trentmkelly/LessWrong-43k huggingface dataset:
How the response to a pandemic affecting mainly children would look like?
by mukashi — 2022-01-05T10:15:49.223Z

At the beginning of the pandemic, I was unable to predict how utterly incompetent most Western governments were going to be to handle the situation at all levels (barring some honourable exceptions) and I have had to update more than once my model of how inefficient the political structures are to handle crises like this one. Have I updated enough my model? I am not sure. I am barely surprised with any new intervention they announce, mostly because in my (updated) model of the world, we live in a deeply inadequate system where the people in charge are not really trying to minimize the damage of COVID.

Imagine an alternative universe where the virus affects mainly children, i.e. the younger someone is, the higher the risk. About 10% of newborns getting COVID will die. It still might affect adults but it is way less likely. Old people are mostly asymptomatic. My question is, how different would have been a world like this? Would have we seen the same amount of controversy around the vaccines, mask mandates, etc? There is a part of me that believes that politicians would have taken way harsher measures to nip it in the bud, that the bureaucracy would have been forced to evolve faster than the virus and that we would have not seen the same polarization we have seen regarding lockdowns or any other intervention. I would dare to say that the pandemic could be over by now. However, at the same time, I am thinking that I might not have updated enough my model of the world and the system we live in is so absolutely disastrous that not even a situation like this would have forced society into a better Nash equilibrium.
A Reaction to Wolfgang Schwarz's "On Functional Decision Theory"
by Heighn — 2022-01-05T09:00:42.777Z

So I finished reading On Functional Decision Theory by Wolfgang Schwarz. In this critique of FDT, Schwarz makes quite some claims I either find to be unfair criticism of FDT or just plain wrong - and I think it's interesting to discuss them. Let's go through them one by one. (Note that this post will not make much sense if you aren't familiar with FDT, which is why I linked the paper by Yudkowsky and Soares.)

Schwarz first defines three problems:

Blackmail. Donald has committed an indiscretion. Stormy has found out and considers blackmailing Donald. If Donald refuses and blows Stormy's gaff, she is revealed as a blackmailer and his indiscretion becomes public; both suffer. It is better for Donald to pay hush money to Stormy. Knowing this, it is in Stormy's interest to blackmail Donald. If Donald were irrational, he would blow Stormy's gaff even though that would hurt him more than paying the hush money; knowing this, Stormy would not blackmail Donald. So Donald would be better off if here were (known to be) irrational.

Prisoner's Dilemma with a Twin. Twinky and her clone have been arrested. If they both confess, each gets a 5 years prison sentence. If both remain silent, they can't be convicted and only get a 1 year sentence for obstructing justice. If one confesses and the other remains silent, the one who confesses is set free and the other gets a 10 year sentence. Neither cares about what happens to the other. Here, confessing is the dominant act and the unique Nash equilibrium. So if Twinky and her clone are rational, they'll each spend 5 years in prison. If they were irrational and remained silent, they would get away with 1 year.

Newcomb's Problem with Transparent Boxes. A demon invites people to an experiment. Participants are placed in front of two transparent boxes. The box on the left contains a thousand dollars. The box on the right contains either a million or nothing. The participants can choose between taking both boxes (two-boxing) and taking just the box on the right (one-boxing). If the demon has predicted that a participant one-boxes, she put a million dollars into the box on the right. If she has predicted that a participant two-boxes, she put nothing into the box. The demon is very good at predicting, and the participants know this. Each participant is only interested in getting as much money as possible. Here, the rational choice is to take

...
Omicron in Biobot
by jefftk — 2022-01-05T02:50:05.235Z

I wrote a few weeks ago about how the increase in covid in Boston's
sewage was seasonal, and

didn't yet reflect
Omicron. Now this, though, this is Omicron:

We're at about 8x the previous peak and still climbing:

It also looks to be moving a bit quicker in the Southern half of the
system, possibly even peaking but that might be optimism:

Test positivity is very high: 22%
over the last seven days per the state dashboard, but 29% if you take the
most recent daily number and adjust for effect of the day
of the week. This, plus rapid testing now being much more common,
means that official case numbers are pretty hard to interpret, so
it's really nice to have the wastewater data as something consistent.
That is, unless Omicron makes people excrete more virus at a given
level of infectivity...

Comment via: facebook
Movie review: Don't Look Up
by Sam Marks — 2022-01-04T20:16:04.593Z

[There have already been some reviews of Don’t Look Up, for example Quinn Dougherty's, Nicholas Kross's, and Scott Alexander's. I’m posting this anyway because I think I say pretty different things than these reviews; in particular, my impression of the movie was much more positive.]

