📚 Quinn's Highlights

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The need for transparent and democratic decision-making: Human bullshit and algorithmic bullshit are two sides of the same coin Summary: Data and algorithms are not inherently bad, but they should be used in a transparent and democratic way that empowers everyone. Instead of arguing about whether computer or human decision-making is better, we should focus on accountable and transparent decision-making. This means avoiding human biases and stereotypes as well as naive machine learning without considering its real-world implications. Transcript: Speaker 1 So the point is that it's not that data and algorithms are bad it's that they need to be applied in a way which is transparent and which is democratic and which empowers all of us to carry On these debates rather than simply being tools which accurately or inaccurately are being used to buy the powerful to control the rest of us it's silly to argue about which is better You know computer decision making or human decision making that's really not the point I mean the point is we should have accountable transparent decision making instead of bs there's Human bs which comes in the form of stereotypes in ideology and there's algorithmic bs which comes in the form of naive machine learning without thinking enough about its applications

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

COMPLEXITY: Physics of Life

The Problem of Scale Clash in Human Collaboration Summary: The problem goes beyond ideal scale of humanity. Different things we want involve different scales. Science works on a huge scale for problems like climate change while other things work on medium or small scales. There is a clash of different scales and no optimal scale. The big scales tend to win and squash out the small scales. However, over long time scales, these complex systems tend to implode. It's about a dynamic balance where different forces coexist. How do we handle this in light of global coordination, bioregional organization, and personal relationships at the neighborhood level? Transcript: Speaker 2 I think the problem is even worse than what you're describing I'm going to try to pessimize what you said I mean when you ask me a question like have we gone past the ideal scale of humanity That implies that there is an ideal scale that we could plausibly hit if we could somehow convince people to scale back. For me the real worry is there's no ideal scale of humanity because different things we want to be involved in demand different scales science works really big good on a huge scale solving Problems like climate change our massive scale problems that everyone has to get together on and then there are other things that work at medium or small scales and there's just this Unsolvable scale clash my real worry is that different parts of us and our needs call us to different scales and there is not an optimal scale and so I have to participate in these different Scales or in tension with each other and also the big scales tend to win because they get really powerful and so they squash out the small scales. Speaker 3 Over short time scales though right because over long time scales those like you know this is the Bob May will a complex system large complex system be stable question it's like at some Point those things tend to implode so it's not about like an equilibrium so much as it is about a a dynamic balance or a zone at which these different forces are able to coexist how do you Deal with all of this in light of both the need for global coordination and bioregional organization and neighborhood level personal relationships etc.

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

COMPLEXITY: Physics of Life

Two Models of Searching for Truth: Unearthing the Truth v.s. Growing Into The Truth Summary: Science is like carving away everything that isn't truth, but I think it's more like an infinite vacuum with trees growing in all directions. The search for truth is complex and ever-expanding. It's like ecology, where species have multiple solutions to a problem, which continually changes. I believe in infinite diversity and combinations, and that complexity can emerge from simplicity. Instead of focusing on the core, we should expect to branch out. Transcript: Speaker 2 One metaphor I like is that I think some people have as their image of science. Imagine we're sitting on the surface of a sphere, and they think they're kind of digging down to the core of the truth. They're discarding the earth beneath them, the falsities, and they're going to hit the truth. Speaker 1 We're carving away everything that isn't science, you're saying? Speaker 2 Yeah. And I think that the image I have instead is there's an infinite vacuum outside of that sphere, and there are trees growing out from the surface of the sphere in all directions. And as they grow out, more space is available, and they branch and expand. And that just goes on, and it gets more and more complex the further you get out. And that's kind of how I think of the search for the truth. That strikes people maybe initially is a little bit weird. I guess that's how I interpret like beginning of infinity, David Deutsches' phrase. But another way to see that is ecology, the way the species were. Species are all after some abstracted fitness landscape, I guess is one way to conceive of it. But somehow we don't end up with one solution to that problem. In fact, we get a bunch of solutions to the problem, and as that problem gets solved, it actually changes the problem, because now for all the other species you've got to deal with, and There's other species that you can eat, there's all kinds of stuff going on. That's how I think about it. I eat reflecting infinite diversity and infinite combinations. I think that there's just a lot of things going on, and you can build a lot of complexity from a small set of ingredients. And you shouldn't expect to get down to the core, you should expect to branch out from the core.

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

COMPLEXITY: Physics of Life

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