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A batch of the best highlights from what Quinn's read, .

The danger, and you see it often in investing, is when people become too McNamara-like – so obsessed with data and so confident in their models that they leave no room for error or surprise. No room for things to be crazy, dumb, unexplainable, and to remain that way for a long time. Always asking, “Why is this happening?” and expecting there to be a rational answer. Or worse, always mistaking what happened for what you think should have happened. The ones who thrive long term are those who understand the real world is a neverending chain of absurdity, confusions, messy relationships, and imperfect people.

Does Not Compute

collabfund.com

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

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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