I’m sorry to say I found this reflection by Adam Briggle almost entirely uninteresting. Of course we feel the absence of our tools. Is there really any philosophy to be done there?

In biographies and brands, after some clear examples Jacobs notes that many accusations of “factual errors” are really brand defenses:

When they said that Jacobs makes many factual errors, they weren’t even really making a truth claim, they were uttering a spell to ward off the stranger. They were placing me outside their Inner Ring.

~ ~ ~

In vendoring culture, I’m fascinated by the parallels he draws between vendoring code, and what Gene Luen Yang has done by incorporating DC Comics' earliest racist caricature into a new comic:

What Yang has done is moral repair through vendoring code &em; in this case ... cultural code. And note that Yang has not ... simply pointed to code created and maintained by someone else. ...he could only correct it by making it his own.

Had I read both, I still wouldn’t have made that connection. Spark.

~ ~ ~

Frictionless note-taking produces notes, but it doesn’t - for me - produce memory.

HTT Nuño Sempere’s January forecasting newsletter. And be sure to check out his marvelous Metaforecast service!

~ ~ ~

So: Metacululs and RootClaim give very different probabilities that COVID-19 originated in a lab (see earlier post summarizing Monk):

• Metaculus: 15% for Hubei lab origins (either accidental or deliberate) - median never went above 30% during the last year.
• RootClaim: 76% accidental release, and 2% deliberate, based on a (simplified?) Bayesian analysis.

Metaculus has ~3K forecasts on that question over the last year+, and over 260 comments, most well-informed. They’ve done well in COVID-19 forecasts vs. experts. (And famously one of their top forecasters nailed the pandemic in late January 2020, as Sempere reminds us.)

Rootclaim, as far as I can tell, begins with some crowdsourcing to formulate hypotheses, get initial probabilities, gather sources, and maybe to help set likelihoods. Then they do a Bayesian update. At one point they used full Bayesian networks. It seems this one treats each evidence-group as independent.

Both are heavily rationalist and Bayesian-friendly, and had access to each other’s forecasts. So the divergence is quite interesting - I wish I had time to dig into it some more.

The Excel row-limit inadvertently prevented contact tracing for two weeks in the UK, causing a natural experiment. Using outcome data the team estimated the gap caused 125,000 extra SARS-COV-2 cases and 1,500 COVID-19 deaths. Ouch.

ncrc.jhsph.edu/research/…

Sullivan on SAT

Killing the SAT Means Hurting Minorities

While I’m thinking of Sullivan, this from his newsletter, regarding a conversation on his podcast:

When you regard debate itself as a form of white supremacy, you tend not to be very good at it.

Psychic AI

FollowTheArgument on Inferring Political Orientation From a Single Picture reviews a recent paper showing algorithms can do this an astonishing 70% of the time, beating humans (55%) and a 100-item personality inventory (66%).

It’s still possible it’s latched onto some irrelevant or fragile feature set, but (a) they cropped close to the face, (b) they controlled for age/sex/race, (c) they cross-validated, and (d) they tested models from facebook on photos from other sites, and verce visa. Given the 2,048 features extracted by the facial image classifier, even regression did as well.

It seems ~60% is easily-named transient features like head-tilt, facial expression, etc. Leaving the rest as-yet-unnamed.

It’s tempting to go to physiognomy, but consider the following things humans do specifically to signal their affiliations:

• Makeup amount and style
• Beard type
• Earrings, other jewelry
• Hair style

What’s fascinating is how poorly humans do. But then, that result might be very different if the subjects were trained cold-readers.

Republicans embracing “class”

FTA also covers Scott Alexander’s Modes Proposal. Good read.

Muse of Seuss

I’ve been musing about all the Seussing. Social media discussions, and reading the spectrum on Flip Side (recommended).

I’m not especially qualified, but it seems to me:

• Liberals are right the board’s decision probably isn’t cancellation. (It depends on motivation, which we’re likely to get wrong.)
• But eBay’s action is cancellation. It’s illiberal, and wrong. It’s also downright silly given what eBay still sells.
• Conservatives make a strong case that most of the alleged offenses really weren’t – see Cathy Young’s take for why anyone thought so. If I Ran the Zoo being a notable exception.

Worth remembering:

“Among the people I work with in medical schools, there’s a strong adherence to what they call the health-literacy model, which is that physicians really believe that if you tell people the right information they will make decisions for themselves you yourself would make. And that’s an incorrect assumption.”

The New Yorker

Despite the title, I found the article reassuring.

Key quotes from this post:

Snell:

incompatibility comes for every abandoned app eventually

Rendle:

on the web we don’t really own any space, we’re just borrowing land temporarily.

