verteu

As touched on in the article: The data's not IID, and there hasn't been very much "time" to generalize across.

Safely aligning a powerful CEO is difficult.

Yes, the quote was "Ads plus AI is sort of uniquely unsettling to me. I kind of think of ads as a last resort for us for a business model." (Sam Altman, Harvard 2024)

I agree, the conjecture never says anything about a proper map.

No, housing those people is only half the budget, so it's like $25k/person.

It's unlikely there's a trivial arbitrage to eliminate homelessness in a city full of engineers.

Not likely: SF has ~7,973 homeless people now, and current spending provides housing for 14,498 "previously homeless" people: https://media.api.sf.gov/documents/Agenda_Item_9_HSH_Budget_...

Thus, cutting all budget for cash transfers could increase homelessness by 80%! (Are those 14,498 now-homeless people eligible for this year's $100k? They can't be, since you already spent it on the 7,973 currently-homeless people).

Model the situation as "X(t) people become homeless at year t, Y(t) people become housed at time t," and you'll see the most important metric is "how much can we decrease X and increase Y per dollar spent"?

"Number of dollars per current homeless" is not really meaningful at all.

This is a fallacy because it's not the same people homeless each year. There's substantial turnover in the homeless population.

"Replace services with direct transfers" would eliminate homelessness for 1 year. Then new people would become homeless, and you'd have no services, because your budget is already committed to the "year 1 homeless-cohort."

The money spent grows quadratically (not linearly) over time.

Here's what I see on desktop: https://i.imgur.com/vuA2Y3w.png

Is this an artifact of dynamic resizing at small resolutions?

Rent seeking, *according to the Georgist*

Only Georgists believe that. And it's the rent of the "bare land", not including the housing constructed on it.

Seems the actual article is here? https://www.texasmonthly.com/news-politics/tesla-autopilot-c...

You can compare modeled heat deaths across different countries, Western Europe is still significantly higher. Eg Figure 3C in https://pmc.ncbi.nlm.nih.gov/articles/PMC7618246/

It doesn't affect life expectancy much, because most deaths are among the elderly (70% over 80 IIRC).

This simulation claims otherwise (though I agree it's hard to believe):

A significant degradation of external thermal comfort can also be seen in the simulations, as heat released by AC systems warms the outside air (see figure 3). The temperature increases due to AC depend on the time of day and on the characteristics of the heat wave, mainly its intensity. On average, the duration spent under high heat stress conditions in the streets is increased by about 20 min per day because of AC.

https://iopscience.iop.org/article/10.1088/1748-9326/ab6a24#...

Yeah, good point.

They're using a Benjamini–Hochberg correction (alpha=0.05) to account for multiple comparisons (see Table 2).

Obviously a rejected resume is more likely to be rejected by every other employer and an accepted resume is more likely to be accepted by every other employer.

But that wasn't the case for non-algorithmic screening. From the paper:

"By contrast, we find that when first round screening is not mediated by a single screening procedure, systemic rejections are close to the baseline. To support the empirical validity of our baseline, we study homogeneous outcomes in the largest study of first-round screening at U.S. employers to date. Kline et al. [38] generated 83000 synthetic resumes and submitted these resumes to vacant positions at 108 US companies between October 2019 and April 2021, a similar time period to our data. The companies, which are a subset of the Fortune 500,15 collectively employ 15 million workers. We analyze the homogeneity observed in the resulting callback outcomes in their data. We find that the baseline is an effective estimator of the systemic rejection rate for this dataset. As shown in Figure 3, the observed systemic rejection rate is accurately predicted by the baseline and a chi-squared goodness-of-fit test cannot reject equality of the two distributions (2 = 20.05, = 0.69). In other words, while the largest previous study observes systemic rejection rates consistent with employers making statistically independent decisions, the algorithmic hiring data shows significantly correlated outcomes that lead to higher-than-baseline systemic rejection rates."

The paper is here: https://arxiv.org/pdf/2605.27371

They find "disparate impact" of pymetrics across racial groups, but it doesn't seem like they controlled for anything.

I'm getting SSL_ERROR_RX_RECORD_TOO_LONG on Firefox.

It does not, as explained in the section "Are Landlords Rent Seekers?"

"Rent seeking" is more about making money by changing the rules instead of providing a service.

Counterintuitively, collecting rent is not considered "rent-seeking" by the econ definition, eg: https://www.investopedia.com/terms/r/rentseeking.asp

Opposing Israel's flagrant violations of international law is not hate speech or discrimination against Jews, regardless of how desperately you want it to be.

Not quite. That was Black Cube, a second Israeli spy firm accused of election meddling: https://www.politico.eu/article/robert-golob-slovenia-eu-pro...

Alameda was only profitable in the years when Bitcoin was going up. By 2022 their trading operations were deeply negative (hence the decision to steal customer funds).

Why not simply use median life expectancy, which is more robust to fraud and outliers, instead of "number of centenarians"?

It's weird to me that standardized tests were demonized as anti-equity rather than GPA

I think it's because socioeconomic status is much more correlated with tests (40% of variance explained) than grades (<10% of variance explained): https://cshe.berkeley.edu/news/family-background-accounts-40...

https://drive.google.com/file/d/1qeeeGJ4100oM-mK0g-1Z34VqEaF...

I'm surprised the correlation between SES and grades is so low.

Indeed GP is falsely equating "wealthiest" with "highest taxable income".

They are likely referring to a stat like this: https://usafacts.org/articles/who-pays-the-most-income-tax/

Indeed, the ultra-wealthy pay far less than 40% effective estate tax. Seems closer to 15% due to creative accounting, which is further reduced to 6.8% by charitable contributions:

Specifically, for single decedents, estate taxes paid equal 6.8% of the value of Forbes wealth at death. The value of their gross estate is 39% of the Forbes estimate of their wealth. This large gap, already noted in earlier work (Raub et al., 2010), is likely to reflect the various techniques available to high-net-worth individuals to undervalue assets in the context of the estate tax. Taxable estate is then 45% of gross estate (due to deductions primarily gifts to charities) and on that base the tax rate is 39% (Balkir et al., 2025, Table 4 Panel B).

https://www.nber.org/system/files/working_papers/w34170/w341...

One way to avoid the tax is to rent out the residence: https://comptroller.nyc.gov/reports/the-pied-a-terre-tax-and...

It's interesting that people choose to leave their properties vacant - They're effectively "taxing" themselves by foregoing rent (4+%/yr cap rate).

Is vacant real estate even a good investment?

Many places like this in the Rust Belt or Appalachia: https://en.wikipedia.org/wiki/Decline_of_Detroit https://en.wikipedia.org/wiki/Lists_of_ghost_towns_in_the_Un...

No, it's about as "controversial" as claiming lead exposure is bad for children's brains.

Do we have RCTs for that? Or might we reasonably shape our priors from the hundreds of studies using a dozen different causal methodologies, which all find the same result?

Neat, thanks for sharing! I suppose drones are the most likely explanation?