📚 Quinn's Highlights

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Don’t attach your identity to something that’s unsustainable. Optimize for sustainability Summary: Avoid attaching your identity to something unsustainable, such as a career, relationship, or investing strategy, as it could lead to devastation when it ends. Instead, focus on sustainability and longevity in all aspects of life, including friendships, careers, investing, and habits. Prioritize maintaining activities and relationships over short-term gains, aiming to live at 80% potential to avoid burnout and ensure long-term sustainability. Transcript: Speaker 1 I think it's super dangerous in any life to attach your identity to something that's unsustainable, whether it's being a model or having a certain career, having an investing strategy, If you attach your identity to something that you cannot sustain, when it ends, you're going to be morally crushed. It's just going to destroy you. And this like back to investing, the variable that I want to maximize for is how long can I do this for? It's not, can I earn the highest returns? It's, can I maintain this investing strategy for another 50 years? And I know that I couldn't earn a higher return this year and over the next five years, if I did something different. But I'm way less confident that I could keep it going and sustain it. And I think it's the same for relationships. Like you might be able to find a more attractive or a wealthier spouse or partner. But can you keep that going? Is it something you can maintain? I'm not interested in anything that's not sustainable. Friendships, investing, careers, podcasts, reading habits, exercise habits, if I can't keep it going, I'm not interested in it. And I think the only way to really do that is if you are going out of your way to live life at like 80 to 90% potential, if you're always trying to squeeze out 100% percent potential for something, Almost certainly it's going to lead to burnout, whether it's a friendship or a relationship or an investing strategy. So I think it's not easy thing to do. And if you're a type A person, it's almost impossible to do. But going out of your way to live life at 80% has always been a strategy that I want to do just because I want to keep it going for a long time.

#702 — Morgan Housel — Contrarian Money and Writing Advice, Three Simple Goals to Guide Your Life, Journaling Prompts, Choosing the Right Game to Play, Must-Read Books, and More

The Tim Ferriss Show

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

While Algorithmic Decision-Making Does Suffer From Bias, It Offers the Potential for Unparalleled Transparency In the Decision-Making Process Summary: Algorithms offer a transparent and accountable way for decision making. They can detect bias and perpetuated patterns, but must be transparent, independently audited, and not proprietary or snake oil. Transcript: Speaker 1 And then the response comes back saying yes but if you're basing it on historical data then you're feeding in biases of the past which you're going to propagate into the future there Is a kind of new attitude about all this which is kind of orthogonal to these two axes which I personally find pretty compelling and it's come up in from a couple of different places independently I could drop a few names but let me just say that the attitude is that algorithms at their best offer a new way for decision making to be transparent and accountable that's at their best So you know if an algorithm is something that everyone understands how it works everyone understands why we are chose to use this algorithm how it was trained and it's something which Can be independently audited it's even something which could be tinkered with to see if it could be made more fair and more accurate that kind of algorithm could raise the standard of Decision making in many areas and let us detect bias where it crops up and also help us detect where historical patterns are being perpetuated and what we might do to fix that but the big But is they have to be transparent they have to be independently audited they can't be proprietary and opaque and hidden behind veils of intellectual property and they also can't just Be snake oil right so there is a lot of snake oil out there there's a lot of products being put out to market which have not in any sense been independently verified or validated and where Their users and customers frankly don't really know whether their results ought to be interpreted the way they ought to be interpreted and so there needs to be a lot more critical thinking Aimed at these

Glen Weyl & Cris Moore on Plurality, Governance, and Decentralized Society

COMPLEXITY: Physics of Life

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