Jacobs:

My data I own, my internet presence I rent.

it’s quite likely that I will outlive all my work, and I’m just fine with that. So I’ll write in venues that give me pleasure,

Worth reading in entirety, Alan Jacobs reflects on an essay by Douthat:

Such a system, predictably, was terrible at generating the kind of outward-facing, evangelistic conservatives who had made the Reagan revolution possible.

He ends by saying Antonin Scalia was the sole survivor of the Old Republic, making Amy Coney Barret the Last Jedi.

(OK, Douthat doesn’t use Star Wars. But Sunstein did. I just blended them.)

Where Douthat muses on Trump’s loss, Ian Leslie reflected on Biden’s victory over both Sanders and Trump:

It's worth spending a bit of time on what it means to be moderate.

Turns out Leslie has a new book, Conflicted:

Disagreement is the best way of thinking we have. It weeds out weak arguments, improves decision-making, leads to new ideas, and, counter-intuitively, brings us closer to one another. But only if we do it well - and right now, we’re doing it terribly.

Looking forward to it. Mercier & Sperber demonstrated that disagreement is how groups think, and that under the right conditions, they vastly outthink people.

For some gentle advice on How to Think, try Alan Jacobs' book by that name. We all cover the philosophy & cognitive science. Jacobs tackles the human component:

[We describe] argument as war ... because in many arguments there truly is something to be lost, and most often what's under threat is social affiliation. [My bold.]

What to do?

6. Gravitate, as best you can, in every way you can, toward people who seem to value genuine community and can handle disagreement with equanimity.

Slogan on an ad for scrum training. Featured in the the 2015 talk “Agile is Dead”.

Dave Thomas shows what goes wrong when “Agile” becomes a proper noun, and talks about reclaiming agility.

• Find out where you are.

• Take a small step towards your goal.

• Adjust your understanding based on what you learned.

• Repeat.

• [All things equal], take the path that makes future change easier.

Gelman’s recent short post on Relevance of Bad Science for Good Science includes a handy Top10 junk list:

A Ted talkin’ sleep researcher misrepresenting the literature or just plain making things up; a controversial sociologist drawing sexist conclusions from surveys of N=3000 where N=300,000 would be needed; a disgraced primatologist who wouldn’t share his data; a celebrity researcher in eating behavior who published purportedly empirical papers corresponding to no possible empirical data; an Excel error that may have influenced national economic policy; an iffy study that claimed to find that North Korea was more democratic than North Carolina; a claim, unsupported by data, that subliminal smiley faces could massively shift attitudes on immigration; various noise-shuffling statistical methods that just won’t go away—all of these, and more, represent different extremes of junk science.

And the following sobering reminder why we study failures:

None of us do all these things, and many of us try to do none of these things—but I think that most of us do some of these things much of the time.

January 6 moved Randy Pherson at Globalytica to ask if there is an active insurrectionist movement in the US.

Before clicking, at least quickly decide whether you would rate these as High, Medium, or Low (image from his post):

Then click to see ratings from a dozen of Pherson’s colleagues - probably professional or retired analysts.

Just re-found this @ayjay essay in an old tab.

The question I would ask churches that are re-opening without masks or distancing, but with lots of congregational singing, is: How do you think infectious disease works, exactly? How do you think COVID–19 is transmitted? What’s the theory you’re operating on?

I still know people using an incoherent mix of, well, all of these:

• There is no real pandemic.
• It’s a Chinese bio-weapon.
• Masks (etc.) don’t work.
• There’s easy and effective treatments.

Writing for IEEE Spectrum, Joanna Goodrich says that Deep Blue beat Kasparov because was just so fast.

The supercomputer could explore up to 200 million possible chess positions per second with its AI program.

But it wasn’t. Fast enough. Not really. IBM didn’t expect to win, just to lose less badly. Kasparov won the first game. Lost the second. Drew three.

In an account I read years ago (Pandolfini?), it came down to psychology. Deep Blue was doing better than expected, and K started to doubt his preparation or understanding.

Then Deep Blue played a move that spooked Kasparov into thinking it was far faster than it really was, and (uncharacteristically) he panicked and resigned.

But the machine itself had panicked. A bug made that move random.

This recent article roughly agrees with my decades-old memory, supplying the bit I forgot about it being a bug.

Sam Rocha, In America Magazine

Well, this seems backwards. Hopefully Janelle Shane will have a delightful and silly riposte.

www.washingtonpost.com/technolog…

Huh. My age group (45+) has about 25% more deaths this year - roughly the same excess % as for 85+. Just based on eyeball and spot-check, but I’m surprised - I expected to have much lower % increase than 85+. CDC chart

CDC total deaths snapshot: December weekly #s gained about 4,500 vs. two weeks ago: there are now 4 weeks right near 80K, slightly above the highest April week.

