaker 3: does not guarantee future returns. So maybe actually preferring the

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Speaker 3: savings account is a form of ambiguity aversion rather than

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Speaker 3: risk aversion, responding to the idea that, well, what are

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Speaker 3: the odds that suddenly, somehow investing in the stock market

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Speaker 3: becomes a bad idea in a way that it has

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Speaker 3: not within living memory. It's hard to understand what the

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Speaker 3: odds of something like that are. Seems pretty unlikely, but

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Speaker 3: it's fundamentally ambiguous. You just can't say what the objective

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Speaker 3: odds are. There's really no way to calculate them. So

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Speaker 3: sometimes there's actually ambiguity about whether there is ambiguity, you know,

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Speaker 3: because like I think an invest an investment advisor might

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Speaker 3: tell you on one hand, like, well, you know, historical

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Speaker 3: performance of the stock market, you can pretty much depend

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Speaker 3: on that that's a known risk when you know you

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Speaker 3: have you have statistics that tell you that you'll most

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Speaker 3: likely get this rate of return on average, and you

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Speaker 3: just don't know how seriously to take the possibility that

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Speaker 3: the future will not be like the past.

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Speaker 2: Yeah. Absolutely, And another angle that I was looking at

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Speaker 2: here on all this is that it's not just the

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Speaker 2: ambiguity and risk, but it's perceptions of ambiguity and risk.

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Speaker 2: So you know, it ultimately isn't necessarily coming down as

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Speaker 2: much to like what are actually the hard probabilities here.

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Speaker 2: It can skew greatly depending on what a particular individual's

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Speaker 2: worldview is. So you could have somebody like you could

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Speaker 2: have like a you know, a Washington Bartholomew hog Wallop figure,

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Speaker 2: and he's decided not only is he not going to

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Speaker 2: invest in the stock market, he's not even gonna put

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Speaker 2: his money in the bank. It's better off in the

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Speaker 2: tin can buried in his backyard.

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Speaker 3: Yeah, there you go.

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Speaker 2: Yeah, even though there may be very good statistics that

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Speaker 2: show that is less safe. Yeah, and that is a

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Speaker 2: greater risk. Your worldview and perception could be Oh no, absolutely,

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Speaker 2: you can't trust the banks at all. I can only

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Speaker 2: trust myself, and therefore it's safer in my yard with

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Speaker 2: me standing over it with a shotgun.

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Speaker 3: But anyway, so this all brings us back to this

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Speaker 3: distinction between risk aversion and ambiguity aversion, and how difficult

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Speaker 3: it can be to tell the difference between the two,

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Speaker 3: Like when we feel aversion to making a bet of

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Speaker 3: some kind, which by way of analogy. That doesn't have

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Speaker 3: to mean literally a bet with money, but just any

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Speaker 3: important decision in our lives when we feel that, like fear, hesitancy,

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Speaker 3: or resistance. We often think of this as risk aversion,

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Speaker 3: but could it actually be more often ambiguity aversion That

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Speaker 3: we're responding subconsciously to the fact that we don't know

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Speaker 3: how to calculate the odds for the decision we're about

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Speaker 3: to make, and that makes us uncomfortable. Now, one of

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Speaker 3: the big things we left open after we introduce the

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Speaker 3: concept of ambiguity a version in the last episode is

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Speaker 3: how is decision theory supposed to make sense of this

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Speaker 3: finding of like the Elsberg paradox? And there has been

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Speaker 3: a great amount of inks billed in answering this question

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Speaker 3: in the fifty something years since Elsberg. I don't think

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Speaker 3: I can even attempt to cover the whole landscape of

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Speaker 3: responses here, so I want to be clear this will

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Speaker 3: not be a comprehensive technical survey of the ambiguity of

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Speaker 3: version literature. I'm just going to mention a couple of

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Speaker 3: broad trends and then a few ideas within each. So

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Speaker 3: within the responses there are two main categories of thought.

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Speaker 3: One assumes that ambiguity aversion is actually a component of

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Speaker 3: rational decision making, that it is, in a subjective sense

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Speaker 3: wise to avoid ambiguity even when you can't really prove

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Speaker 3: that the ambiguous bets will generally turn out bad. The

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Speaker 3: other main way of thinking is that ambiguity a version

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Speaker 3: is some type of error or cognitive bias. And here

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Speaker 3: I'm going to mention a couple of sources. The first

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Speaker 3: one I cited in our last episode. That is a

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Speaker 3: book chapter by Mark J. Maschina and Marciano Siniscalci called

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Speaker 3: Ambiguity and Ambiguity of Version in the Handbook of Economics

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Speaker 3: of Risk and Uncertainty published in twenty fourteen. And then

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Speaker 3: the second source I want to mention here is by

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Speaker 3: Nabil I al Najar and Jonathan Weinstein published in the

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Speaker 3: Journal of Economics and Philosophy called the Ambiguity of Version

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Speaker 3: Literature a Critical Assessment. This one is more in that

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Speaker 3: second category I mentioned. It's an approach arguing that ambiguity

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Speaker 3: of version is actually just a type of error basically.

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Speaker 3: So first I want to look at what are some

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Speaker 3: of the ways that ambiguity aversion and like the Elsberg

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Speaker 3: paradox might actually be a form of rational, self consistent

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Speaker 3: decision making. One theory here can be called the multiple

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Speaker 3: priors model, also known as max men expected utility max

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Speaker 3: men is max n max men expected utility or MEU.

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Speaker 3: Let's think about it like this. Imagine you are asked

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Speaker 3: to make a bet involving ambiguous odds, like we'll go

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Speaker 3: back to the balls in the urn example from the

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Speaker 3: first episode. So am I more likely to pull a

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Speaker 3: red ball or a black ball out of this urn?

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Speaker 3: And so to remember the details there? The three color

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Speaker 3: eurn experiment was that inside this urn you can't see inside,

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Speaker 3: you don't know what color you're reaching into grab, but

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Speaker 3: there are exactly thirty red balls and then sixty balls

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Speaker 3: that could be any mix of yellow and black. So

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Speaker 3: they could be zero yellow and sixty black, sixty yellow

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Speaker 3: and zero black, thirty and thirty, or anything in between.

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Speaker 3: You have no way of knowing the mix in advance.

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Speaker 3: In these situations, maximin expected utility theory would say that

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Speaker 3: instead of forming one consistent belief about the number of

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Speaker 3: black balls inside and then placing bets according to that prediction,

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Speaker 3: we allow ourselves to consider multiple different probabilities and we

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Speaker 3: apply those probabilities to different bets pessimistically. So essentially, for

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Speaker 3: each new bet that requires us to guess the number

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Speaker 3: of black balls, we ask ourselves what would be the

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Speaker 3: worst case scenario for me here, and then we assume

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Speaker 3: those worst case odds when considering the bet. So if

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Speaker 3: you're asked to choose between black and red, there could

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Speaker 3: be anywhere between zero and sixty black balls, you just

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Speaker 3: assume there are zero and you bet on red. I

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Speaker 3: tried to come up with a real life decision sequence

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Speaker 3: that might help the contradictory behavior under MEU makes sense.

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Speaker 3: So here's what I've got to imagine this. You're making

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Speaker 3: plans for the afternoon and you don't know what the

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Speaker 3: weather is going to be. It might rain, it might not.

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Speaker 3: Don't know how to calculate that. You were thinking about

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Speaker 3: maybe going out for a walk, but then again, considering

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Speaker 3: that it might rain, you don't want to be caught

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Speaker 3: out in a storm, so you decide instead to stay

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Speaker 3: home and do some indoor activities. At the same time,

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Speaker 3: you are also deciding what to do about the flowers

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Speaker 3: on your front porch. They're drooping and they need some water.

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Speaker 3: Now it might rain and then they would get all

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Speaker 3: the water they need from that, But then again it

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Speaker 3: might not rain, so you decide to make time to

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Speaker 3: fill up a watering can and water them manually. This

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Speaker 3: could appear inconsistent because you've made two different decisions, both

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Speaker 3: on the bet that it will rain in one case

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Speaker 3: and on the bet that it won't rain in the

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Speaker 3: other case. It's possible that that's just self contradictory, or

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Speaker 3: it could be perfectly self consistent and logical if you

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Speaker 3: are considering a range of different probabilities of rain for

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Speaker 3: the afternoon and then applying the most pessimistic one to

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Speaker 3: each decision rather than just assuming one probability that applies

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Speaker 3: to all decisions. Does that make sense?

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Speaker 2: Yeah, yeah, I think so.

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Speaker 3: And to be clear, there's no guarantee here that the

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Speaker 3: pessimistic assumptions will be correct, because again, the information environment

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Speaker 3: is truly ambiguous. You just can't know. That's what ambiguity is.

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Speaker 3: But considering multiple probabilities and acting according to the most

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Speaker 3: pessimistic one for each decision is theoretically a logical and

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Speaker 3: consistent strategy. So the authors that support this model argue

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Speaker 3: that it is actually a rational way. Ambiguity version might

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Speaker 3: produce the apparently self contradictory results we observe, like the

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Speaker 3: apparent contradiction comes from the fact that we're sort of

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Speaker 3: coming up with different predictions for each bet instead of

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Speaker 3: one prediction for the actual full state of affairs.

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Speaker 2: Yeah. Though, of course, making all your decisions based on

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Speaker 2: worst case scenario is not a great way to live your.

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Speaker 3: Life, right, And I'm going to come back to that

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Speaker 3: in a minute, because that is part of the critical assessment.

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Speaker 3: Another theory that would make the Elsberg paradox behavior rational

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Speaker 3: is what's known as show qu expected utility or CEU

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Speaker 3: and the show K. There. That's a French name. It's

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Speaker 3: cho q u e.

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Speaker 2: T show k sounds delicious.

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Speaker 3: Oh yeah, so sho K. Expected utility is the idea

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Speaker 3: that when we evaluate a bet and the odds are ambiguous,

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Speaker 3: we basically we do come up with a single internal

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Speaker 3: belief about probability, but it takes a weird form. Instead

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Speaker 3: of a probability, we use what the literature calls a capacity.

