📚 Quinn's Highlights

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A batch of the best highlights from what Quinn's read, .

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

Pol.is: An Example of Tools for Facilitating Non-Adverserial Debate at Scale Summary: A twitter-like system in Taiwan guides conversations towards consensual outcomes by using k-means clustering. It's a simple proof of concept for fact checking and has been effective in large-scale conversations. The science of plurality can advance to help navigate complexity in diverse opinions. Transcript: Speaker 2 Pol.is i don't know if you guys are familiar with that but it's a system used in Taiwan it's a twitter like format but it deliberately guides conversations towards consensual or partially Consensual outcomes while highlighting the differences that exist in the conversations in a non-judgmental way and it's just a wonderful system and at the same time it's like the Most simplistic proof of concept of the general direction it uses k-means clustering of stated opinions it doesn't use any natural language processing it's like the bargain basement Version of what it's trying to achieve but it still has been transformatively effective for these types of conversations at scale in Taiwan and is being adopted if it survives by the Twitter bird watch folks as the foundations of what they're trying to do for fact checking so i do believe that there is a science here that can advance dramatically i think that we have Not chosen to apply ourselves to it because we've been seduced by oh we're going to do the unbiased algorithm that's going to predict the truth the right way rather than saying no people Are diverse you have a lot of different opinions how do we actually help people navigate that complexity so i really am hopeful that this science what i would call plurality really can Advance and and help us do these things much better and again i'll put in the plug if you're a researcher interested in these things we're trying to build an academic community that really Wants to work on them right to me at when at pluralitynetwork.org

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

COMPLEXITY: Physics of Life

Most of us really enjoy the building aspect but start to get a little shy when it comes to telling people about the stuff we’ve built. That could be for any number of reasons: fear, embarrassment, self-preservation, or an aversion to being perceived as hawking your wares. It’s a valuable exercise to investigate whether or not you resonate with any of those reasons. Are you afraid people are going to make fun of what you built? Are you embarrassed that it isn’t up to your own (admittedly high) standards? Are you waiting for some elusive perfect moment? Do you have an aversion to “marketing” and don’t want to become the thing you hate? Whatever it is for you, I encourage you to really dig into it and see if that fear is worth keeping around.

Publishing your work increases your luck

https://github.com/readme/

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