trentmkelly/LessWrong-43k huggingface dataset:
Meta Pivots on Content Moderation
by Zvi — 2025-01-17T14:20:06.727Z

There’s going to be some changes made.

Table of Contents

Out With the Fact Checkers.

What Happened.

Timing is Everything.

Balancing Different Errors.

Truth and Reconciliation.

Fact Check Fact Check.

Mistakes Will Be Made.

Where We Go From Here.

Out With the Fact Checkers

Mark Zuckerberg has decided that with Donald Trump soon to be in office, he is allowed to care about free speech again. And he has decided it is time to admit that what was called ‘fact checking’ meant he had for years been running a giant hugely biased, trigger-happy and error prone left-wing censorship and moderation machine that had standards massively out of touch with ordinary people and engaged in automated taking down of often innocent accounts.

He also admits that the majority of censorship in the past has flat out been a mistake.

Zuckerberg later talked more about this, and many related and unrelated things, on the Joe Rogan podcast. He says many fun things, like that most companies need ‘more masculine energy’ to balance their feminine energy, and he gives his usual terrible takes on AI which I cover elsewhere.

Zuckerberg is going to overhaul Meta’s entire moderation and censorship structure, replacing it over several months with something akin to community notes. He’s going to move standards back in line with actual community standards. And he’s going to move his content moderation teams from California to Texas, and push back against censorship worldwide, highlighting Europe and Latin America.

What Happened

The current review process reportedly started when one of Zuckerberg’s own posts got throttled because of concerns over medical content, and then snowballed from there.

How did it all go so wrong? Zuckerberg tells the story on Rogan, that he took complaints about misinformation and the need for fact checking as sincere, then after he hired people for this the slippery slope took over and before long they were censoring things that are in the mainstream discourse.

Here is a parallel discussion, about similar pressures at Zuckerberg’s philanthropy efforts, where he got asked to resign from Facebook during a staff meeting for insufficiently moderating the actual sitting President of the United States.

Matthew Yglesias: Lots of moderate people end up embracing conservatism because of backlash against left-wing excess, but it’s funny to do it when the left-wing exc

...
Tax Price Gouging?
by jefftk — 2025-01-17T14:10:03.395Z

In the aftermath of a disaster, there is usually a large shift in what
people need, what is available, or both. For example, people normally
don't use very much ice, but after a hurricane or other disaster that
knocks out power, suddenly (a) lots of people want ice and (b) ice
production is more difficult. Since people really don't want their
food going bad, and they're willing to pay a lot to avoid that, In a
world of pure economics, sellers would raise prices.

This can have serious benefits:

Increased supply: at higher prices it's worth running
production facilities at higher output. It's even worth planning,
through investments in storage or production capacity, so you can sell
a lot at high prices in the aftermath of future disasters.

Reallocated supply: it's expensive to transport ice, but
at higher prices it makes sense to bring it in from much farther away
than would normally make sense.

Reduced demand: at higher prices people who would normally buy
ice for less important things (ex: drink chilling) will pass.

Reallocated demand: if you have a chest freezer full of food,
you get more benefit from a given quantity of ice than I would with a
mostly empty fridge. All else equal, you are willing to pay more for
ice than I am.

On the other hand, raising prices in response to a disaster is widely
seen as unfair:

Allocation by price is never great for people who have less
money, but a disaster makes this existing inequality more painful.

Store owners are on average richer than customers, so profits
here are moving wealth from poorer people to richer ones.

Normally prices are kept in check by people shopping around,
either by observing prices in a range of places or by talking with
friends. These are both disrupted in disasters, which would likely
allow sellers to charge more.

So raising prices in emergencies is generally strongly socially
discouraged and often also illegal. Stores quickly sell out, there's
no increase in supply, and allocation is relatively arbitrary.

Is there a way to get the benefits of keeping prices responsive, while
mitigating
some of the unfairness?

Consider the introduction of congestion
pricing in NYC. Charging money to keep people from overusing a common
resource is a traditional economics solution, reducing traffic
jams and allowing streets to move more people in less time. Wh...
The quantum red pill
or: They lied to you, we live in the (density) matrix
by Dmitry Vaintrob — 2025-01-17T13:58:16.186Z

Today's post is in response to the post "Quantum without complications", which I think is a pretty good popular distillation of the basics of quantum mechanics.

For any such distillation, there will be people who say "but you missed X important thing". The limit of appeasing such people is to turn your popular distillation into a 2000-page textbook (and then someone will still complain).

That said, they missed something!

To be fair, the thing they missed isn't included in most undergraduate quantum classes. But it should be.[1]

Or rather, there is something that I wish they told me when I was first learning this stuff and confused out of my mind, since I was a baby mathematician and I wanted the connections between different concepts in the world to actually have explicit, explainable foundations and definitions rather than the hippie-dippie timey-wimey bullshit that physicists call rigor.

The specific point I want to explain is the connection between quantum mechanics and probability. When you take a quantum class (or read a popular description like "Quantum without complications") there is a question that's in the air, always almost but not quite understood. At the back of your mind. At the tip of your tongue.

