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People have more accurate models of people in close proximity than they do of people far away (socially)
Summary:
People have a good understanding of their friends and are accurate in predicting their behavior.
This is shown by their ability to accurately predict election results based on their friends' voting preferences. However, biases arise when people are asked to judge unfamiliar populations.
These biases can be attributed to the structure of their personal social networks.
The more biased their social networks are, the more biased their estimates of the general population will be.
Transcript:
Speaker 1
Oh yeah, after seven years of research on this paper, that people actually have a quite a good idea about their friends, family, acquaintances, people that they meet on every day basis And then we'd whom they need to cooperate with, learn from or avoid. And that they're actually not that not as biased as a traditional social psychology would like us to think. And we see that because when we ask people about their friends, we see that this predicts societal trends quite well. So in one line of research, we asked a national probabilistic sample of people to tell us who their friends are going to vote for. We average those things across the national sample and got better prediction of election results than when we asked people about their own behavior. And this would not have happened if people were biased in reporting their friends. They must have told us something that must have given us information that's accurate and that's goes beyond their own behavior in order for that to happen to predict the elections better. And by now we saw that in four further, so we five elections all together in the US 2016 in France, the Netherlands, the Sweden and US 2018, and we hope to predict again 2020. So things like that tell us that people are actually pretty good in understanding their social circles and then the apparent biases show up when people are asked to judge people that They don't know so well. So when I'm asked to tell you something about people in another state or another country or people from another socioeconomic cluster, which I don't know well, then I am likely to have Some biases. But these biases we show can be explained by what I know about my friends. So if you ask me something like that, I will really try to answer your question honestly. And to do that, I will try to recall from my memory everything that I know about our social my social world. But you know, if I'm surrounded by rich people like here on the East side of Santa Fe, it could be very difficult to imagine in what poverty people can live in other parts. And so even if I'm trying my best to recall, you know, the most poor person I know, I might never recall such poverty that actually exists in the world. And when asked about the overall level of income in the US, I'm likely to overestimate the overall level. And similarly, if you are poor, you're people who are poor might have problems imagining the wealth of really rich people and they will typically underestimate the wealth of the country. So okay, so let me let me summarize this. So this piece actually suggests that people are not that biased when it comes to judging their immediate friends. They have a lot of useful information about their friends and pretty accurate. The bias is show up when people are asked about other populations that they don't know so well. And they can be mostly explained by the structure of their own personal social networks. The more biased your social networks are, the more biased your estimates will be about the general population.
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
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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