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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

Increasing Returns (Order) in a System is a Product of Disorder, Numerosity, and Feedback Summary: Disorder, in tandem with feedback, leads to order. Feedback occurs when information is transmitted and found by others, creating a cycle. This feedback, combined with disorder, results in the phenomenon of increasing returns, where random decisions influence subsequent decisions. Increasing returns in a system depend on disorder, feedback, and the involvement of a sufficient number of individuals. Transcript: Speaker 1 The next one on the list will be feedback. So the disorder only in tandem with feedback is going to lead to order. And the and trail again, an example, the feedback is coming from one end going out, finding something interesting as happenstance by accident. And then it leaves information. Another and finds it. And that's where the feedback starts. And this feedback is, you know, just like, I believe, Brian Arthur was talking about increasing returns. Initially, something random happens. Someone makes a random decision and a few more, say, people make a random decision. And that leads other people to not make a random decision, but make a decision based on that previous one. So this increasing returns phenomenon is a combination of disorder and feedback. And of course, the morosity, you need a few people to make it happen.

The 10 Features of Complex Systems — Part 1

Simplifying Complexity

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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