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Speaker 3: So most of the time when we're trying to judge

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Speaker 3: how likely something is to happen, together the likelihood of

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Speaker 3: that event and the likelihood of its negation of not

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Speaker 3: that event have to sum up to one hundred percent. Right,

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Speaker 3: So like under normal probability, if there is a one

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Speaker 3: third chance a ball will be read, there is a

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Speaker 3: two thirds chance the ball will not be read. These

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Speaker 3: complementary probabilities should always sum to one, or, if expressed

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Speaker 3: as a percentages up to one hundred percent. CEU theory

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Speaker 3: says that our internal representation of likelihoods for ambiguous events

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Speaker 3: is not like this. Instead, when the odds are ambiguous,

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Speaker 3: we operate on the basis of a capacity, which mathematically

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Speaker 3: incorporates our lack of confidence in the situation by representing

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Speaker 3: the chance of an outcome and its negation together in

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Speaker 3: a way that does not have to add up to

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Speaker 3: one hundred percent. And I apologize to the more informed people,

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Speaker 3: I'm skipping over some mathematical complexity here, but this is

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Speaker 3: the simplified version. Is if you take the example of

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Speaker 3: the three color eurn, a person might begin with the

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Speaker 3: objective information that you know thirty one third of the

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Speaker 3: balls are red, so you know you actually have a

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Speaker 3: one third chance that the ball you draws red, And

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Speaker 3: then for the yellow and black balls, instead of coming

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Speaker 3: up with with guesses that sum up to two thirds,

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Speaker 3: which would be the actual sort of objective probability. Whatever

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Speaker 3: the mix is, you pick some smaller probabilities, like you

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Speaker 3: add in a maybe a one fifth chance that the

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Speaker 3: ball is yellow and a one fifth chance that the

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Speaker 3: ball is black. Obviously, these these cannot be the real

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Speaker 3: objective odds. Again with the caveat on what are actually

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Speaker 3: objective odds, but they can't be the real They can't

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Speaker 3: represent reality because they don't add up to one and

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Speaker 3: there are no other colors in there. But again, the

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Speaker 3: values we come up with in these kinds of decision

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Speaker 3: making processes don't have to be perfect at predicting real outcomes,

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Speaker 3: and in fact they can't be because we are missing

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Speaker 3: information that is the ambiguity. The point is that this

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Speaker 3: is another self consistent way our minds could work while

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Speaker 3: producing the behaviors observed in these experiments, like the missing

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Speaker 3: percentage of likely outcomes and the calculation is missing to

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Speaker 3: reflect the level of ambiguity we feel about the bet.

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Speaker 3: So that's two main models, and there are other models

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Speaker 3: for making sense of the Elsberg paradox behavior in these

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Speaker 3: sorts of ways. But I think these give you a

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Speaker 3: general idea of how this strain of thinking works. The

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Speaker 3: other main way of thinking about ambiguity version is that

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Speaker 3: it is not actually rational, like you don't need to

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Speaker 3: find a way of making rational sense of it. Instead,

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Speaker 3: it is a form of error or cognitive bias. And

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Speaker 3: this is the thrust of the paper that I mentioned

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Speaker 3: earlier from two thousand and nine by on the jar

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Speaker 3: In Weinstein. The authors here argue in short, that ambiguity

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Speaker 3: a version is actually a misapplied heuristic. It meaning it's

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Speaker 3: a mental shortcut that might be truly useful in some scenarios,

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Speaker 3: for example, in situations where we need to be cautious

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Speaker 3: to avoid being scammed or manipulated, but this shortcut gets

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Speaker 3: mistakenly applied to scenarios where it is not helpful, and

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Speaker 3: misapplying the ambiguity version heuristic like this, they say, could

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Speaker 3: cause you to like make different bets about the same

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Speaker 3: thing when conditions are the same and no new information

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Speaker 3: has been learned, so you know, like that's producing this

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Speaker 3: contradictory or apparently irrational behavior, or it could cause you

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Speaker 3: to treat non non informative information as informative. They also

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Speaker 3: argue that relying on heuristics like pessimism coming back to

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Speaker 3: your comment earlier, Rob, Again, that's always assuming the worst

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Speaker 3: case scenario for ambiguous bets. If you actually do this,

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Speaker 3: if you rely on a pessimistic heuristic in real life,

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Speaker 3: this will systematically produce incorrect predictions and bad outcomes. It's

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Speaker 3: actually not a good strategy to follow. Failure to make

436
00:25:17,600 --> 00:25:21,680
Speaker 3: bets or decisions in the presence of ambiguity also causes

437
00:25:21,800 --> 00:25:25,560
Speaker 3: us to never gain useful information because a lot of

438
00:25:25,560 --> 00:25:29,080
Speaker 3: times we can only learn more about what the real

439
00:25:29,119 --> 00:25:33,320
Speaker 3: odds are by making decisions in ambiguous conditions. You know,

440
00:25:33,440 --> 00:25:38,119
Speaker 3: like past bets on ambiguity lead to more informed bets

441
00:25:38,119 --> 00:25:41,200
Speaker 3: with higher certainty in the future because the previous bets

442
00:25:41,200 --> 00:25:43,639
Speaker 3: and their outcomes are information gathering tools.

443
00:25:44,440 --> 00:25:46,159
Speaker 2: Yeah, and of course we see this played out in

444
00:25:46,200 --> 00:25:49,000
Speaker 2: the simplified world of games. If you want to get

445
00:25:49,000 --> 00:25:51,879
Speaker 2: good at you know, particular card game or chess or

446
00:25:51,920 --> 00:25:56,240
Speaker 2: anything like that, you need to be prepared to be

447
00:25:56,240 --> 00:25:59,280
Speaker 2: beat a lot, you know. I mean, that's that's part

448
00:25:59,320 --> 00:26:01,920
Speaker 2: of learning what your odds are with a native in play.

449
00:26:02,040 --> 00:26:05,199
Speaker 3: That's right. So this strain of thinking says, no, ambiguity

450
00:26:05,200 --> 00:26:09,399
Speaker 3: aversion is not a rational strategy for making decisions. Instead,

451
00:26:09,400 --> 00:26:12,720
Speaker 3: it's it's more like an emotional bias that causes us

452
00:26:12,760 --> 00:26:16,680
Speaker 3: to act on yes self contradictory beliefs and to make

453
00:26:16,720 --> 00:26:20,760
Speaker 3: bad decisions because we do not like the feeling of ambiguity.

454
00:26:21,359 --> 00:26:25,120
Speaker 3: And honestly, I'm not sure which strain of thinking is

455
00:26:25,200 --> 00:26:27,160
Speaker 3: more on track. I've been reading about these and I'm

456
00:26:27,160 --> 00:26:30,360
Speaker 3: not I don't know who's more convincing that like that

457
00:26:30,400 --> 00:26:35,159
Speaker 3: it's part of rationality overall, or that it's not. The

458
00:26:35,200 --> 00:26:38,600
Speaker 3: whole thing about ambiguity, of course, is that it's ambiguous

459
00:26:38,640 --> 00:26:40,480
Speaker 3: whether or not you should bet on it, so there

460
00:26:40,520 --> 00:26:44,760
Speaker 3: really is no objective answer, but I think there, I mean,

461
00:26:44,800 --> 00:26:49,520
Speaker 3: what we're instead looking for is what is the most

462
00:26:50,160 --> 00:26:54,119
Speaker 3: what is the most consistent way to explain the subjective behavior,

463
00:26:54,280 --> 00:26:57,320
Speaker 3: rather than like, who's actually right about you know, the

464
00:26:57,400 --> 00:26:59,639
Speaker 3: ambiguous outcomes because there's no way to know them in

465
00:26:59,680 --> 00:27:03,600
Speaker 3: advance by definition. I do think the critical assessment makes

466
00:27:03,640 --> 00:27:07,760
Speaker 3: a really good point about learning. You really do often

467
00:27:07,840 --> 00:27:10,879
Speaker 3: have to be bold and make decisions in the face

468
00:27:10,920 --> 00:27:14,359
Speaker 3: of ambiguity so that there will be more information and

469
00:27:14,480 --> 00:27:17,520
Speaker 3: less ambiguity in future decisions. That seems like a highly

470
00:27:17,520 --> 00:27:18,560
Speaker 3: salient point to me.

471
00:27:19,280 --> 00:27:22,800
Speaker 2: Yeah, yeah, And would you say based on what you

472
00:27:22,880 --> 00:27:27,600
Speaker 2: were looking at that it sounds like ambiguity aversion is

473
00:27:27,640 --> 00:27:31,920
Speaker 2: itself adaptive in the grand scheme of things. Maybe it's

474
00:27:31,920 --> 00:27:35,600
Speaker 2: one of these situations like type one errors in cognition

475
00:27:35,720 --> 00:27:40,120
Speaker 2: false pos positives versus type two errors and cognition's false negatives,

476
00:27:40,160 --> 00:27:44,040
Speaker 2: where in sort of the hypothetical tiger's hiding in the

477
00:27:44,040 --> 00:27:48,119
Speaker 2: bush's scenario, this is absolutely adaptive. But then when taken

478
00:27:48,280 --> 00:27:51,280
Speaker 2: into other aspects of life, especially modern life and all

479
00:27:51,280 --> 00:27:53,879
Speaker 2: its complexity, it's not necessarily useful.

480
00:27:54,240 --> 00:27:55,919
Speaker 3: Well, I mean that, I think you could think of

481
00:27:55,960 --> 00:27:57,840
Speaker 3: it that way, and that might be one way of

482
00:27:57,880 --> 00:28:03,280
Speaker 3: approaching the error theory, right, that it's a mental shortcut

483
00:28:03,320 --> 00:28:06,040
Speaker 3: that is useful in some scenarios, again, especially when you're

484
00:28:06,080 --> 00:28:09,679
Speaker 3: like trying to avoid being tricked or trying to avoid

485
00:28:09,720 --> 00:28:12,800
Speaker 3: being taken advantage of by somebody who has superior information

486
00:28:12,960 --> 00:28:17,080
Speaker 3: to you. But then you're misapplying it to scenarios where

487
00:28:17,080 --> 00:28:20,640
Speaker 3: that's not really the case. You're just like you're using

488
00:28:20,680 --> 00:28:23,480
Speaker 3: a defensive mental shortcut in a case where you don't

489
00:28:23,480 --> 00:28:26,480
Speaker 3: really need to, and it's causing you to act with

490
00:28:26,760 --> 00:28:30,400
Speaker 3: unnecessary levels of defense, which produce irrational behavior. And we've

491
00:28:30,400 --> 00:28:32,280
Speaker 3: talked about other ways that that can be true. So

492
00:28:32,600 --> 00:28:35,280
Speaker 3: I think that fits more with the error way of thinking.

493
00:28:35,960 --> 00:28:38,520
Speaker 3: I think the other way of thinking would just say that, yeah,

494
00:28:38,560 --> 00:28:41,600
Speaker 3: I mean this would probably assume it doesn't really comment

495
00:28:41,680 --> 00:28:44,360
Speaker 3: on this, but it would just assume probably that it's

496
00:28:44,400 --> 00:28:49,280
Speaker 3: adaptive because it is just part of our consistent decision

497
00:28:49,320 --> 00:28:51,960
Speaker 3: making toolkit, and it's you know, just the same way

498
00:28:52,000 --> 00:28:55,880
Speaker 3: that our brains decide that it's better to take a

499
00:28:55,920 --> 00:28:58,280
Speaker 3: bet with a ninety percent chance of winning than a

500
00:28:58,320 --> 00:29:01,600
Speaker 3: ten percent chance of winning. It also has this other function,

501
00:29:01,720 --> 00:29:03,680
Speaker 3: which is this ambiguity of version function.