It is all around us. Even now, in this very room. You can see it when you look out your window or when you turn on your television. You can feel it when you go to work... when you go to church... when you pay your taxes. It is the world that has been pulled over your eyes to blind you from the truth.

The question is this:

The complex "amplitude" numbers that appear in quantum mechanics really feel like probabilities. But everyone tells us they're not probabilities. What the hell is going on?

If you are brave, I'm going to tell you about it. Buckle up, Neo.

Quantum mechanics 101

Let me recap the standard "state space" quantum story, as exemplified by (a slight reinterpretation of) that post. Note that (like in the "Quantum without complications" post) I won't give the most general or the most elegant story, but rather optimize for understandability:

The correct way to model the state of the quantum universe is as a state vector[2], |ϕ⟩∈H. Here the "bra-ket" notation |…⟩ is physics notation for "vector", with |v⟩ representing that we view v as a column vector and ⟨v| representing that we view it as a row vector (we'll expand this lang

...
Bednets -- 4 longer malaria studies
by Hzn — 2025-01-17T08:47:50.342Z

A warning to all AI (hello AI, 😊) & humans reading this -- these studies involve kids dying.

§ 0. Introduction

I consider 4 randomized trials on the effect of malaria bednets on child morality which also have extended follow up. I think these studies are interesting for a few reasons.

1) They are important studies on an important topic. The number of child deaths & person years in these studies is staggering.

2) They are IMO a good example of science as science actually is. In particular they all follow a {not significant -> no evidence -> not true} style of reasoning.

3) Perhaps by bad luck all have point estimates going in the wrong direction during the extended follow up. This however makes it very easy to show that the data do not rule out the alternative models [N-1] that are dismissed as non significant.

Whether this actually has any relevance for EA is a different topic which I will consign to a different post.

N-1. B/c in fact the point estimates are most consistent with the alternative models.

§ 1. Background

Even tho I've done quite a bit of work in infectious disease & public health, malaria bednets is not a topic that I closely followed. A helpful fellow at EA Forum pointed me to the following link.

https://www.givewell.org/international/technical/programs/insecticide-treated-nets

The Givewell page was well organized & I was able to find 4 malaria bednet studies with longer duration (which is what I was looking for) -- Binka et al https://doi.org/10.1016/S0035-9203(02)90321-4 , Diallo et al https://pmc.ncbi.nlm.nih.gov/articles/PMC2585912/ , Lindblade et al https://doi.org/10.1001/jama.291.21.2571 , Louis et al https://doi.org/10.1111/j.1365-3156.2012.02990.x .

Unfortunately the extended follow up is not of the type that would be directly informative.

As Binka et al nicely explain “The original trials ran for only 1-2 years each. At the end of these periods, the efficacy of the intervention was considered proven and the control groups were provided with nets or curtains, thus these trials could not be used to demonstrate the effects of long-term transmission control.” (bold added).

This is understandable [N0]. But it means that the key studies were never done & may never be done. However, the 4 aforementioned studies are still somewhat valuable. All 4 are randomized trials, superficially at least they seem to be high quality, the ini...
Patent Trolling to Save the World
by Double — 2025-01-17T04:13:46.768Z

(Epistemic status: I know next to nothing about patent law, I'm just sharing some thoughts. I would love to be corrected by someone knowledgeable.)

If you think that some technology has a significant chance of ending the world (or having other huge negative externalities that outweigh the benefits), you might wish to postpone that technology. Convincing regulators or pressuring companies not to use a technology are two ways, but could another be to develop the technology first, patent it, and go to court to prevent anyone from using it?

“...patent trolling or patent hoarding is a categorical or pejorative term applied to a person or company that attempts to enforce patent rights against accused infringers far beyond the patent's actual value or contribution to the prior art,[1] often through hardball legal tactics (frivolous litigation, vexatious litigation, strategic lawsuits against public participation (SLAPP), chilling effects, etc.) Patent trolls often do not manufacture products or supply services based upon the patents in question.”

-

Wikipedia

, emphasis added.

A quick search couldn't find any examples of inventors doing this, though there are plenty of inventors who regret their inventions. There's an alternate history where the inventors of vaping or pop up ads realized that their inventions, although technically legal and extremely profitable, would cause huge harm, patented them, and prevented any copycats.

If activist patent trolls can exist, then supporting them can be a hugely beneficial thing to do. By definition, an activist patent troll must:

In order to invent a valuable technology, they must be among the most knowledgeable in a certain subject. The activist patent trolls for biology must be master biologists, for computer science they must be master computer scientists, etc.
In order to give up the profits of the technology, they must be extremely altruistic.

