📚 Quinn's Highlights

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

The Danger of Incorrectly Mapping Between Scientific Measures and Truth Transcript: Speaker 1 And it's a problem when scientific culture tolerates too much ambiguity. There's always a caveat there, which is that at the early stage of theory development, sometimes you need ambiguity because you don't actually know really what you're talking about Yet. And so you need to allow for multiple interpretations to be possible until you can figure out what you mean. But a mature theory should be minimally ambiguous. This is at odds with things like metrics in terms of let's say how to evaluate something because people think, oh, well, it's scientific. Therefore, I want to use this to then therefore impose a value judge on something. It's better because it has a higher score on it. But that's not what science is actually able to do. Science can say, it has this score and it measures this thing because what it measures is this. If you say what it measures is this, and therefore it means this other thing, that's a problem because that's a false mapping. And it's not really about ambiguity versus precision. It's about, I think, the imprecision of the mapping between the measure and the term. So if you want to measure something like happiness or economic prosperity, you can say, well, we'll measure the genie coefficient, we'll measure GDP. But those are rigorous, clearly unambiguous measures. They have a meaning. This is what they are. This is how we measure them. We can compare things on this measure. And that's not problematic until you then say, and it is better to have a higher GDP full stop.

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

COMPLEXITY: Physics of Life

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

Bad Norms and Policies Produce "Legislatice Mediocrity" in Organizations Summary: Encouraging a culture of being teachable and open to listening to others is crucial for innovation and improvement in organizations. While standard operating procedures (SOPs) and efficient systems are appreciated, they should not create taboos or hinder learning, leading to what the speaker refers to as 'legislative mediocrity.' The speaker advocates for a focus on innovation and continuous improvement, rather than being stifled by rigid norms and policies. Transcript: Speaker 1 You want to be teachable and you want to have a culture of being teachable and listening to others. Yeah. That's that's really important. And so I love SOPs. I love I love it when you get a system working well and efficient. But I don't like it when it creates taboos and when it stops people learning. Legislative mediocrity. It drives me nuts. I'm very much let's do innovation. Let's improve.

Organizational Structures That Enable Knowledge Flow With Stuart French

Because You Need to Know Podcast ™

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