502
00:29:04,320 --> 00:29:07,600
Speaker 2: Yeah, and like any toolkit, you want to use multiple

503
00:29:07,640 --> 00:29:11,640
Speaker 2: tools depending on the actual situation. If you have an

504
00:29:11,680 --> 00:29:15,360
Speaker 2: expansive toolkit and it's the screwdriver every time, even when

505
00:29:15,400 --> 00:29:18,160
Speaker 2: you need to hammer a nail, yeah, that's probably not

506
00:29:18,200 --> 00:29:20,680
Speaker 2: going to work out too well. But when you got

507
00:29:20,680 --> 00:29:23,479
Speaker 2: to screw a screw in, yeah, you know you're golden,

508
00:29:24,000 --> 00:29:26,000
Speaker 2: assuming it's the right dude ad at the end and

509
00:29:26,080 --> 00:29:27,240
Speaker 2: not one of it's not the star.

510
00:29:28,040 --> 00:29:30,480
Speaker 3: Do you go through the same one two process every

511
00:29:30,480 --> 00:29:32,640
Speaker 3: time you find a sharp screw out on the road

512
00:29:32,720 --> 00:29:35,240
Speaker 3: or on the sidewalk, where like I hit the same

513
00:29:35,280 --> 00:29:37,440
Speaker 3: two thoughts every time and be like, first of all,

514
00:29:37,480 --> 00:29:40,560
Speaker 3: it's like, ooh, pick it up, Glad somebody a child

515
00:29:40,640 --> 00:29:42,480
Speaker 3: didn't step on this or a car hit this with

516
00:29:42,560 --> 00:29:44,400
Speaker 3: their tire. And then the second thing is what did

517
00:29:44,480 --> 00:29:47,640
Speaker 3: this come out of? Was it holding something important together?

518
00:29:48,000 --> 00:29:50,200
Speaker 2: Oh? I never do the second step. I'm I always

519
00:29:50,280 --> 00:29:51,920
Speaker 2: just stick at the first step, where I'm like, oh,

520
00:29:52,000 --> 00:29:54,240
Speaker 2: glad nobody stepped on that or got that in their tire.

521
00:29:54,480 --> 00:29:57,080
Speaker 2: I have saved the day. And then I carry on.

522
00:29:57,360 --> 00:29:59,800
Speaker 3: If it's like near my house, I like, look at

523
00:29:59,800 --> 00:30:04,640
Speaker 3: my house, and I'm like, something on. I don't know.

524
00:30:05,120 --> 00:30:07,520
Speaker 2: If it's in the house, definitely, and I guess if

525
00:30:07,520 --> 00:30:09,479
Speaker 2: it's in close proximity to the house, But if it's

526
00:30:09,520 --> 00:30:13,000
Speaker 2: in the road, I'm just assuming, you know, I don't know.

527
00:30:13,040 --> 00:30:14,480
Speaker 2: I just never think about it falling out of a

528
00:30:14,560 --> 00:30:18,440
Speaker 2: vehicle in a like in a dangerous capacity. But maybe

529
00:30:18,480 --> 00:30:20,920
Speaker 2: I should. Maybe that's an additional level of worry that

530
00:30:20,960 --> 00:30:22,560
Speaker 2: I should begin to employ.

531
00:30:23,200 --> 00:30:25,480
Speaker 3: I didn't mean a vehicle specifically. I mean it might

532
00:30:25,520 --> 00:30:27,520
Speaker 3: be or a house or anything. There are all kinds

533
00:30:27,560 --> 00:30:29,760
Speaker 3: of things that really need to remain stuck together.

534
00:30:30,120 --> 00:30:32,680
Speaker 2: Yeah, I guess I just assume it's like it's work vehicles.

535
00:30:32,760 --> 00:30:35,800
Speaker 2: They have surplus screws rolling around and they're just rolling

536
00:30:35,840 --> 00:30:36,640
Speaker 2: out under the road.

537
00:30:37,440 --> 00:30:39,880
Speaker 3: Let's hope that's the case most of the time, but

538
00:30:39,920 --> 00:30:49,840
Speaker 3: I'm glad I could share that anxiety.

539
00:30:51,520 --> 00:30:53,920
Speaker 2: All Right, a few other angles we want to touch

540
00:30:53,920 --> 00:30:55,680
Speaker 2: on here. This first one. I'm not going to go

541
00:30:55,720 --> 00:30:57,320
Speaker 2: in super deep on this one because this one is

542
00:30:57,360 --> 00:31:02,880
Speaker 2: another highly economic topic, but it's a There's what's known

543
00:31:02,880 --> 00:31:05,640
Speaker 2: as the competence effect. So we've already touched on the

544
00:31:05,680 --> 00:31:07,280
Speaker 2: basics of this a little bit, but this is the

545
00:31:07,360 --> 00:31:09,640
Speaker 2: term for the phenomenon by which we tend to be

546
00:31:09,680 --> 00:31:13,400
Speaker 2: more ambiguity a verse in fields where we feel we

547
00:31:13,480 --> 00:31:18,960
Speaker 2: lack experience or expertise. In economics and finance, this manifests

548
00:31:19,000 --> 00:31:21,680
Speaker 2: in investors who are more willing to invest in familiar

549
00:31:21,720 --> 00:31:26,080
Speaker 2: domestic stocks rather than complex foreign markets. And if you're

550
00:31:26,120 --> 00:31:28,800
Speaker 2: like me, that sentence is like, yeah, well, I'm uncomfortable

551
00:31:28,800 --> 00:31:30,160
Speaker 2: with either. I don't know my way, I don't know

552
00:31:30,200 --> 00:31:32,680
Speaker 2: one from the other, so I just mark me down

553
00:31:32,680 --> 00:31:35,920
Speaker 2: as ambiguity averse to either.

554
00:31:36,720 --> 00:31:38,360
Speaker 3: But it seems to be making the point.

555
00:31:38,440 --> 00:31:42,520
Speaker 2: Yeah, but this is apparently a thing. I believe this

556
00:31:42,640 --> 00:31:44,760
Speaker 2: was first looked at in a paper by Chip Heath

557
00:31:44,800 --> 00:31:49,080
Speaker 2: and Amos Tversky titled Preference and Competence in Choice under

558
00:31:49,160 --> 00:31:51,880
Speaker 2: Uncertainty published in the Journal of Risk and Uncertainty in

559
00:31:51,960 --> 00:31:55,080
Speaker 2: ninety one, and this found that people tended to stick

560
00:31:55,120 --> 00:31:58,560
Speaker 2: to gut instincts in a familiar area versus even against

561
00:31:58,560 --> 00:32:02,040
Speaker 2: a rational, diversified approach that gets into areas they're not

562
00:32:02,080 --> 00:32:02,920
Speaker 2: that familiar with.

563
00:32:03,680 --> 00:32:06,240
Speaker 3: This rings true for me. I know I am more

564
00:32:06,400 --> 00:32:10,440
Speaker 3: ambiguity averse in domains of life that I don't understand

565
00:32:10,680 --> 00:32:14,400
Speaker 3: very well, which is funny because we have to make

566
00:32:14,480 --> 00:32:19,200
Speaker 3: decisions with ambiguous odds of success in both unfamiliar and

567
00:32:19,360 --> 00:32:24,520
Speaker 3: in familiar domains. I mean, ambiguity does not leave reality

568
00:32:24,640 --> 00:32:26,600
Speaker 3: just because you know what you're doing in a certain

569
00:32:26,680 --> 00:32:29,960
Speaker 3: knowledge domain or hobby area or something like that. Having experience.

570
00:32:30,600 --> 00:32:32,200
Speaker 3: You can have all the experience in the world and

571
00:32:32,240 --> 00:32:33,960
Speaker 3: still there are things where it's just like you don't

572
00:32:34,000 --> 00:32:37,840
Speaker 3: know what your odds are. So I think maybe the

573
00:32:37,960 --> 00:32:42,480
Speaker 3: explanation for this difference is that in the unfamiliar domains,

574
00:32:43,800 --> 00:32:49,600
Speaker 3: I'm more likely to worry that ambiguity is artificial and

575
00:32:49,680 --> 00:32:53,880
Speaker 3: that I am being tricked or manipulated by someone who

576
00:32:54,000 --> 00:32:59,040
Speaker 3: has superior knowledge of that domain, whereas in familiar situations,

577
00:33:00,120 --> 00:33:03,600
Speaker 3: understand what amount of information it is normal to have

578
00:33:04,200 --> 00:33:07,720
Speaker 3: and thus how much ambiguity is just natural and unavoidable,

579
00:33:08,080 --> 00:33:11,360
Speaker 3: and thus the ambiguity that is there becomes easier to embrace.

580
00:33:12,440 --> 00:33:13,240
Speaker 3: Does that make sense?

581
00:33:13,560 --> 00:33:16,680
Speaker 2: Yeah? Yeah, And of course all this ends up coming

582
00:33:16,720 --> 00:33:19,600
Speaker 2: back to the topic of not only like what do

583
00:33:19,640 --> 00:33:21,320
Speaker 2: you know, but what do you not know? And what

584
00:33:21,360 --> 00:33:23,880
Speaker 2: do you think that you know that you actually don't know.

585
00:33:25,400 --> 00:33:27,400
Speaker 2: We've talked about this before on the show, and it

586
00:33:27,440 --> 00:33:29,480
Speaker 2: always reminds me of a line. I had to look

587
00:33:29,520 --> 00:33:31,320
Speaker 2: this up. I'd forgotten the source, but it was from

588
00:33:31,360 --> 00:33:33,840
Speaker 2: the movie Body Heat. You have a characters played by

589
00:33:33,920 --> 00:33:36,880
Speaker 2: Mickey Rourke. He says that, and this is a I'm

590
00:33:36,920 --> 00:33:38,720
Speaker 2: going to paraphrase the quote a little bit. He says,

591
00:33:38,720 --> 00:33:41,000
Speaker 2: anytime you try to commit a crime, they are about

592
00:33:41,040 --> 00:33:42,880
Speaker 2: fifty ways that you could mess up, and if you

593
00:33:42,880 --> 00:33:46,800
Speaker 2: can think of twenty five of them, you're a genius. Now.

594
00:33:46,800 --> 00:33:48,800
Speaker 2: I don't know if those numbers are exact, but I

595
00:33:48,880 --> 00:33:52,080
Speaker 2: like the spirit of the thing, you know, Like he's saying,

596
00:33:52,120 --> 00:33:55,120
Speaker 2: You're going into a situation and you have this great

597
00:33:55,560 --> 00:33:58,400
Speaker 2: degree of overconfidence. You don't realize all of the ways

598
00:33:58,400 --> 00:34:02,680
Speaker 2: you could potentially fail, and nobody can have perfect knowledge,

599
00:34:02,680 --> 00:34:05,280
Speaker 2: like you know, this is a quote that does recognize

600
00:34:05,280 --> 00:34:07,520
Speaker 2: that there will always be a certain amount of ambiguity.

