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Inversion: Avoiding stupidity is easier than trying to be brilliant. Instead of asking, “How can I help my company?” you should ask, “What’s hurting my company the most and how can I avoid it?” Identify obvious failure points, and steer clear of them.
50 Ideas That Changed My Life - David Perell
perell.com
The people with the most accurate models of others tend to have diverse social networks
Summary:
To correct for this handicap, we need to listen to the oppressed in the population.
This includes laborers, students, and others who are usually not given a political voice. By expanding our social networks to include more diverse perspectives, policymakers can make better decisions based on a deeper understanding of societal trends and people's desires.
Transcript:
Speaker 1
But it sounds like this gives us a really clear pointer on how to correct for this handicap. And that we really ought to be like, perhaps when it comes time to make decisions on behalf of everyone, we should really be listening to whomever the oppressed are in that population. We should be really paying attention, for example, to laborers and students and people that are ordinarily not historically, not given a lot of political voice. And what you're saying, yeah, it's in other words, what we need to do is broader our social networks include in our social networks, those people who are typically not there. So if the policymakers who are making these important decisions should know as many different people as possible. And we show in related studies that people who have most diverse social circles are also best able to predict societal trends and to understand how the overall population lives and What people want.
Mirta Galesic on Social Learning & Decision-Making
COMPLEXITY: Physics of Life
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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