📚 Quinn's Highlights

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The Expert Identification Problem and the Challenges of Democratic Decision-Making Key takeaways: • The expert identification problem is a major concern when it comes to trusting experts in a democracy. • Democracies aim to harness the intellectual power of diversity for better solutions. • The challenge lies in recognizing the best solutions when they require expertise that the democratic entity may not possess. • There is no clear solution to this problem, and democracy remains the best way to organize society according to the speaker. Transcript: Speaker 2 So for a long time I would say that the problem I've been most obsessed with is something I call the expert identification problem it's like how does the non-expert figure out which expert To trust if they don't have the expertise and one of the worries about a democracy is that it runs straight into the expert identification problem right like if we're democratically Voting on what to do we are aggregate non-experts I mean I'm not talking here about like oh we are the experts and you all are not even if you are the world expert in X you're a non-expert In a million other fields right so as an aggregate we are non-expert so here's the real worry for me if you have the right solution how would that get democratically approved Helen Landemore Is this a political theorist I really like she's part of a movement who are epistemic democrats and they think that democracies are the best way to harness the intellectual power of Diversity and the basic model is something like diverse people will come up with a better set of solutions and when you put them together the best solutions will rise to the top and my Worry is how will the democratic entity recognize which are the best solutions because if the best solution requires expertise to recognize and the democratic entity as an aggregate Is not an expert how will they figure it out and that's a problem I'm not sure there's a solution to and I also can't think of a better way to organize the world than democratically

Paul Smaldino & C. Thi Nguyen on Problems With Value Metrics & Governance at Scale

COMPLEXITY: Physics of Life

Prediction Markets Are Built on the Principle of Adverserial Engagement Transcript: Speaker 2 There the first is what you're describing is precisely the reason why i am a bit of a skeptic of prediction markets not to say that they don't have a role but i don't think that they are nearly The solution that many believe they are and it's because they set us up in an adversarial relationship with regards to determining the truth it's not at all the say i don't think incentives Have a role or that it isn't worth a listening information for me i believe in all those things but the notion that the way that we should do it is betting against each other so that we want Everyone else to be as wrong as possible so we can be right and we want to get like one big payoff for like the person who's most right and anything that can be like too easily analogized To some sort of like dick measuring contest is not something that like excites me as a mechanism for like coming to good social outcomes and i think that prediction markets have an important Element of that

Glen Weyl & Cris Moore on Plurality, Governance, and Decentralized Society

COMPLEXITY: Physics of Life

The Danger of Incorrectly Mapping Between Scientific Measures and Truth Transcript: Speaker 1 And it's a problem when scientific culture tolerates too much ambiguity. There's always a caveat there, which is that at the early stage of theory development, sometimes you need ambiguity because you don't actually know really what you're talking about Yet. And so you need to allow for multiple interpretations to be possible until you can figure out what you mean. But a mature theory should be minimally ambiguous. This is at odds with things like metrics in terms of let's say how to evaluate something because people think, oh, well, it's scientific. Therefore, I want to use this to then therefore impose a value judge on something. It's better because it has a higher score on it. But that's not what science is actually able to do. Science can say, it has this score and it measures this thing because what it measures is this. If you say what it measures is this, and therefore it means this other thing, that's a problem because that's a false mapping. And it's not really about ambiguity versus precision. It's about, I think, the imprecision of the mapping between the measure and the term. So if you want to measure something like happiness or economic prosperity, you can say, well, we'll measure the genie coefficient, we'll measure GDP. But those are rigorous, clearly unambiguous measures. They have a meaning. This is what they are. This is how we measure them. We can compare things on this measure. And that's not problematic until you then say, and it is better to have a higher GDP full stop.

Paul Smaldino & C. Thi Nguyen on Problems With Value Metrics & Governance at Scale

COMPLEXITY: Physics of Life

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