601
00:34:08,520 --> 00:34:12,880
Speaker 2: But if you have expertise, that sort of cloud of

602
00:34:12,920 --> 00:34:14,960
Speaker 2: ambiguity is going to be smaller. It's not going to

603
00:34:14,960 --> 00:34:17,600
Speaker 2: go away completely, but it will be smaller.

604
00:34:17,840 --> 00:34:19,160
Speaker 3: Well, I think yeah, and I think this.

605
00:34:19,520 --> 00:34:19,759
Speaker 2: Yeah.

606
00:34:19,800 --> 00:34:22,880
Speaker 3: The spirit of the quote is that like people often

607
00:34:22,920 --> 00:34:25,400
Speaker 3: go into a crime thinking they're betting on red, that

608
00:34:25,440 --> 00:34:28,120
Speaker 3: they're taking a known risk, when in fact they're actually

609
00:34:28,320 --> 00:34:31,560
Speaker 3: they're going into an ambiguous risk where they don't understand

610
00:34:31,560 --> 00:34:32,719
Speaker 3: how much risk there is.

611
00:34:33,800 --> 00:34:38,520
Speaker 2: So anyway minor cinematic diversion, there now another higher stakes

612
00:34:38,640 --> 00:34:43,960
Speaker 2: area for the individual concerning ambiguity and ambiguity. Aversion is

613
00:34:44,000 --> 00:34:48,160
Speaker 2: how ambiguity often factors into the healthcare experience. I was

614
00:34:48,200 --> 00:34:52,880
Speaker 2: reading about this. So there are two broad categories within healthcare.

615
00:34:52,880 --> 00:34:57,239
Speaker 2: There's diagnostic ambiguity, this is where the underlying disease. There's

616
00:34:57,280 --> 00:35:00,560
Speaker 2: ambiguity surrounding the underlying disease and how it works. And

617
00:35:00,600 --> 00:35:03,560
Speaker 2: then there's therapeutic ambiguity, like how do we treat it

618
00:35:03,680 --> 00:35:06,080
Speaker 2: or even cure it, and I imagine a lot of

619
00:35:06,080 --> 00:35:09,919
Speaker 2: you out there have encountered examples of this. In these

620
00:35:09,960 --> 00:35:14,160
Speaker 2: different ambiguities can lead to rather opposite choices, But due

621
00:35:14,160 --> 00:35:17,000
Speaker 2: to ambiguity aversion, a patient might choose a treatment with

622
00:35:17,160 --> 00:35:21,200
Speaker 2: known but terrible side effects over one with the chance of, say,

623
00:35:21,239 --> 00:35:23,600
Speaker 2: a better outcome, but also unknown risks.

624
00:35:24,440 --> 00:35:27,120
Speaker 3: Or because of ambiguity aversion, I think very often in

625
00:35:27,160 --> 00:35:32,799
Speaker 3: healthcare will gravitate towards someone who offers them false certainty

626
00:35:33,040 --> 00:35:38,160
Speaker 3: versus someone who is honestly communicating like unknowns about the

627
00:35:38,239 --> 00:35:38,960
Speaker 3: level of risk.

628
00:35:39,560 --> 00:35:43,120
Speaker 2: Yeah, communication is key, and this becomes important in a

629
00:35:43,200 --> 00:35:46,120
Speaker 2: number of different ways. You know, is an impact of

630
00:35:46,160 --> 00:35:50,240
Speaker 2: course on public health and highlights the importance of science,

631
00:35:50,239 --> 00:35:53,400
Speaker 2: communication and healthcare, as well as the dangers of medical

632
00:35:53,480 --> 00:35:58,520
Speaker 2: misinformation and conspiracy thinking. For instance, in the context of vaccination,

633
00:35:59,040 --> 00:36:01,960
Speaker 2: ambiguity a version and can definitely take the form of

634
00:36:02,120 --> 00:36:06,399
Speaker 2: vaccine hesitancy. And I want to stress again here that

635
00:36:06,440 --> 00:36:10,600
Speaker 2: the ambiguity need only be perceived ambiguity. So if one

636
00:36:10,640 --> 00:36:13,399
Speaker 2: has already bought into such statements, says, well, no one

637
00:36:13,400 --> 00:36:16,080
Speaker 2: really knows how what these vaccines are, or no one

638
00:36:16,160 --> 00:36:20,160
Speaker 2: really knows how they work. Just assuming that those statements

639
00:36:20,239 --> 00:36:23,560
Speaker 2: are true, there's some large degree of truth to them,

640
00:36:23,920 --> 00:36:28,000
Speaker 2: then there may be well enough ambiguity subjective ambiguity in

641
00:36:28,080 --> 00:36:31,960
Speaker 2: place in the individual's mind to make them rather adverse

642
00:36:32,160 --> 00:36:35,720
Speaker 2: to this perceived ambiguity and more likely to choose options

643
00:36:35,760 --> 00:36:39,400
Speaker 2: that bring with them greater risk. But more of a

644
00:36:39,560 --> 00:36:45,680
Speaker 2: communicated idea of certainty, like dubious alternative preventative and treatment methods,

645
00:36:45,840 --> 00:36:47,759
Speaker 2: or just the idea of doing nothing at all.

646
00:36:47,880 --> 00:36:49,960
Speaker 3: The body knows how to take care of itself, that

647
00:36:50,080 --> 00:36:52,920
Speaker 3: kind of thinking, Yeah, which sounds very certain when delivered

648
00:36:52,960 --> 00:36:54,840
Speaker 3: by a confident and charismatic speaker.

649
00:36:55,160 --> 00:36:57,880
Speaker 2: Yeah. I was looking at a paper in Behavioral Medicine

650
00:36:57,880 --> 00:37:03,320
Speaker 2: from earlier this year, Psychological Correlates of ambiguity aversion in

651
00:37:03,440 --> 00:37:07,680
Speaker 2: the contest of COVID nineteen vaccination, And this was by

652
00:37:08,239 --> 00:37:13,200
Speaker 2: Somanovic at All, and they found four different major takeaways

653
00:37:13,200 --> 00:37:16,080
Speaker 2: here that I thought were interesting. They found that Americans

654
00:37:16,120 --> 00:37:20,560
Speaker 2: who perceived higher ambiguity about COVID nineteen vaccines reported lower

655
00:37:20,600 --> 00:37:24,440
Speaker 2: worry and lower perceived severity of COVID nineteen, which were

656
00:37:24,440 --> 00:37:28,480
Speaker 2: each associated with lower vaccination intentions and lower information seeking

657
00:37:29,560 --> 00:37:31,600
Speaker 2: about COVID nineteen vaccines.

658
00:37:31,719 --> 00:37:34,560
Speaker 3: Okay, So if I'm understanding that, right, Americans who had

659
00:37:34,960 --> 00:37:39,560
Speaker 3: lower confidence in the efficacy and safety of COVID vaccines

660
00:37:40,000 --> 00:37:43,880
Speaker 3: were also for whatever reason, less worried about covid infection.

661
00:37:45,040 --> 00:37:47,799
Speaker 2: Right. But at the same time, they were also just

662
00:37:48,120 --> 00:37:50,160
Speaker 2: they were obvious, And this is kind of a no brainer, right,

663
00:37:50,200 --> 00:37:52,600
Speaker 2: It would seemed to follow they would be less inclined

664
00:37:52,800 --> 00:37:56,080
Speaker 2: to have any intention of being vaccinated, and then would

665
00:37:56,080 --> 00:37:59,600
Speaker 2: be less inclined to seek out any information about said vaccinations.

666
00:38:00,200 --> 00:38:02,200
Speaker 2: Their mind at this point is already kind of made up.

667
00:38:02,360 --> 00:38:04,520
Speaker 3: Well, I think that's right, But it's also interesting to

668
00:38:04,920 --> 00:38:10,240
Speaker 3: note like the counterintuitive ways forms that having your mind

669
00:38:10,360 --> 00:38:12,600
Speaker 3: made up in this way can take, because sometimes the

670
00:38:12,640 --> 00:38:15,320
Speaker 3: way that I think that is expressed is like sometimes

671
00:38:15,400 --> 00:38:17,520
Speaker 3: it's just a statement of like, oh, yeah, nobody knows,

672
00:38:17,560 --> 00:38:20,000
Speaker 3: nobody can know about the vaccines, and so it just

673
00:38:20,040 --> 00:38:25,279
Speaker 3: becomes like this infinitely and unsolvably dangerous thing out there

674
00:38:25,400 --> 00:38:27,920
Speaker 3: that you know, nobody you can never really have confidence

675
00:38:27,960 --> 00:38:30,200
Speaker 3: in your mind is made up about it, but it's

676
00:38:30,280 --> 00:38:32,680
Speaker 3: made up in a way that always just sort of

677
00:38:32,719 --> 00:38:35,080
Speaker 3: like holds it as an unresolved danger.

678
00:38:35,680 --> 00:38:41,000
Speaker 2: Yeah, yeah, yeah, And I'm sure that the individuals on

679
00:38:41,000 --> 00:38:43,479
Speaker 2: that side of the argument might well make the counter

680
00:38:43,600 --> 00:38:46,000
Speaker 2: argument that like, okay, well, people who trust in the vaccine,

681
00:38:46,000 --> 00:38:47,880
Speaker 2: they're just they trust blindly. They've just made up their

682
00:38:47,920 --> 00:38:50,720
Speaker 2: mind and they're not going to listen to any of

683
00:38:49,520 --> 00:38:53,120
Speaker 2: the criticisms. And I mean, I disagree with that. But

684
00:38:53,160 --> 00:38:57,320
Speaker 2: on the other hand, you know, I feel like, speaking personally,

685
00:38:57,400 --> 00:38:59,800
Speaker 2: like I can't be like I'm not going to pretend

686
00:38:59,840 --> 00:39:02,520
Speaker 2: to be like doctor Robert all the time where I'm

687
00:39:02,520 --> 00:39:04,960
Speaker 2: making all of all of these I'm doing all my

688
00:39:05,000 --> 00:39:08,719
Speaker 2: own research on you know, like health and dental concerns.

689
00:39:08,760 --> 00:39:11,640
Speaker 2: Like ultimately, I have to trust in a professional who

690
00:39:12,320 --> 00:39:15,120
Speaker 2: knows what they're doing and is certified in what they're

691
00:39:15,160 --> 00:39:18,239
Speaker 2: doing and leave it to them to tell me what

692
00:39:18,360 --> 00:39:21,040
Speaker 2: I should do, because I don't want to have all

693
00:39:21,080 --> 00:39:23,279
Speaker 2: these decisions on me. I don't want to do my

694
00:39:23,719 --> 00:39:26,200
Speaker 2: own research on everything. I've got enough research to do

695
00:39:26,239 --> 00:39:27,399
Speaker 2: in and out during the week.