[Epistemic status: trying to extract morals about x-risk from an allegory, but beware that some parts might accidentally

generalize from fictional evidence

.]

[Spoilers for Don’t Look Up on the level of: I tell you the entire plot.]

I think of Don’t Look Up as being divided into two parts.

The first part is about a relatively straightforward x-risk scenario: a grad student discovers a comet which will impact the Earth in 6 months, there’s some issues with coordination and getting the powers-the-be to take the problem seriously, but eventually the relevant players recognize the direness of the threat and launch rockets to deflect the comet. But then there’s a twist: actually the comet has lodes of valuable ore, $140 trillion of it. The deflection mission is aborted, and the second part of the movie begins.

The second part represents a much more interesting x-risk scenario: now some players have an incentive to trade off [probability of averting the x-risk] for money. This is more dire, and much more reflective of the likely x-risk scenarios we could face, especially AGI. Accordingly, where the movie’s society managed to pull itself together enough to avert the simple comet scenario in part 1, their levels of coordination and competence are not high enough to avert the modified comet-with-massive-economic value scenario in part 2. The comet impacts Earth and everyone dies.

The transition between parts 1 and 2 is kinda awkward. In the middle of the deflection mission – the launch has gone off flawlessly, the rockets are in the air, and people are already celebrating – someone informs the president that actually the comet is extremely valuable, and they abort the mission. It sort of seems like the movie is trying to communicate something like “okay good job, you defeated the comet on easy mode, but now let’s change things up.” In my mindcanon, the deflection mission goes off perfectly, the Earth is saved, and the movie ends in triumph. Then a new movie starts, Don’t Look Up 2, with the modified premise. I think this is a less confusing way to think about the story. Below ...
More Is Different for AI
by jsteinhardt — 2022-01-04T19:30:20.352Z

Machine learning is touching increasingly many aspects of our society, and its effect will only continue to grow. Given this, I and many others care about risks from future ML systems and how to mitigate them.

When thinking about safety risks from ML, there are two common approaches, which I'll call the Engineering approach and the Philosophy approach:

The Engineering approach tends to be empirically-driven, drawing experience from existing or past ML systems and looking at issues that either: (1) are already major problems, or (2) are minor problems, but can be expected to get worse in the future. Engineering tends to be bottom-up and tends to be both in touch with and anchored on current state-of-the-art systems.
The Philosophy approach tends to think more about the limit of very advanced systems. It is willing to entertain thought experiments that would be implausible with current state-of-the-art systems (such as Nick Bostrom's paperclip maximizer) and is open to considering abstractions without knowing many details. It often sounds more "sci-fi like" and more like philosophy than like computer science. It draws some inspiration from current ML systems, but often only in broad strokes.

I'll discuss these approaches mainly in the context of ML safety, but the same distinction applies in other areas. For instance, an Engineering approach to AI + Law might focus on how to regulate self-driving cars, while Philosophy might ask whether using AI in judicial decision-making could undermine liberal democracy.

While Engineering and Philosophy agree on some things, for the most part they make wildly different predictions both about what the key safety risks from ML will be and how we should address them:

Both Engineering and Philosophy would agree on some high-level points: they would agree that misaligned objectives are an important problem with ML systems that is likely to get worse. Engineering believes this because of examples like the Facebook recommender system, while Philosophy believes this based on conceptual arguments like those in Superintelligence. Philosophy is more confident that misaligned objectives are a big problem and thinks they could pose an existential threat to humanity if not addressed.
Engineering and Philosophy would both agree that out-of-distribution robustness is an important issue. However, Philosophy might view most engineering-robustness p

...
How do you turn an idea into a reality? (warning: involves politics)
by Nicole Dieker — 2022-01-04T19:29:37.770Z

I am still relatively new to this community; if you do not want questions that imply or directly state political persuasions, I promise you won't get any more of them from me.

Let's say that there's a movement to implement a specific idea that you believe could have unusually positive societal benefits.

Could be a net positive for the entire world, in fact.

Let's say that the person leading the movement has hired a team to create a website with volunteer opportunities, and let's say you look at the opportunities that are on display and ask yourself "how does completing this task move us closer to the implementation of the idea"?

This might actually be two questions.

No, wait. Three questions.

The first question is "how do you evaluate volunteer tasks for their actual efficacy," i.e. "how do you decide what to spend time on," and I'm pretty sure I can find some answers in the Effective Altruism section of LW.

