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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

Perspectives on Organizational Strategy & Coordination: Optimizing for Few Coherent Goals v.s. Many Incoherent Goals Transcript: Speaker 1 I think one of the things where the corporate world is actually much better at this than the academic world or the educational world, because their goal is profit. So it's very clear. It's much harder to say what the goal of an educational institution is. It feels like it should be obvious, but within the general goal of like we want to produce successful, well-rounded people, there's a lot of disagreement about what the goals are. And so shaping the institutional incentives around those goals becomes extremely difficult, because not only do we have to worry about perverse incentives, but we have to worry about Vigorous disagreement about the kinds of things that are valued in the first place. And I think exactly what you're talking about, T, is something that if you went to a bunch of university administrators, let's say, or medical school administrators or doctors, and You said, what is the point to what you're doing? Is it to produce wise, well-rounded people? Is it to minimize costs to insurance companies? Is it to increase donor contributions? What is it? And there are all these competing goals. And so there's this constant infighting about among different people who have different versions of what the best version of their institution is, and it's so difficult to articulate What that is. Speaker 2 I wonder if we're in different sides of this, because are you like worried about the hardness of it? It sounds like you think it's a problem that it's hard to come to agreement and articulate a goal, where I actually prefer the university that disagrees, has many incuit and plural goals, And worry that when it articulates an outcome clearly and starts orienting around that outcome, that's when it starts shedding a lot of what was good about the kind of pluralistic more. So let me just give you this is like from my life, right? So a university I've been employed at has started moving toward orienting everything around student success, where student success is defined as graduation rate, graduation speed, Salary after graduation. When you define that outcome, it becomes really easy to target, and the people that are targeting it, as you say, the people that target it well tend to rise, people that are willing to Go all in on targeting that stuff instead of caring about all the other weird shit that education might be for, tend to have better recordable outcomes and tend to rise in the university Structure. So I actually am happier for something as complicated with education, in which different groups have different conceptions of values about what they're doing, and we don't actually Try to settle it, and we don't hold them all to a high articulability constraint, because I think the business school and the CS department have more easily articulable outcomes than The creative writing department, art history department. A lot of the stuff that I'm writing right now is about like this defense of the inarticulable. Speaker 1 It's a hard question to answer because I think that there are multiple levels of organization going on here. There's like a top administrator level, because these institutions tend to be pretty hierarchical. I think at the top of the hierarchy, there has to be some sort of reasonably well-defined goal, even if it doesn't specify what every individual component of the organization or institution Would do it. And I think that that trickles down to those levels though, and creates incentives. Regardless of whether or not it's a good thing, I think there has to be some sort of coherence at the very top level, even if it doesn't dictate what each individual component is doing.

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

COMPLEXITY: Physics of Life

Ambiguity in Communication is Both a Feature and a Bug Summary: In 1984, Eisenberg proposed that ambiguity in communication is important and influential. This idea suggests that being too clear can limit interpretation and hinder coalition-building. Ambiguity can be used to evade accountability, but it is also a general principle of communication. Transcript: Speaker 1 It's Eisenberg in 1984 in communication monographs or something. It's this great rambling paper and this idea has been massively influential to me, but he's basically arguing that it would seem like the point of communication should be clarity, To be as clear as possible. For me to say, I mean this and you do know exactly what I mean and that's the goal and ambiguity is therefore a bad thing. He argues that actually no ambiguity is a really important thing and other people have expanded on this. Now the way I think about this is like a blend of Eisenberg and then other people who've come a bit later, but that in a lot of ways if you're trying to get let's say a coalition, you don't Want to say this is exactly what our goal is and this is what we're trying to do. You want to use vague terms so that a bunch of people can sort of map whatever they think that the goal is onto and say that's consistent. It also leads to a reduction in accountability because after you do something and someone says, you said you were going to do this and you say, nah-ah listen to what I said, it's consistent With what I did because what I said was ambiguous. So it's pernicious in a way too. It's used nefariously in a lot of ways by let's say politicians and other kinds of leaders to avoid accountability, but it's also just a general principle of communication I think.

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

COMPLEXITY: Physics of Life

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