696
00:39:27,840 --> 00:39:30,759
Speaker 3: Well, I mean about like medical matters. When people say

697
00:39:30,800 --> 00:39:34,400
Speaker 3: do your own research ninety nine point whatever percent of

698
00:39:34,440 --> 00:39:37,080
Speaker 3: the time, somebody who says that either is not doing

699
00:39:37,080 --> 00:39:39,680
Speaker 3: any research at all, and that just means go with

700
00:39:39,719 --> 00:39:42,360
Speaker 3: your gut feeling, or if they are doing research, it

701
00:39:42,640 --> 00:39:45,560
Speaker 3: just means doing very bad research. It means relying on

702
00:39:46,680 --> 00:39:49,360
Speaker 3: sources that you have no objective reason for thinking or

703
00:39:49,400 --> 00:39:53,360
Speaker 3: giving you good information, and probably are just confirming your priors.

704
00:39:53,520 --> 00:39:57,360
Speaker 2: Yeah, like I choose to research my health topic by

705
00:39:57,480 --> 00:39:59,200
Speaker 2: picking up chariots of the gods.

706
00:39:59,560 --> 00:40:02,720
Speaker 3: Yeah, I mean I would argue, of course, like doctors

707
00:40:02,719 --> 00:40:05,560
Speaker 3: and healthcare professionals can be wrong. That's possible, and it

708
00:40:05,560 --> 00:40:08,000
Speaker 3: happens all the time. But I think on average, you're

709
00:40:08,000 --> 00:40:10,040
Speaker 3: going to do a lot better just like listening to

710
00:40:10,120 --> 00:40:13,200
Speaker 3: doctors than like reading a Facebook post and then making

711
00:40:13,280 --> 00:40:14,680
Speaker 3: up your own mind about medicine.

712
00:40:15,080 --> 00:40:18,239
Speaker 2: Yeah. So this particular paper, I'm going to breathe through

713
00:40:18,280 --> 00:40:20,600
Speaker 2: the other main bullet points. Basically, they came down to

714
00:40:20,719 --> 00:40:24,239
Speaker 2: people who perceived higher ambiguity about COVID nineteen vaccines. They

715
00:40:24,600 --> 00:40:29,520
Speaker 2: reported higher anger about COVID nineteen vaccines, which was associated

716
00:40:29,520 --> 00:40:33,120
Speaker 2: with lower perceived severity of COVID nineteen. They reported lower

717
00:40:33,160 --> 00:40:36,040
Speaker 2: happiness about the vaccines, which was associated with both lower

718
00:40:36,080 --> 00:40:39,799
Speaker 2: worry and lower perceived a severity of COVID nineteen. And

719
00:40:40,160 --> 00:40:42,560
Speaker 2: they also found that both Americans and Israelis who were

720
00:40:42,600 --> 00:40:45,080
Speaker 2: looked at in the study who perceived higher ambiguity about

721
00:40:45,080 --> 00:40:48,560
Speaker 2: COVID nineteen vaccines, reported lower feelings of relaxation from the

722
00:40:48,560 --> 00:40:52,239
Speaker 2: COVID nineteen vaccine, which was associated with lower perceived severity

723
00:40:52,400 --> 00:40:53,680
Speaker 2: of the illness itself.

724
00:40:53,960 --> 00:40:57,280
Speaker 3: So you have these constellations of different tendencies acting together.

725
00:40:57,480 --> 00:41:01,480
Speaker 3: You've got like a lower confidence of lower trust in

726
00:41:02,600 --> 00:41:06,360
Speaker 3: a healthcare treatment that also seems to go along with

727
00:41:06,560 --> 00:41:12,320
Speaker 3: having a lower concern or lower level of seriousness about

728
00:41:12,360 --> 00:41:15,719
Speaker 3: the condition that that treatment is supposed to treat, less

729
00:41:15,719 --> 00:41:19,239
Speaker 3: emotional positivity about the idea of taking the treatment, and

730
00:41:20,000 --> 00:41:23,399
Speaker 3: all of this together. So it I mean, well, one

731
00:41:23,400 --> 00:41:26,520
Speaker 3: thing this sort of suggests to me is that, of

732
00:41:26,560 --> 00:41:29,640
Speaker 3: course this is obvious, but it just reminds us that

733
00:41:30,080 --> 00:41:34,120
Speaker 3: when we are making decisions, we do, to some extent

734
00:41:34,200 --> 00:41:37,120
Speaker 3: try to make rational decisions based on our beliefs, but

735
00:41:37,160 --> 00:41:40,120
Speaker 3: we're also just like highly emotional creatures, and our decision

736
00:41:40,160 --> 00:41:45,680
Speaker 3: making is deeply entangled with feelings we have about the

737
00:41:45,719 --> 00:41:48,319
Speaker 3: things we're making decisions about. You know, it's not really

738
00:41:48,360 --> 00:41:51,839
Speaker 3: possible for us to approach every decision in life as

739
00:41:51,920 --> 00:41:55,960
Speaker 3: just like purely like odds and benefit maximizing machines. Like

740
00:41:56,000 --> 00:41:58,719
Speaker 3: we have feelings about things and those feelings, whether we

741
00:41:58,800 --> 00:42:00,920
Speaker 3: want them to or not do, influence the way we

742
00:42:00,960 --> 00:42:01,680
Speaker 3: make decisions.

743
00:42:01,800 --> 00:42:04,480
Speaker 2: Yeah, and they will, they will override reason and and

744
00:42:04,560 --> 00:42:06,400
Speaker 2: all of us, all of us, is susceptible to this

745
00:42:06,440 --> 00:42:10,080
Speaker 2: sort of thing. But yeah, another way that it's I

746
00:42:10,080 --> 00:42:12,279
Speaker 2: think it's interesting and dreadful to think about all of

747
00:42:12,280 --> 00:42:16,400
Speaker 2: this is that is that again, there's generally some degree

748
00:42:16,400 --> 00:42:22,000
Speaker 2: of ambiguity with both medical diagnognosis and medical treatment. And

749
00:42:22,200 --> 00:42:23,919
Speaker 2: I can say I can speak from experience, and again

750
00:42:23,960 --> 00:42:26,560
Speaker 2: most of you can can can relate to this as well.

751
00:42:26,800 --> 00:42:28,760
Speaker 2: It can be frustrating when you go to a doctor

752
00:42:28,920 --> 00:42:31,000
Speaker 2: and instead of a clear course of action that you

753
00:42:31,080 --> 00:42:34,600
Speaker 2: might want or a definite solution that you are seeking,

754
00:42:34,640 --> 00:42:37,360
Speaker 2: you instead get a certain amount of ambiguity about what

755
00:42:37,480 --> 00:42:40,439
Speaker 2: might be wrong and how it might be addressed. Because

756
00:42:40,480 --> 00:42:41,839
Speaker 2: at the end of the day, I think we all

757
00:42:41,920 --> 00:42:46,200
Speaker 2: want the Star Trek medical tricorder experience where someone's able

758
00:42:46,200 --> 00:42:49,399
Speaker 2: to just scan us, perfect scan, see what ails us,

759
00:42:49,760 --> 00:42:51,880
Speaker 2: and then tell us exactly what needs they need to

760
00:42:51,880 --> 00:42:53,960
Speaker 2: do to fix this, probably with another device that they

761
00:42:54,040 --> 00:42:56,000
Speaker 2: just kind of run up and down our body. But

762
00:42:56,200 --> 00:42:59,279
Speaker 2: even with today's technology, it's it's more complex than that.

763
00:42:59,360 --> 00:43:03,520
Speaker 2: In most cases, Meanwhile, where do we actually encounter this

764
00:43:03,680 --> 00:43:07,240
Speaker 2: lack of ambiguity in the messaging? Again, it comes generally

765
00:43:07,320 --> 00:43:10,440
Speaker 2: in different forms of alternative medicine, or in snake oils

766
00:43:10,840 --> 00:43:15,280
Speaker 2: or conspiracy thinking, because none of these voices ever says, look,

767
00:43:15,480 --> 00:43:18,080
Speaker 2: there's absolutely no evidence this works, but give it a shot,

768
00:43:18,200 --> 00:43:20,719
Speaker 2: or we can't know for sure if lizard people run

769
00:43:20,800 --> 00:43:26,200
Speaker 2: a secret government in Antarctica. But there's always plenty of

770
00:43:26,239 --> 00:43:29,319
Speaker 2: ambiguity in their evidence, of course, if supplied at all,

771
00:43:29,640 --> 00:43:33,200
Speaker 2: but you'll often find them maneuvering around that in their messaging,

772
00:43:33,239 --> 00:43:37,520
Speaker 2: which again is low on ambiguity and high uncertainty. And

773
00:43:37,719 --> 00:43:42,080
Speaker 2: like you mentioned earlier, when it comes to legitimate medical messaging,

774
00:43:42,160 --> 00:43:45,640
Speaker 2: it tends to communicate both probability and risk. You'll get

775
00:43:45,960 --> 00:43:48,160
Speaker 2: that list of fast talk side effects at the end

776
00:43:48,160 --> 00:43:53,879
Speaker 2: of your advertisement for an actual certified medication, And again

777
00:43:53,920 --> 00:43:58,400
Speaker 2: this is just the inherent uncertainty in even very modern medicine.

778
00:44:07,600 --> 00:44:10,880
Speaker 2: Another paper I looked at was twenty twenty two's Vaccine

779
00:44:10,920 --> 00:44:15,040
Speaker 2: Hesitancy and Cognitive Biases by Kassigliami at All, and this

780
00:44:15,080 --> 00:44:19,080
Speaker 2: points out that vaccination education strategies long followed a fact

781
00:44:19,080 --> 00:44:23,440
Speaker 2: based approach, but given our aversion to ambiguity, along with

782
00:44:23,560 --> 00:44:28,480
Speaker 2: bias and other heuristics. These various cognitive biases in messaging

783
00:44:28,840 --> 00:44:31,200
Speaker 2: have to be factored into the outreach, and of course

784
00:44:31,360 --> 00:44:34,359
Speaker 2: this gets into the complex way in which public health

785
00:44:34,360 --> 00:44:37,720
Speaker 2: and vaccine messaging have to attempt to counteract all the noise,

786
00:44:38,880 --> 00:44:42,640
Speaker 2: sometimes by leaning more on empathetic and audience based approaches

787
00:44:42,760 --> 00:44:45,960
Speaker 2: rather than fact based debate, because again, in many cases,

788
00:44:46,000 --> 00:44:50,400
Speaker 2: the actual medical facts have baked in ambiguity, while the

789
00:44:50,480 --> 00:44:54,479
Speaker 2: non scientific counter claims do not. You know, it's again,

790
00:44:54,520 --> 00:44:58,960
Speaker 2: this is absolutely frustrating and increasingly dangerous, an increasingly dangerous

791
00:44:58,960 --> 00:45:02,600
Speaker 2: part of our reality. But yeah, the voice saying that

792
00:45:03,120 --> 00:45:05,840
Speaker 2: the vaccine has microchips in it that will turn you

793
00:45:05,880 --> 00:45:08,960
Speaker 2: into robots, like, you know, there's no ambiguity to that statement.