The second question is "at what point do you say ummmm telling your volunteers that you want to see 1000 letters to the editor published by the end of 2021 is a BAD GOAL that you will FAIL because YOU DON'T CONTROL THE OUTCOME and also YOU'RE CONFUSING OP-EDS AND LETTERS TO THE EDITOR, and MOST NEWSPAPERS WILL NOT ACCEPT LETTERS TO THE EDITOR THAT ARE NOT A RESPONSE TO A PREVIOUSLY PRINTED ARTICLE and this is a WASTE OF TIME without either sounding like a jerk or unwittingly volunteering to take control of the entire project?"

The second-point-five question is whether I should wittingly volunteer to take control of the entire project, or at least the volunteer tasks that are related to the industry I've worked in for the past decade.

The third question is how you make an idea into a reality, especially when it involves societal and governmental buy-in.

The (secret) fourth question is whether any of you can guess which idea I'm referring to, and whether you agree that it's worth trying to make real.
The Speed of Rumor
by NancyLebovitz — 2022-01-04T19:27:03.474Z

So I was talking with someone in the community about Michael Vassar (I should check for permission to put a name to this story), and they said that Michael encouraged people to take high doses of psychedelics.
I said he'd encouraged me to take psychedelics, but at ordinary doses.
And the person said, "Right-- one of the people who had a psychotic break said they'd taken high doses, but not that Michael had encouraged them." (I've seen a quote from one of the people Michael was alleged to have pushed into a psychotic break who said, no, Michael wasn't the problem.)
I'm glad they were meticulous enough to take the correction, but I'm spooked. I'm probably should have learned much earlier how easy it is for people to get reputation-damaging details wrong, but this was a very clear example.
I read a fair amount of https://www.lesswrong.com/posts/MnFqyPLqbiKL8nSR7/my-experience-at-and-around-miri-and-cfar-inspired-by-zoe, but ran out of steam for the whole thing. I was impressed by the community at least eventually taking some care to get things right, but I don't know if there's any discussion of what went wrong.
Omicron Post #12
by Zvi — 2022-01-04T15:50:01.288Z

It involved a backlog, but the USA reported over 1 million cases yesterday. That’s a lot of cases, and we’re missing a ton more of them. Schools, hospitals and all businesses face massive disruptions from people unable to work, even with the new CDC isolation guidelines.

So far, we’re holding up well, better than I expected even after previous severity estimates were adjusted. Things are going to be severely disrupted for a while, but not as severely as we might have feared, and even if we get a median outcome that is much better than the mean outcome given the tail risk of true disaster.

Still, brace yourself, and choose how you want to handle the next month or two. If you’re serious about trying to avoid Omicron, now is the time to show it.

Vaccine Effectiveness

A Danish study from earlier found large negative vaccine effectiveness. Large negative effectiveness is not a thing, we would know about it and the world would look very different, but anti-vax people are of course jumping on it and the attempt to explain isn’t going all that well. Which it mostly shouldn’t, in my view, because when you get nonsense results that are clearly nonsense results but you don’t control properly and so you publish anyway, what else do you expect?

I looked at the paper. They control for the basics, including geographical region.

VE was calculated as 1-HR with HR (hazard ratio) estimated in a Cox regression model adjusted for age, sex and geographical region, and using calendar time as the underlying time scale.

I’ve heard reasons that make it possible for vaccine effectiveness to go negative, but those reasons don’t seem compatible with large positive effectiveness shortly after two doses, and large positive effectiveness again after a booster shot.

More than that, check the sections on severity and hospitalization below. They make it very clear that being vaccinated offers a lot of effective protection and is very much a good idea, and getting boosted is an even better idea.

Treatment

CDC lifts the pause on anti-Delta monoclonal antibodies, says they can be used if Delta is still in your region and there aren’t other options available. My guess is there are still some places in America where this makes sense, since even a small chance of getting the old effectiveness is better than doing nothing, but this window is ending rapidly.

Quarantine, Isolation

...
The Map-Territory Distinction Creates Confusion
by Gordon Seidoh Worley — 2022-01-04T15:49:58.964Z

LessWrong isn't exactly founded on the map-territory model of truth, but it's definitely pretty core to the LessWrong worldview. The map-territory model implies a correspondence theory of truth. But I'd like to convince you that the map-territory model creates confusion and that the correspondence theory of truth, while appealing, makes unnecessary claims that infect your thinking with extraneous metaphysical assumptions. Instead we can see what's appealing about the map-territory metaphor but drop most of it in favor of a more nuanced and less confused model of how we know about the world.

