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A batch of the best highlights from what Quinn's read, .
People's Understanding of Others' Lives Is Biased Based on the Structure of Their Social Network
Transcript:
Speaker 1
So there's something in that that I found really interesting about this social sampling, which is that as you mentioned, like if you happen to be worse off and everyone else is worse Off, as is the case with like income, for example, then being worse off, you're going to project your bias into that general population more accurately than if you're better off in some Situation for which the most of the population is worse off. And that these biases are not all created equal. Yes. It has to do with how they stand relative to the broader population. So what we show is that this kind of biases of judgments of the broader population can be explained by the structure of social network and not by some cognitive deficit or motivational, Motivational bias, some desire to be better than others or that or some idea that everybody's like me or some cognitive deficit that people cannot, that people are too stupid to understand How other people live. It's really determined by the context of memory, that by the content of one's memory, which comes from one social circle.
Mirta Galesic on Social Learning & Decision-Making
COMPLEXITY: Physics of Life
The Small Animal Replacement Problem in Animal Advocacy
Summary:
Choosing a meat tax as a form of advocacy may seem logical, but it can actually lead to a shift in consumption from red meat to white meat like chicken and fish.
This shift increases the number of animals farmed overall, which is known as the small animal replacement problem.
Transcript:
Speaker 2
The vast difference in choosing one campaign over another and how much difference you can have between the two. But actually, not only that, just highlighting the damage you can do. That was so enlightening for me. I think I've never thought about it like that before. I think specifically we were working with an organisation on whether doing a meat tax would be an effective form of advocacy. On the surface, you're like, oh, meat tax, yeah, it makes sense. It's the same as cigarette, alcohol or other kind of syntaxes that we have in the UK. It's just put a tax on me and then less consumption, less demand, etc. Then just kind of flippantly thinking about it in that sense and then the team did an in-depth report and actually kind of long story short. I would recommend going and reading the report if you're interested. But essentially consumption moves generally from the red meat from an environmental or health perspective and that's what in the UK, that's the only way that could be passed is through An environmental or health committee. Yeah, like a carbon tax on food products, that kind of thing. Right, exactly. And actually all that does is move consumption from red meat cows to white meat, like chicken and fish. And so actually for looking at numbers, comparatively farming one cow versus 50 chickens that it would take to be comparable, the numbers are huge and even more so for fish and probably Shrimp as we were talking about before. So actually just that shifting consumption was going to increase the amount of animals that were farmed. And so all of a sudden within a short space of time, we've gone from, or I certainly did, I feel like the team have more experienced some more skeptical and it's called the small animal Replacement problem. And we've been talking about this for a long time.
Introducing — How I Learned to Love Shrimp
How I Learned to Love Shrimp
How Measurability/Mathematical Bias Limits the Scope of Scientific Inquiry and Human Discovery
Transcript:
Speaker 1
So there's this old paper from the, I think, 1960s by Eugene Vigner, the Nobel Prize physicist. It's called something like, on the unreasonable effectiveness of mathematics. The fun paper, and he's like, there's no good reason why mathematics should work as well as it does. And there's no good reason why there should be a tool that allows humans to predict things as well as math does. There's no good reason. It's kind of nuts. And we should all just be grateful. And he says some other things, but he's basically just kind of being all about how great mathematics is and how there's no good reason why it should be. And it's pretty cool that it does work so well. I think that there's a counter to that, which is that not everything is that easily described that mathematics. And there's lots of things for which mathematics is not that effective at describing. And it's actually just the things that were well described or easily described by mathematics are the things that were discovered using mathematical tools. They're the things that lend themselves that were amenable to mathematical inquiry. And a lot of the things that we're interested in terms of social science and cognitive science and the related philosophical inquiry are things that are much less tangible in terms Of this kind of specification. And you can see it like in a physics equation, right, a physical theory, whether it's about mass or electricity or something else, right, you have a theory about how things work. And then you can write out equations. And all the terms in the equations have units. And they are all directly related to the things that are measurable. The theories are directly about relationships between things that are measured. And in social theories and cognitive theories, so often our theories are about relating constructs. And then we have proxy measurements, but the theory isn't about the relationship between the proxy measures. The theory is about the constructs and the relationships between the constructs that are social in nature, that are cognitive in nature, but aren't the things that are being measured. And so there's this gap. And I don't know the extent to which that gap can be overcome.
Paul Smaldino & C. Thi Nguyen on Problems With Value Metrics & Governance at Scale
COMPLEXITY: Physics of Life
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