794
00:45:09,000 --> 00:45:12,759
Speaker 2: They're generally, it's generally very they're very clear. Uh, they're

795
00:45:12,840 --> 00:45:18,279
Speaker 2: very certain in it. Whereas again, actual medical facts and

796
00:45:18,440 --> 00:45:22,400
Speaker 2: actual medicine based arguments are going to have some level

797
00:45:22,440 --> 00:45:24,440
Speaker 2: of ambiguity in their messaging.

798
00:45:24,840 --> 00:45:27,759
Speaker 3: This is one of the things that makes communication about

799
00:45:27,840 --> 00:45:31,160
Speaker 3: science generally, but especially about something very high stakes like

800
00:45:31,160 --> 00:45:34,839
Speaker 3: like medical you know, medical science, medical treatments, makes it

801
00:45:34,960 --> 00:45:38,640
Speaker 3: so difficult just because you have to You have to

802
00:45:38,680 --> 00:45:41,600
Speaker 3: find this very difficult balance of like you you are

803
00:45:41,640 --> 00:45:45,640
Speaker 3: compelled ethically to be forthright and honest about what you know,

804
00:45:46,200 --> 00:45:48,120
Speaker 3: but you also have to wait to find a way

805
00:45:48,160 --> 00:45:51,319
Speaker 3: to present that truth in a way that will be

806
00:45:51,560 --> 00:45:56,640
Speaker 3: rhetorically effective and hit correctly. And uh, and that's so,

807
00:45:56,760 --> 00:45:59,640
Speaker 3: like you are balancing things that somebody who is not

808
00:46:00,160 --> 00:46:03,360
Speaker 3: bound by an obligation to be ethical and honest is

809
00:46:03,400 --> 00:46:06,120
Speaker 3: not bound like they can only focus on the rhetorical

810
00:46:06,160 --> 00:46:08,439
Speaker 3: part of the appeal, Like all they have to worry

811
00:46:08,480 --> 00:46:12,160
Speaker 3: about is what I'm saying exciting and charismatic and convincing.

812
00:46:13,600 --> 00:46:15,760
Speaker 3: They don't have the other side of the scale to balance.

813
00:46:16,200 --> 00:46:20,000
Speaker 2: That's right, that's right. And obviously this easily spills over

814
00:46:20,200 --> 00:46:26,000
Speaker 2: into other areas, you know, pseudo archaeology, pseudo paleontology, other pseudosciences,

815
00:46:26,120 --> 00:46:31,759
Speaker 2: alternative history, ufology, and more, because, as we I think

816
00:46:31,920 --> 00:46:35,720
Speaker 2: really strive to drive home and related episodes on this show,

817
00:46:36,360 --> 00:46:42,160
Speaker 2: actual history and archaeology inherently contain ambiguity. Like all histories are,

818
00:46:42,640 --> 00:46:44,960
Speaker 2: to some degree or another, imperfect. Some are just more

819
00:46:45,000 --> 00:46:48,400
Speaker 2: imperfect than others. You know, you know, as much as

820
00:46:48,440 --> 00:46:50,359
Speaker 2: we know about certain periods of the past and certain

821
00:46:50,400 --> 00:46:53,240
Speaker 2: individuals and events. We still have gaps, we have disagreements

822
00:46:53,280 --> 00:46:58,800
Speaker 2: about interpretations, we have uncertainties, and then we I'm reminded

823
00:46:58,800 --> 00:47:04,600
Speaker 2: too of particularly Alan Moore's use of the the Cox snowflake.

824
00:47:04,680 --> 00:47:08,279
Speaker 2: That's koc h in nineteen eighty Nine's from Hell, his

825
00:47:08,400 --> 00:47:13,480
Speaker 2: graphic novel about Jack the Ripper. So, the Cox snowflake

826
00:47:13,560 --> 00:47:16,840
Speaker 2: is a fractal curve that was first described by Neil's

827
00:47:16,880 --> 00:47:20,680
Speaker 2: Fabian Helga von Kock in nineteen oh four. The idea

828
00:47:20,680 --> 00:47:23,000
Speaker 2: here is that it has a finite area but an

829
00:47:23,040 --> 00:47:30,040
Speaker 2: infinitely long perimeter, so lots of cremulations. And Moore's treatment

830
00:47:30,080 --> 00:47:33,800
Speaker 2: of this is that history has a shape with infinite

831
00:47:33,960 --> 00:47:38,960
Speaker 2: perimeter and finite area, a labyrinth of connections and repeated patterns,

832
00:47:39,000 --> 00:47:42,360
Speaker 2: but that we never fully comprehend. Ah.

833
00:47:42,360 --> 00:47:45,359
Speaker 3: That's interesting. So if I understand that right, it sort

834
00:47:45,360 --> 00:47:49,080
Speaker 3: of explains why as you read more about history and

835
00:47:49,160 --> 00:47:53,040
Speaker 3: learn more about history, you can, by incorporating more and

836
00:47:53,080 --> 00:47:55,560
Speaker 3: more knowledge and holding it, you know, parallel in your mind,

837
00:47:56,000 --> 00:47:59,520
Speaker 3: you can have in some ways a stronger and realer

838
00:47:59,560 --> 00:48:04,359
Speaker 3: picture of the past. But also the the increasing informational

839
00:48:04,440 --> 00:48:10,040
Speaker 3: complexity it makes everything increasingly blurry as well, like you're

840
00:48:10,080 --> 00:48:14,759
Speaker 3: always finding it becomes harder to have it becomes harder

841
00:48:14,800 --> 00:48:18,360
Speaker 3: to have like causal through lines and clear narratives about

842
00:48:18,360 --> 00:48:20,840
Speaker 3: why history happens, because the more you know, the more

843
00:48:21,280 --> 00:48:25,120
Speaker 3: other causal factors you can consider when thinking about, like

844
00:48:25,160 --> 00:48:28,319
Speaker 3: why something happened in history. And ultimately it gets to

845
00:48:28,320 --> 00:48:31,200
Speaker 3: the point where it's so complex that it's like who

846
00:48:31,200 --> 00:48:32,440
Speaker 3: knows why anything happened?

847
00:48:32,760 --> 00:48:35,160
Speaker 2: Right, right? And that was his point about like who

848
00:48:35,280 --> 00:48:37,839
Speaker 2: was Jack the Ripper? You know, you can we end

849
00:48:37,920 --> 00:48:40,160
Speaker 2: up with all of these just so many books, so

850
00:48:40,239 --> 00:48:44,520
Speaker 2: many theories, so much literature and writing and conspiracy theories

851
00:48:44,520 --> 00:48:46,920
Speaker 2: and so forth, and for the most part, it's all

852
00:48:46,960 --> 00:48:50,080
Speaker 2: within the confines of that snowflake. The actual answer is

853
00:48:50,120 --> 00:48:52,520
Speaker 2: outside the snowflake. You know, we can never we can

854
00:48:52,520 --> 00:48:56,920
Speaker 2: never actually determine it with any degree of accuracy, just

855
00:48:56,960 --> 00:49:03,560
Speaker 2: be conjecture. So you know. At the same time, conspiracy

856
00:49:03,560 --> 00:49:06,560
Speaker 2: thinking itself engages in something akin to the cock snowflake,

857
00:49:06,600 --> 00:49:09,360
Speaker 2: you know, because there's it's it's often an infinite search

858
00:49:09,400 --> 00:49:11,799
Speaker 2: for hidden details, whether those details are there or not.

859
00:49:12,239 --> 00:49:15,239
Speaker 2: But still the basic premise holds true. Actual history is complex.

860
00:49:15,560 --> 00:49:18,960
Speaker 2: While the narrative provided by conspiracy thinking is generally simple

861
00:49:19,280 --> 00:49:22,160
Speaker 2: and single track, leading to a singular force at the

862
00:49:22,160 --> 00:49:26,840
Speaker 2: center of the entire conspiracy. Like it will be. It

863
00:49:26,880 --> 00:49:28,919
Speaker 2: will be more akin to like why did this happen? Well,

864
00:49:28,920 --> 00:49:32,200
Speaker 2: it's this evil cabal or this you know evil you

865
00:49:32,239 --> 00:49:36,200
Speaker 2: know corporation leader and so forth, as opposed to well,

866
00:49:36,239 --> 00:49:40,640
Speaker 2: there are multiple societal factors and historical anomalies that play

867
00:49:40,680 --> 00:49:46,280
Speaker 2: into this particular reality. And again, more ambiguity in real life,

868
00:49:46,640 --> 00:49:51,840
Speaker 2: less ambiguity or no ambiguity at all in the conspiracy argument. Yeah,

869
00:49:52,000 --> 00:49:54,080
Speaker 2: comes back to it's like stocks. You know, I don't

870
00:49:54,120 --> 00:49:55,640
Speaker 2: know anything about stocks, but I know that when I

871
00:49:55,719 --> 00:49:58,880
Speaker 2: see that little advertisement at the bottom of a blog

872
00:49:58,960 --> 00:50:03,360
Speaker 2: where and there's a picture of like an old person smiling,

873
00:50:03,400 --> 00:50:06,319
Speaker 2: and it's like, this is a surefire bet stock that

874
00:50:06,440 --> 00:50:08,760
Speaker 2: so and so has just identified, It's like, I'm instantly

875
00:50:08,840 --> 00:50:12,600
Speaker 2: suspicious because it seems a little bit too good to

876
00:50:12,600 --> 00:50:15,680
Speaker 2: be true. It seems like there's not much ambiguity to

877
00:50:15,719 --> 00:50:20,160
Speaker 2: this particular suggestion would be a risky click. All right,

878
00:50:20,200 --> 00:50:22,319
Speaker 2: one more area I want to touch here, because I

879
00:50:22,360 --> 00:50:26,680
Speaker 2: was looking at a really recent paper on ambiguity a version. Okay,

880
00:50:26,680 --> 00:50:31,120
Speaker 2: here's a hypothetical scenario. You're considering a couple of vacation options,

881
00:50:31,280 --> 00:50:33,759
Speaker 2: and we'll assume for the purposes of this experiment that

882
00:50:34,200 --> 00:50:37,480
Speaker 2: the cost and other matters are equal. Here, one is

883
00:50:37,520 --> 00:50:40,280
Speaker 2: a trip to a family vacation destination that you've visited

884
00:50:40,360 --> 00:50:44,120
Speaker 2: numerous times before, and the other is an entirely new experience.