The map-territory metaphor goes something like this: a map is a representation of some part of the world—a territory. The mind that models the world via thoughts can be said to create a map of the territory of reality. Thus, under the map-territory model, beliefs are true if they represent what we actually find when we investigate the territory directly. Or, if you want to add some nuance, the map is more accurate and thus closer to being true the better it represents the territory.

The map-territory model implies a correspondence theory of truth. That is, it's a theory of truth that says propositions are true to the extent they accurately represent reality. On the surface this seems reasonable. After all, the process of finding out what the world is like feels a lot like drawing a map of reality: you collect evidence, build a model, check the model against more evidence, iterate until the model is good enough for whatever you're doing, and if the model seems like it matches all the evidence you can throw at it, we might call the model true. But there are problems with correspondence theories of truth. I'll focus on the one that I think is the worst: unnecessary, metaphysical claims.

In order to set up a correspondence between map and territory and judge truth based on the accuracy of that correspondence, there must be an assumption that there is something we call "the territory" and that in some way we can construct a map that points to it. Whatever we think the territory is, we must presume it exists prior to establishing a criterion for truth because if we don't have a territory to check against we have no way to assess how well the map corresponds to it. Two common versions of the territory assumption are the materialist version (there's an external physical reality we o...
Promising posts on AF that have fallen through the cracks
by Evan R. Murphy — 2022-01-04T15:39:07.039Z

Yesterday on the Weekly Alignment Research Coffee Time call as people were sharing updates on their recent work, Vanessa Kosoy brought up her and Diffractor's post Infra-Bayesian physicalism: a formal theory of naturalized induction which she was interested in getting feedback on.

Vanessa seemed a bit disappointed/frustrated that this post had received no comments yet. I had to agree after learning that it proposes the first formal decision theory realizing naturalized induction, which has been an open problem in alignment for years. It's also been over 5 weeks since she posted it.

So why hasn't anyone commented? Well it's possible folks have just been busy since it's been the end of the year and the holidays. It also may have to do with that the post includes accompanying proofs and invokes some complex-looking maths; such papers take more time to digest and it's only a subset of people on this forum and LessWrong who are capable of doing so.

But it's also possible that the post was forgotten. Even though it may be important, since it's no longer on the front page of the Alignment Forum and hasn't been referenced anywhere else, nobody would think to look at it again unless it happened to come up in one of their searches or they were prompted about it. In other words, it may have just "fallen through the cracks".

This got me wondering about what other posts on the Alignment Forum might have fallen through the cracks. I did a quick search on the forum to see if I could find out. My search criteria was the following:

A post received substantial upvotes (arbitrarily 20+ points), suggesting that the community thought it was somewhat interesting or valuable
But it received no comments or pingbacks on AF - It may still have received comments on LessWrong though or comments/pingbacks by the original authors
It was posted more than 2 weeks ago
It's an original "researchey" post - I filtered out posts that were event announcements, linkposts, etc.

Here are the posts that came up in my search. I only went through about ~200 posts for this so consider it exemplary rather than exhaustive:

Infra-Bayesian physicalism: a formal theory of naturalized induction
Jitters No Evidence of Stupidity in RL
Sources of intuitions and data on AGI
How DeepMind's Generally Capable Agents Were Trained

To be sure, I don't expect all of these posts to necessarily be super important and in di...
[New Feature] Support for Footnotes!
by Ruby — 2022-01-04T07:35:21.500Z

It is with great excitement[1] that I am pleased to announce that the main LessWrong text editor[2] now has support for footnotes![3] A huge thanks to our friends over at the Effective Altruism Forum who coded this one up.

You can insert footnotes via:

1. Manually selecting text in the text box and selecting insert footnote from the footnotes menu icon.

The footnote icon is the [*] on the right.

2. Using Markdown syntax

Type [^n] where is the number of the footnote you wish to insert.
To insert a new footnote, use n that is <number of existing footnotes + 1>; to reuse an existing footnote, set n to be whichever footnote you are reusing.

Footnotes will automatically renumber as you add and delete them!

What's more, footnotes will render with hover-over previews once published:

Behold! A footnote hover-preview!

That's it. Go forth and create scholarly works!

^

I mean it, really. I've looked forward to us adding this support for years.

^

That is, the LW Docs editor, as distinct from the Markdown editor and legacy Draft-JS editor.[4]

^

The Markdown editor already had support for footnotes using Markdown footnote syntax.

^

Yes, footnotes can have footnotes. And those footnotes can reference themselves.[4]