That’s bad. But still hard to square with covidtracking deaths being 50% higher than in April.

Update 19-Feb

Week of 26-Dec is now at 81,406, up by ~1K. The week of 2-Jan is higher now, above 82K, gaining 1-2K.

#### Update 23-May

December totals are now about +26K versus April, or about +6,500/week. That’s pretty much all the discrepancy I was concerned to explain.

That further supports the live CovidTracking numbers from last autumn.

“Either we can all be cold… or we can live in Florida.”

The thing I read today was Yudkowsky on r/WallStreetBets - I did not know that.

Essay worth reading in its entirety: The Great Reinforcer by Stuart Ritchie.

To be sure, out of the gloom of the pandemic came some incredible advances – the stunning progress made on vaccines chief among them. But these bright spots were something of an exception. For those of us with an interest in where science can go wrong, the pandemic has been the Great Reinforcer: it has underlined, in the brightest possible ink, all the problems we knew we had with the way we practice science.

Acknowledging stunning successes in the science of COVID-19, he reviews our regrettable and predictable failures. And hitting a little too close for comfort, notes how much harm comes from a desire to help.

It seems flu counts really are extraordinarily low. Sure, we’re missing cases because people aren’t getting tested as much, but of lab tests done, positivity is down 100-fold.

A good column by our SVP for technology & innovation.

This was a sobering take on possible downsides of Universal Basic Income. HTT Bryan Caplan.

A friend notes that the US has a long of equating vaccines and public health with commie conspiracies. This from 1955, citing US Rep. Clare Hoffman.

What do today’s anti-vaxxers think of the polio vaccine?

~ ~ ~

Among the saner anti-vax objections is the observation that any prior exposure could lead to an overactive immune response in a later exposure – a leading explanation for the 1918 lethality. The careful objectors say simply, “we don’t know it won’t”. True, though I’d be curious whether their odds are notably different from pro-vaxxers. (Do they both agree we’re x% sure it won’t, and just value that differently, or do they have very different x?)

According to my social media, a popular version of the objection is that something is so wrong with the vaccine that half the vaccinated population dies in 5 years, from overreacting to the common cold, or some variant of “gray goo”. This appears to be as informed as the polio-vax scare above.

A stronger version would be that we recreate 1918, but bigger. Suppose SARS-COV-3 appears in 2048, and has a similar relationship that Spanish flu (1918) had to Russian flu (1889): those who got COV-2 (or its vaccine) have a hyperactive immune response. In a world where we don’t vaccinate now, maybe 1/3 of the population gets COV-2, and so suffers heightened mortality in 2048. In the world where we vaccinate everyone, the whole population faces heightened mortality in 2048.

A great deal turns on “heightened”. Like meteor strikes, the main force comes from an exceedingly rare worst-case event. If it’s worth spending on meteor defense, shouldn’t we “spend” to avoid a vaccine own-goal, however unlikely?

It’s worth remembering some things about 1918:

• The priming seems mostly to have affected those exposed in early development, not universally. Hence the peak mortality at 28 years old.
• Even that mortality was 5-10%, not 90%. (And I’m pretty sure case fatality, so infection mortality would be more like 1-3%.)

So the bookends choice looks more like:

1. Do nothing. COV-2 infects about 1/3 of the planet, and ~12M people die. So, about 10M more than now. COV-3 does something similar, but infection mortality is 1-3% among 28-year-olds, so globally we lose up to 1% of them. (Unless we’re prepared for it, and prevent secondary infections.)

2. Vaccinate. COV-2 stops relatively soon, so maybe 5M total (using Metaculus' forecast for end of 2021.) COV-3 does something similar, but now peak infection mortality among 28-year-olds olds is more like 3-9%, so globally we lose 1-3% of them. (Unless we’re prepared for it.)

Scenario 2 is bleak enough - and you can tweak it to be worse. But in this 1918-specific version, it’s mostly an argument against vaccinating the pregnant and very young. Two groups we already tend to exclude.

But that’s just one scenario. Presumably whatever happens won’t look exactly like 1918. We don’t know what it will look like. But we do know we can probably save 7M lives now by vaccinating. The weight of the “what if” scenarios might be a good argument for limiting vaccination to some degree (just in case), but seem a poor argument against not doing it at all.

Thought exercise: suppose the fastest, cheapest, best way to immunize the population was via GMO corn? I assume it would have no effect on the arguments. But would it shift the battle lines?

[Edit: the thought exercise is not intended as a desirable alternative. It’s here to pump intuition among pro-vax but anti-GMO folks, as the argument outlined above seems similar to anti-GMO arguments. ]