885
00:50:44,200 --> 00:50:46,600
Speaker 2: Maybe it's visiting a country you've never traveled to, or

886
00:50:46,640 --> 00:50:50,040
Speaker 2: something of that nature. And then, as you're making up

887
00:50:50,080 --> 00:50:52,719
Speaker 2: your mind, what do you do? You flip on the

888
00:50:52,719 --> 00:50:57,040
Speaker 2: news and surprise, surprise, it's all negative. It's all traveling.

889
00:50:57,920 --> 00:51:01,640
Speaker 2: Would this exposure to negative news influence your decision making

890
00:51:01,680 --> 00:51:05,319
Speaker 2: and push you toward the less ambiguous choice, or would

891
00:51:05,360 --> 00:51:09,680
Speaker 2: you still basically make your decision as if you would

892
00:51:09,840 --> 00:51:11,600
Speaker 2: have if you didn't watch the news at all.

893
00:51:12,239 --> 00:51:14,600
Speaker 3: Well, I guess it could go multiple ways. But yeah,

894
00:51:14,640 --> 00:51:19,080
Speaker 3: I would tend to assume that increasing my anxiety would

895
00:51:19,160 --> 00:51:22,440
Speaker 3: make me more ambiguity averse, and that I would be

896
00:51:22,719 --> 00:51:28,600
Speaker 3: seeking more known odds and familiar experiences if my anxiety

897
00:51:28,680 --> 00:51:29,520
Speaker 3: levels are higher.

898
00:51:30,719 --> 00:51:33,440
Speaker 2: Yeah, yeah, you know, prior to reading this paper, I

899
00:51:33,520 --> 00:51:36,560
Speaker 2: might have jumped at this thinking as well. I have

900
00:51:36,760 --> 00:51:39,200
Speaker 2: very rarely altered travel plan to do to something I

901
00:51:39,280 --> 00:51:40,960
Speaker 2: saw in the news. But I'll be the first to

902
00:51:41,000 --> 00:51:43,560
Speaker 2: admit that news items can rattle my resolve with pet

903
00:51:43,600 --> 00:51:46,080
Speaker 2: you know, they can make me more anxious. So I

904
00:51:46,120 --> 00:51:48,759
Speaker 2: would have guessed, yeah, negative news can surely push one

905
00:51:48,760 --> 00:51:51,920
Speaker 2: away from risk, away from ambiguity, and back into the familiar,

906
00:51:52,040 --> 00:51:54,960
Speaker 2: and more to the point, might be likely to do

907
00:51:55,040 --> 00:51:55,920
Speaker 2: so on the whole.

908
00:51:56,520 --> 00:51:58,200
Speaker 3: Now, one of the only things I would think that

909
00:51:58,400 --> 00:52:00,239
Speaker 3: might push me back in the other direction and is

910
00:52:00,280 --> 00:52:04,280
Speaker 3: a finding we talked about in the previous episode where essentially,

911
00:52:04,440 --> 00:52:11,759
Speaker 3: if the known odds are bad, people's ambiguity aversion to

912
00:52:11,960 --> 00:52:15,480
Speaker 3: take the other bet lessons right. So, like in the

913
00:52:15,800 --> 00:52:18,920
Speaker 3: three color Earn experiment, if instead of thirty red balls

914
00:52:18,960 --> 00:52:22,320
Speaker 3: there are like five red balls, people at that point

915
00:52:22,360 --> 00:52:25,640
Speaker 3: become more likely to bet on black because it's like, well,

916
00:52:25,760 --> 00:52:28,560
Speaker 3: the odds of the thing you know about are terrible,

917
00:52:29,000 --> 00:52:32,680
Speaker 3: so why not take a gamble on something else? So

918
00:52:33,239 --> 00:52:36,120
Speaker 3: I wonder maybe if that could push you back the

919
00:52:36,160 --> 00:52:40,160
Speaker 3: other way. Like my intuition is that anxiety makes you

920
00:52:40,239 --> 00:52:43,200
Speaker 3: more ambiguity averse and just want to go with something

921
00:52:43,280 --> 00:52:46,400
Speaker 3: where the odds are clear, But maybe anxiety makes you

922
00:52:46,480 --> 00:52:50,880
Speaker 3: believe that Like essentially the odds of stasis are really bad,

923
00:52:51,280 --> 00:52:53,480
Speaker 3: and thus you might as well take a gamble on

924
00:52:53,520 --> 00:52:54,280
Speaker 3: something different.

925
00:52:55,200 --> 00:52:58,880
Speaker 2: Yeah, yeah, you know we can. We also have to

926
00:52:59,120 --> 00:53:03,520
Speaker 2: have to ignow knowledge that news reporting can certainly change

927
00:53:03,880 --> 00:53:07,440
Speaker 2: the perceived odds of something happening. Like if you were

928
00:53:07,440 --> 00:53:10,840
Speaker 2: to watch a news network, a hypothetical news network that

929
00:53:10,960 --> 00:53:13,879
Speaker 2: was just twenty four hours coverage of snake bites, that's

930
00:53:13,920 --> 00:53:17,480
Speaker 2: all they covered. Anytime anywhere in the world someone's beitten

931
00:53:17,520 --> 00:53:19,800
Speaker 2: by a snake, they are there to cover it in full.

932
00:53:20,320 --> 00:53:23,520
Speaker 2: This would maybe give you a certainly a heightened awareness

933
00:53:23,760 --> 00:53:26,399
Speaker 2: of maybe the legitimate risks of snake bite, but also

934
00:53:26,520 --> 00:53:30,680
Speaker 2: maybe an inflated feeling about your personal risks of snake bite.

935
00:53:31,000 --> 00:53:33,560
Speaker 3: Yeah, okay, so that's different in that what I was

936
00:53:33,600 --> 00:53:36,160
Speaker 3: just talking about was like just how general emotional affect

937
00:53:36,239 --> 00:53:38,560
Speaker 3: could affect the way you reason, but it could also

938
00:53:38,600 --> 00:53:39,640
Speaker 3: be content specific.

939
00:53:39,920 --> 00:53:43,359
Speaker 2: You're right, yeah, But anyway, mostly what we're dealing here

940
00:53:43,400 --> 00:53:48,040
Speaker 2: with is the effect here. So a recent study from

941
00:53:48,280 --> 00:53:51,200
Speaker 2: Adelphi University looked into this. It was published in Frontiers

942
00:53:51,200 --> 00:53:54,280
Speaker 2: and Psychology and titled negative news exposure does not affect

943
00:53:54,360 --> 00:53:57,840
Speaker 2: risk or ambiguity a version. So their answer is pretty

944
00:53:57,880 --> 00:54:00,319
Speaker 2: much in the headline. There is often the case. Now,

945
00:54:00,600 --> 00:54:02,680
Speaker 2: this is another one of those small studies, I believe

946
00:54:02,680 --> 00:54:05,160
Speaker 2: the working they worked with groups here of like eighty

947
00:54:05,200 --> 00:54:07,520
Speaker 2: four and two hundred and twenty nine, so you know,

948
00:54:07,960 --> 00:54:11,800
Speaker 2: as always, more research is required. This is not something

949
00:54:11,840 --> 00:54:13,440
Speaker 2: you can just take to the bank, but it's an

950
00:54:13,440 --> 00:54:17,319
Speaker 2: interesting possibility. The authors point out that while studies have

951
00:54:17,440 --> 00:54:21,520
Speaker 2: found that negative effect can increase risk aversion and ambiguity

952
00:54:21,560 --> 00:54:25,440
Speaker 2: a version, we didn't know I quote these effects generalized

953
00:54:25,440 --> 00:54:29,680
Speaker 2: to more realistic negative stimuli such as watching the news.

954
00:54:30,440 --> 00:54:34,120
Speaker 3: Oh okay, so maybe in previous studies it's been found

955
00:54:34,200 --> 00:54:39,960
Speaker 3: that negative emotions can increase ambiguity version and risk aversion,

956
00:54:40,400 --> 00:54:43,280
Speaker 3: and so you would just assume that stimuli like watching

957
00:54:43,320 --> 00:54:46,959
Speaker 3: the news would would also increase those versions. But maybe

958
00:54:47,000 --> 00:54:47,480
Speaker 3: it doesn't.

959
00:54:48,040 --> 00:54:49,840
Speaker 2: Yeah, and you can see why this would be something

960
00:54:49,920 --> 00:54:52,400
Speaker 2: worth knowing. I mean, not only from a general standpoint

961
00:54:52,440 --> 00:54:56,840
Speaker 2: of understanding. You know, how people make choices based on

962
00:54:57,080 --> 00:54:59,719
Speaker 2: their mood and what influences their mood. That's certainly valid

963
00:55:00,120 --> 00:55:02,560
Speaker 2: and that's the main point of the research here, but

964
00:55:02,680 --> 00:55:06,200
Speaker 2: also you can imagine it being very a very interesting

965
00:55:06,200 --> 00:55:10,480
Speaker 2: topic for individuals buying advertisement time on say twenty four

966
00:55:10,480 --> 00:55:15,399
Speaker 2: hour news network, especially if they're say, if they want

967
00:55:15,440 --> 00:55:17,760
Speaker 2: to have an advertisement for some sort of adventure travel

968
00:55:17,880 --> 00:55:21,600
Speaker 2: or something of that nature. You know, Bungee cords, I

969
00:55:21,600 --> 00:55:24,319
Speaker 2: don't know, whatever you happen to be selling. So, in

970
00:55:24,360 --> 00:55:27,760
Speaker 2: this particular study, one group was exposed to negative news,

971
00:55:27,960 --> 00:55:29,840
Speaker 2: and in this case it was like news about a

972
00:55:29,840 --> 00:55:32,879
Speaker 2: car crash, and the other group was exposed to neutral news,

973
00:55:32,920 --> 00:55:35,080
Speaker 2: so not great news, not good news, not like a

974
00:55:35,120 --> 00:55:39,240
Speaker 2: real fluff piece, but just something about train schedules, something

975
00:55:39,360 --> 00:55:41,920
Speaker 2: nice and boring and man, maybe it's a little interesting.

976
00:55:42,560 --> 00:55:45,600
Speaker 2: And they found that although participants who watched negative news

977
00:55:45,640 --> 00:55:49,440
Speaker 2: reported a significant increase in negative effect, they did not

978
00:55:49,600 --> 00:55:52,000
Speaker 2: differ from the neutral news group in their risk or

979
00:55:52,080 --> 00:55:53,880
Speaker 2: ambiguity preferences.

