This uses a well-chosen thought experiment to demonstrate that our understanding of ‘poverty’ is maybe somewhat askew. I tend to lean toward feeling like we — including poor people, at least in the US — have become much better off, and that UBI could solve a lot of the remaining problems. This seems like a legitimate challenge to that view that I’ll have to spend some time thinking about.

I think this is the problem with saying that modern society can’t have real poor people, because they own an amount of clothing and fabric that would’ve once put somebody well into the realm of nobility, back when women spent most of their days stretching wool with a distaff in order to let anyone have clothes at all.  That amount of fabric doesn’t mean you can’t be poor, just like having vast amounts of oxygen in your apartment doesn’t rule out poverty.  It means that a resource which was once very expensive, like fabric in medieval Europe or oxygen in Anoxistan, has become cheap enough not to mention.

And that is an improvement, compared to the counterfactual!  I’m glad I don’t have to constantly worry about running out of clothing or oxygen!  It is legitimately a better planet, compared to the counterfactual planet where life has all of our current problems plus not enough oxygen!

But if you agree that medieval peasants or hunter-gatherers can be poor, you are acknowledging that no amount of oxygen can stop somebody from being poor.

Then fabric can be the same way: there can be no possible sufficiency of clothing in your closet that rules out poverty, even though somebody with plenty of clothing is counterfactually better off compared to somebody who owns only one shirt.

The sum of every resource like that could rule out poverty, if you had enough of all of it.  What would be the sign of this state of affairs having come to hold?  What would it be like for people to not be poor?

I reply:  You wouldn’t see people working 60-hour weeks, at jobs where they have to smile and bear it when their bosses abuse them.

Universal Basic Income and Poverty — LessWrong

This is a very nice demonstration of the robustness against manipulation of well-funded prediction markets. The attempted manipulators spent millions of dollars to drop Trump 5% and bump Harris 3%. The market quickly took their money, pushing both candidates back to (roughly) their previous prices, and the manipulators were unable to achieve their goal, which only required them to keep the market distorted for a three hour period.

Of course this particular market is unusually liquid! Markets that don’t have much liquidity or many people watching them are easier to distort for longer. But if prediction markets continue to thrive (despite recalcitrant regulators), we should expect to see them become much more liquid (more like commodity exchanges or options markets, which are quite tough to manipulate — although the successes make for fascinating stories).

There was a spectacular attempt at manipulation on Polymarket yesterday, and you can see evidence of it in the following sharp price movements:

What happened was this. A group of traders bet heavily on Harris and against Trump in an attempt to push her into the lead for a couple of hours. The sums involved were quite large, with one trader alone wagering about 2.5 million dollars. The goal was to ensure that the Harris contract would have the higher price for a majority of minutes during the three hour period between noon and 3pm EST on Friday, in order to profit from a derivative market that referenced prices in the primary market.

https://rajivsethi.substack.com/p/a-failed-attempt-at-prediction-market

The excellent ‘Roots of Progress’ blog investigates a very interesting question.

Personally, I’ve lately been starting to believe that precision manufacturing is much more difficult and finicky than people generally realize. Even if given precise and comprehensive plans for a high-precision product, it’s very difficult for a new manufacturer to start manufacturing it without hands-on help from someone who’s actually done it. This reaches its apex in semiconductor chip manufacturing, which is so difficult that basically only one company, TSMC, is able to manufacture the high-end wafers.

(this has been of interest to me because it somewhat decreases the risk of human extinction from AI; killing all humans is a losing move for any AI system not yet capable of this level of very-high-precision manufacture, which may require significantly greater-than-human intelligence to be able to reliably spin up from scratch on any reasonable timeframe)

The bicycle, as we know it today, was not invented until the late 1800s. Yet it was a simple mechanical invention. It would seem to require no brilliant inventive insight, and certainly no scientific background.

Why, then, wasn’t it invented much earlier?

Source: Why did we wait so long for the bicycle?

If this pans out, it seems like a big improvement!

