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The Map is not the Territory Summary: Humans often confuse maps with territories, despite evidence from various disciplines. We wrongly assume that what we measure is what matters, but our values may not have quantifiable metrics. Biometric data can oversimplify complex discussions on health. This conundrum becomes more significant when considering governance on a larger scale. How do we count and operate a nation state wisely? Can social science inform smarter political economies? We must escape the false clarity of information systems that lack collective wisdom. Transcript: Speaker 3 There are maps and there are territories and humans frequently confuse the two. No matter how insistently this point has been made by cognitive neuroscience, epistemology, economics, and a score of other disciplines, one common human error is to act as if we know What we should measure and that what we measure is what matters. But what we value doesn't even always have a metric and even reasonable proxies can distort our understanding of and behavior in the world we want to navigate. Even carefully collected biometric data can include the other factors that determine health or can oversimplify a nuanced conversation on the plural and contextual dimensions Of health, transforming goals like functional fitness into something easier to quantify but far less useful. This philosophical conundrum magnifies when we consider governance at scales beyond those at which homo sapiens evolved to grasp intuitively. What should we count to wisely operate a nation state? How do we practice social science in a way that can inform new, smarter species of political economy? And how can we escape this seductive but false clarity of systems that reign information but do not enhance collective wisdom?

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

COMPLEXITY: Physics of Life

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 tension between the ambiguity of individuals' goals and large scale collective organization Transcript: Speaker 2 Here's the pessimistic nightmare. It is really good and healthy for human beings to live in an ambiguous environment with a pluralistic set of goals, many of which are in Kuwait. That is an essential tension with the methods of large scale collective organization. If it's true that for an organization to cohere, it needs to have clear policies so it can act coherently, then we should not expect that kind of ambiguity to survive at scale. And I think what you're describing, so I tend to think about since I'm a philosopher like what makes something constitutively coherent. And what you're describing is a kind of evolutionary process. You know, some organizations are going to be more coherent than others and some people are more interested in coherence. And the people that are more interested in following the strict outcome are going to arise in the organization. And the organizations that have clear outcomes are going to be better at achieving those outcomes. And so our world is going to be full of large organizations staffed with people that have very, very clear specifications of outcomes. And there's something inhumane and bad about that for individuals. But that's what happens when we need to organize in large scale collectives.

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

COMPLEXITY: Physics of Life

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