980
00:55:53,880 --> 00:55:57,680
Speaker 3: Interesting, Okay, so they said past studies had found negative

981
00:55:57,680 --> 00:56:03,040
Speaker 3: effect increases ambiguity of version. They showed people bad news

982
00:56:03,120 --> 00:56:06,800
Speaker 3: and it did increase negative affect, but did not increase

983
00:56:06,840 --> 00:56:07,840
Speaker 3: ambiguity version.

984
00:56:08,560 --> 00:56:11,959
Speaker 2: Right, right, So I don't think it means go ahead

985
00:56:11,960 --> 00:56:13,759
Speaker 2: and consume all the negative news you want. It's not

986
00:56:13,800 --> 00:56:16,960
Speaker 2: going to impact you. Like, no, it can and will

987
00:56:17,000 --> 00:56:19,640
Speaker 2: impact you. But what the study seems to be suggesting

988
00:56:19,760 --> 00:56:26,120
Speaker 2: rather is that like sort of incidental or realistic consumption

989
00:56:26,280 --> 00:56:29,879
Speaker 2: of negative news is that that exposure is not going

990
00:56:29,920 --> 00:56:32,200
Speaker 2: to be enough of a force in and of itself

991
00:56:32,280 --> 00:56:36,840
Speaker 2: to move the scale and actually impact your decision making process. Again,

992
00:56:36,920 --> 00:56:39,520
Speaker 2: on the whole this is this would be a generalization,

993
00:56:39,640 --> 00:56:41,880
Speaker 2: and again it's based on you know, smaller study, and

994
00:56:41,880 --> 00:56:43,880
Speaker 2: there's so many factors on top of this, so you

995
00:56:43,920 --> 00:56:47,880
Speaker 2: could throw into the scenario. But both groups were equally

996
00:56:48,040 --> 00:56:51,320
Speaker 2: likely to choose a certain gamble over an ambiguous one

997
00:56:51,520 --> 00:56:53,880
Speaker 2: following the consumption of their media.

998
00:56:53,920 --> 00:56:55,560
Speaker 3: Oh well, some just occurred to me. I have no

999
00:56:55,640 --> 00:56:57,759
Speaker 3: reason to think this is really true, because I'm sure

1000
00:56:57,800 --> 00:57:00,279
Speaker 3: the authors would have done a pretty good job of

1001
00:57:01,320 --> 00:57:03,600
Speaker 3: planning this out. But like, what if the control group

1002
00:57:03,680 --> 00:57:08,720
Speaker 3: the train schedule news was actually pretty demoralizing. It's supposed

1003
00:57:08,760 --> 00:57:11,920
Speaker 3: to be a neutral control, but actually that made people

1004
00:57:12,040 --> 00:57:13,560
Speaker 3: equally ambiguity averse.

1005
00:57:14,000 --> 00:57:16,080
Speaker 2: How that would have been an interesting outcome? No, no, no,

1006
00:57:16,120 --> 00:57:21,840
Speaker 2: But my understanding is that basically the normal parameters of

1007
00:57:21,960 --> 00:57:25,840
Speaker 2: ambiguity aversion were in place, so people were still averse

1008
00:57:25,880 --> 00:57:30,080
Speaker 2: to ambiguity, but in equal measure, whether they had just

1009
00:57:30,160 --> 00:57:32,280
Speaker 2: learned about a car crash or about the exciting world

1010
00:57:32,360 --> 00:57:33,360
Speaker 2: of train schedules.

1011
00:57:33,560 --> 00:57:37,720
Speaker 3: Yeah, so they basically just conformed roughly to Elsberg's predictions.

1012
00:57:38,360 --> 00:57:42,560
Speaker 2: Yes, exactly. But again, so many studies come out about this.

1013
00:57:42,960 --> 00:57:45,080
Speaker 2: They're new ones all the time. It's just such a

1014
00:57:45,760 --> 00:57:50,360
Speaker 2: fascinating way to sort of get in and crunch how

1015
00:57:50,600 --> 00:57:54,840
Speaker 2: we make decisions in life based on how we deal

1016
00:57:54,840 --> 00:57:58,280
Speaker 2: with ambiguity and the inherent ambiguity of life.

1017
00:57:58,680 --> 00:58:02,280
Speaker 3: Yeah. That again, I can't emphasize this enough, Like, because

1018
00:58:02,360 --> 00:58:05,680
Speaker 3: these studies want to quantify the effect, they need to

1019
00:58:05,760 --> 00:58:09,680
Speaker 3: use these like fixed games that include you know, certain

1020
00:58:10,160 --> 00:58:14,360
Speaker 3: like certain odds and risk conditions where the odds are

1021
00:58:14,480 --> 00:58:17,800
Speaker 3: very clear. But in real life you're dealing with basically

1022
00:58:17,840 --> 00:58:21,080
Speaker 3: top to bottom ambiguity. It's real ambiguity all the time. Like, really,

1023
00:58:21,200 --> 00:58:25,840
Speaker 3: rarely do we encounter decisions where our probability of success

1024
00:58:26,040 --> 00:58:30,720
Speaker 3: is absolutely clear, it's clearer than others. Some decisions have

1025
00:58:30,760 --> 00:58:34,160
Speaker 3: clearer odds than others, but you never really know what

1026
00:58:34,200 --> 00:58:34,880
Speaker 3: your odds are.

1027
00:58:35,600 --> 00:58:37,320
Speaker 2: Yeah, I mean, that's one of the reasons we've talked

1028
00:58:37,320 --> 00:58:38,480
Speaker 2: about this before and the show. Is one of the

1029
00:58:38,520 --> 00:58:42,360
Speaker 2: reasons we like things like zombie apocalypse scenarios, not because

1030
00:58:42,360 --> 00:58:45,400
Speaker 2: we necessarily like the idea of the world ending, or

1031
00:58:45,440 --> 00:58:47,240
Speaker 2: of the dead coming back to life and trying to

1032
00:58:47,240 --> 00:58:51,240
Speaker 2: eat our brains. But baked into those scenarios, there's often

1033
00:58:51,320 --> 00:58:55,760
Speaker 2: like a simplification of how the world works, a removal

1034
00:58:55,840 --> 00:58:58,800
Speaker 2: of some degree of the ambiguity. And there's often still

1035
00:58:59,000 --> 00:59:01,200
Speaker 2: in any good thing, I think you're going to have

1036
00:59:01,240 --> 00:59:05,040
Speaker 2: a contemplation of ambiguity as well. But in broad strokes,

1037
00:59:05,080 --> 00:59:07,960
Speaker 2: you might have a scenario boiled down to like, Okay, well,

1038
00:59:07,960 --> 00:59:10,280
Speaker 2: now it's the living versus the dead. Now it's the

1039
00:59:10,320 --> 00:59:14,200
Speaker 2: clear good guys versus the bad guys. And what is

1040
00:59:14,240 --> 00:59:16,920
Speaker 2: the answer? Well, it's always blasting it with a shotgun.

1041
00:59:16,560 --> 00:59:20,480
Speaker 3: Right, Isn't it interesting how in most stories, any major

1042
00:59:20,760 --> 00:59:25,080
Speaker 3: change that happens to the characters is because of whatever

1043
00:59:25,160 --> 00:59:27,720
Speaker 3: the struggle in the story is about. It's not like

1044
00:59:28,040 --> 00:59:31,280
Speaker 3: totally random, out of nowhere exogynous events come in and

1045
00:59:31,320 --> 00:59:35,400
Speaker 3: completely change the story. Occasionally that happens, and people, I think,

1046
00:59:35,840 --> 00:59:38,760
Speaker 3: I think often find that quite interesting in storytelling because

1047
00:59:38,760 --> 00:59:39,400
Speaker 3: it's pretty.

1048
00:59:39,240 --> 00:59:43,760
Speaker 2: Rare, you where the cause of the scenario is ambiguous.

1049
00:59:43,800 --> 00:59:46,240
Speaker 3: You mean, we're like a major change maybe comes in

1050
00:59:46,280 --> 00:59:48,200
Speaker 3: the middle of the story and it has nothing to

1051
00:59:48,280 --> 00:59:50,320
Speaker 3: do with what the main struggle or plot of the

1052
00:59:50,360 --> 00:59:53,479
Speaker 3: story is just comes out of nowhere. Yeah, I can't

1053
00:59:53,480 --> 00:59:55,080
Speaker 3: think of an example off the top of my head,

1054
00:59:55,120 --> 00:59:57,280
Speaker 3: but I know there are some like this right in

1055
00:59:57,320 --> 00:59:58,560
Speaker 3: with your example.

1056
00:59:58,520 --> 01:00:00,160
Speaker 2: All right, we're gonna gohea and close up this step. So,

1057
01:00:00,200 --> 01:00:01,720
Speaker 2: but we'd love to hear from everyone out there. We

1058
01:00:01,760 --> 01:00:05,000
Speaker 2: know that everyone has experience with ambiguity in life, judging it,

1059
01:00:05,200 --> 01:00:08,760
Speaker 2: being adverse to it, rolling the dice anyway, and so forth.

1060
01:00:09,080 --> 01:00:11,280
Speaker 2: So right in, we would love to hear from you.

1061
01:00:11,720 --> 01:00:13,320
Speaker 2: Just a reminder that Stuff to Blow Your Mind is

1062
01:00:13,360 --> 01:00:15,720
Speaker 2: primarily a science and culture podcast, with core episodes on

1063
01:00:15,760 --> 01:00:18,640
Speaker 2: Tuesdays and Thursdays, short form episodes on Wednesdays and on Fridays.

1064
01:00:18,680 --> 01:00:21,160
Speaker 2: We set aside most serious concerns to just talk about

1065
01:00:21,160 --> 01:00:23,240
Speaker 2: a weird film on Weird House Cinema.

1066
01:00:23,400 --> 01:00:27,160
Speaker 3: Huge thanks as always to our excellent audio producer JJ Posway.

1067
01:00:27,240 --> 01:00:28,800
Speaker 3: If you would like to get in touch with us

1068
01:00:28,800 --> 01:00:31,160
Speaker 3: with feedback on this episode or any other, to suggest

1069
01:00:31,240 --> 01:00:33,160
Speaker 3: a topic for the future, or just to say hello,

1070
01:00:33,600 --> 01:00:36,240
Speaker 3: you can email us at contact at stuff to Blow

1071
01:00:36,240 --> 01:00:44,200
Speaker 3: your Mind dot com.

1072
01:00:44,680 --> 01:00:47,600
Speaker 1: Stuff to Blow Your Mind is production of iHeartRadio. For

1073
01:00:47,680 --> 01:00:50,480
Speaker 1: more podcasts from my Heart Radio, visit the iHeartRadio, app,

1074
01:00:50,640 --> 01:01:06,040
Speaker 1: Apple podcasts, or wherever you listen to your favorite showstor