The AI was trained to detect statistical bumps in real-time seismic data that researchers had paired with previous earthquakes. The outcome was a weekly forecast in which the AI successfully predicted 14 earthquakes within about 200 miles of where it estimated they would happen and at almost exactly the calculated strength. It missed one earthquake and gave eight false warnings.

https://scitechdaily.com/artificial-intelligence-predicts-earthquakes-with-unprecedented-accuracy

I have in the past praised Seeing Like a State; this is by far the most interesting criticism of it that I’ve encountered. That said, I think that the critique leans too heavily on a view of Modernist motivation as fundamentally aesthetic; in many of the cases Scott discusses, it was purely pragmatic, eg in order to more effectively impose taxation.

A defence of metis (and Scott is right that it needs defending) must be mounted with great care, since otherwise it looks like an attack on education itself, which does more than anything else to help people discard those aspects of their local traditions that do them harm. Scott would be horrified to be associated with the school of conservatives who oppose education on the grounds that it gives power to the great unwashed, but they at least have the virtue of brutal honesty. What doesn’t horrify him, but ought to, is his keeping the company of the ‘something-precious-is-lost-to-modern-life-once-mothers-no-longer-circumcise-their-daughters-and-you-can-buy-rambutan-in-Sainsbury’s’ school. There is no feebler pretext for conservatism than the anxiety that progress is somehow inimical to charm.

https://www.lrb.co.uk/the-paper/v21/n11/paul-seabright/the-aestheticising-vice

Presumably over time this’ll lead to a different equilibrium where either fewer appeals are approved, or the number of required hoops will increase. But seems really useful for now.

…most denials can be successfully appealed. However, most people don’t appeal denied claims, with a study showing that Affordable Care Act patients only appeal about 0.1% of denials. Second, anybody, not just doctors, can file a claim with their insurer. You could do it yourself, just like Karau did.

She actually started helping friends with appeals and then wondered whether she could automate the process. The result is the Fight Health Insurance website. Karau spent a year developing the open-source AI platform before making it available to the general public in the US. The engineer spent about $10,000 to create the service.

Health insurance claim denial appeal: This AI website can help

This is a lovely meditation from Sarah Perry on the meaning of mess. I don’t think that I agree with her conclusion (I agree that ‘high-entropy’ isn’t sufficient, but maybe something like Murray Gell-Mann’s effective complexity would work?) but it was a joy to read.

Watts observes that elements of the natural world – clouds, foam on water, the stars, human beings – are not messes, though the nature of their order remains inscrutable, and Watts doesn’t try to pin down its precise nature. Mess seems to be somehow a property perceptible only in the presence of human artifacts. Is this the result of some kind of aesthetic original sin on the part of humans, uncanny beings severed from the holiness of Nature? I hope not. “Humans are bad” is a boring answer.

We can learn something about order from the mystery of mess. We start here: a cloud is not a mess, but an ashtray full of cigarette butts is a mess. In tracking down why this is so, we will find, through the lens of the mess and the non-mess, a clue to the hidden orders in our minds.

Tendrils of Mess in our Brains

This is what I personally try to strive for; it’s good to see that there’s been some academic work on defining and measuring it. Sorry to link to the low-quality Psychology Today; there just isn’t much out there yet for a lay audience on the topic.

date our beliefs takes cognitive effort. We need to override our initial impulses. This is further complicated when a belief is challenged that is central to us (Haidt, 2012). Nevertheless, it can serve as a cognitive aspiration. We will certainly fall short of being actively open-minded, but when we sense we are in Refutation Mode, we can try to momentarily recalibrate and see if being actively open-minded may serve us in the situation.

For example, in making billion-dollar investments, Ray Dalio, the founder of the world’s largest hedge-fund, places the dictate to be “Radically Open-Minded” as one of his key management principles. As he states:

“Radical open-mindedness is the ability to effectively explore different points of view and different possibilities…It requires you to replace your attachment to always being right with the joy of learning what’s true” (2017, p. 187).

https://www.psychologytoday.com/us/blog/learning-at-work/201805/do-i-really-have-to-be-actively-open-minded

https://www.thisiscolossal.com/2024/08/beth-cavener-trust/

https://www.thisiscolossal.com/2024/08/beth-cavener-trust/