📚 Quinn's Highlights

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

The Tension Between Organized Behavior at Scale and Individual Needs Summary: Large-scale organizations aim for legibility and coherence, but this may lead to a lack of diversity and individual needs. The educational system's emphasis on GPA overlooks other important skills and qualities. Transcript: Speaker 2 One of the most influential ideas for me recently has been from James South's book Seeing Like a State. And Scott has this idea that like what large-hill organizations wants its legibility and legibility is a kind of clear coherence that's aggregatable to a kind of higher level view. So a simple version might be like look if you're a CEO you can't have every department have its own obscure little value system. You need a single collective value system or something close to it so you can get production and profit measures and aggregate them in what Scott says is bring the whole organization Into view. So one way to put my worry is that what would be good for human life is an incredible diversity of bottlenecks which work on different often non-metrified systems. If Scott is right large-scale institutions will tend towards is a kind of monolithic measurement system that moves towards let's have a small number of bottlenecks and let's have A unified measure. And so like the heart of my worry is that organized behavior at scale is inevitably in tension with what a diverse population of individuals needs. And that's just an unfixable problem. Let me just give one quick example. In the educational system the dominant measure is GPA. You can add other like I can write in my notes all kinds of other shit about what students are good at. That barely matters because that's not aggregatable. When a law school admissions officer is doing their spreadsheet to do the first main cutoff nothing in my weird little notes is going to make it into that first level cutoff. The big moving forces just look at GPA.

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

COMPLEXITY: Physics of Life

The people with the most accurate models of others tend to have diverse social networks Summary: To correct for this handicap, we need to listen to the oppressed in the population. This includes laborers, students, and others who are usually not given a political voice. By expanding our social networks to include more diverse perspectives, policymakers can make better decisions based on a deeper understanding of societal trends and people's desires. Transcript: Speaker 1 But it sounds like this gives us a really clear pointer on how to correct for this handicap. And that we really ought to be like, perhaps when it comes time to make decisions on behalf of everyone, we should really be listening to whomever the oppressed are in that population. We should be really paying attention, for example, to laborers and students and people that are ordinarily not historically, not given a lot of political voice. And what you're saying, yeah, it's in other words, what we need to do is broader our social networks include in our social networks, those people who are typically not there. So if the policymakers who are making these important decisions should know as many different people as possible. And we show in related studies that people who have most diverse social circles are also best able to predict societal trends and to understand how the overall population lives and What people want.

Mirta Galesic on Social Learning & Decision-Making

COMPLEXITY: Physics of Life

While Algorithmic Decision-Making Does Suffer From Bias, It Offers the Potential for Unparalleled Transparency In the Decision-Making Process Summary: Algorithms offer a transparent and accountable way for decision making. They can detect bias and perpetuated patterns, but must be transparent, independently audited, and not proprietary or snake oil. Transcript: Speaker 1 And then the response comes back saying yes but if you're basing it on historical data then you're feeding in biases of the past which you're going to propagate into the future there Is a kind of new attitude about all this which is kind of orthogonal to these two axes which I personally find pretty compelling and it's come up in from a couple of different places independently I could drop a few names but let me just say that the attitude is that algorithms at their best offer a new way for decision making to be transparent and accountable that's at their best So you know if an algorithm is something that everyone understands how it works everyone understands why we are chose to use this algorithm how it was trained and it's something which Can be independently audited it's even something which could be tinkered with to see if it could be made more fair and more accurate that kind of algorithm could raise the standard of Decision making in many areas and let us detect bias where it crops up and also help us detect where historical patterns are being perpetuated and what we might do to fix that but the big But is they have to be transparent they have to be independently audited they can't be proprietary and opaque and hidden behind veils of intellectual property and they also can't just Be snake oil right so there is a lot of snake oil out there there's a lot of products being put out to market which have not in any sense been independently verified or validated and where Their users and customers frankly don't really know whether their results ought to be interpreted the way they ought to be interpreted and so there needs to be a lot more critical thinking Aimed at these

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

COMPLEXITY: Physics of Life

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