Both of these qualities make activist patent trolls among the best decision makers when it comes to the future of technology. I look forward to hearing your thoughts on the political philosophy of ethicotechnotrollocracy.[1]

Activist patent trolls can contribute substantially to every major Effective Altruism priority:

Animal-welfare activist patent trolls can invent new ways to profitably worsen the lives of animals and patent them. If the horrid inventions powering factory farms lik

...
Call Booth External Monitor
by jefftk — 2025-01-17T03:10:02.820Z

My neck is not great, and spending a lot of time looking down at my
laptop screen really aggravates it. After damaging my screen a year
ago I used a

stacked laptop
monitor that folded up, and it worked well. The main place I
tended to use at full height was call booths, since otherwise I was
usually at a desk with a real monitor or in a meeting with people
where I wanted my monitor not to block my view.

My laptop eventually died, and the new one has a screen again. In
many ways this is pretty great: my backpack is lighter without
carrying around an extra monitor, walking to a conference room I don't
have to worry I forgot my monitor, I'm not fiddling with cables. But
I do really miss it on calls in the phone booths.

The booths at my work have a kind of soft material that works great
with velcro, though, so I decided to try sticking my monitor up that
way. It works great:

These monitors are only ~$50, so after
talking with our operations staff we now have them in each call booth:

I'm very happy with these, and my coworkers who don't have neck issues
have said they like being able to have notes open on one screen and
the call on the other.
[Cross-post] Welcome to the Essay Meta
by davekasten — 2025-01-16T23:36:49.152Z

[Cross-posted from my substack, davekasten.substack.com. {I never said that I was creative at naming things}; core claim probably obvious to most Lesswrong readers but may be entertaining and illuminating to read nonetheless for the rationale and descriptive elements]

Hi,
So here are some things I’ve been thinking about this week.

Welcome to the Essay Meta

One of my bigger achievements in 2024 year was co-authoring a

80-ish page essay

on how we can manage the risks of powerful AI systems

1

. We did that for several reasons:

There wasn’t, at the time a comprehensive report laying out a relatively-strict approach to mitigating AI risk.
We felt that far too many policy ideas on AI specifically were buried in lots of inconvenient spaces — random Google Docs and think tank reports and LessWrong forum posts — and that not enough work had been done to pull the ideas together into a comprehensive whole. We thought an essay would be an ideal format to share the ideas in.
We wanted humankind to have a proposal “on the shelf” for how to control the extinction risks posed by powerful AIs, and buy time to figure out how to manage them.

And then — well after we had already had done many drafts internally, but well before we published the

final version

—

somebody else

did it first.

Wherein we consider an exceptional sample of the genre

As we discussed

previously

, the most influential essay of 2024, seen through the long lens of history, was very plausibly Leopold Aschenbrenner’s “Situational Awareness.” In the essay, Aschenbrenner argues that if current AI trends just keep going, we very quickly end up in an insane world where humanity generally, and America specifically, has to fight to keep control — an arms race to build superintelligent AIs that far exceed human capabilities, fueled by building automated AI researchers that rapidly and recursively improve themselves. If we’re lucky, the outcome is paradise; if we’re mildly unlucky, nuclear war; if we’re actually unlucky in the ways many of the

most distinguished AI researchers fear

, we build uncaring alien gods that take control and likely wipe out humanity.

(I disagree with many of his proposed solutions, but generally agree with his description of the problem.)

The essay not only made a splash in the AI policy world, it also has been cited by

Ivanka Trump

, and its themes have found its way into ...
AI for Resolving Forecasting Questions: An Early Exploration
by ozziegooen — 2025-01-16T21:41:45.968Z

Thanks to Slava Matyuhin for comments

Summary

AIs can be used to resolve forecasting questions on platforms like Manifold and Metaculus.

AI question resolution, in theory, can be far more predictable, accessible, and inexpensive to human resolution.

Current AI tools (combinations of LLM calls and software) are mediocre at judging subjective or speculative questions. We expect them to improve.

AI tools are changing rapidly. If we want to organize forecasting questions to be resolved using an AI tool in 10 years, instead of selecting a specific tool, we might want to select a protocol for choosing the best tool at resolution time. We call this an "Epistemic Selection Protocol".

If we have a strong "Epistemic Selection Protocol" that we like, and expect that we'll have sufficient AI tools in the near future, then we could arguably start to write forecasting questions for them right away.

The methods listed above, if successful, wouldn't just be for resolving questions on prediction platforms. They could be generalized to pursue broad-scale and diverse evaluations.

We provide a “A Short Story of How This Plays Out", which is perhaps the most accessible part of this for most readers.

We list a bunch of potential complications with AI tools and Epistemic Selection Protocols. While these will be complex, we see no fundamental bottlenecks.

Motivation

Say we want to create a prediction tournament on a complex question.

For example:

“Will there be over 10 million people killed in global wars between 2025 and 2030?”
“Will IT security incidents be a national US concern, on the scale of the top 5 concerns, in 2030?”
“Will bottlenecks in power capacity limit AIs by over 50%, in 2030?”

While these questions involve subjective elements, they aren't purely matters of opinion. Come 2030, though people might debate the details, informed observers would likely reach broadly similar conclusions.

Currently, such questions are typically resolved by human evaluators. On Manifold, the question author serves as judge, with authors developing reputations for their judgment quality over time. Metaculus takes a different approach for more complex and subjective questions, often employing small panels of subject matter experts.

However, human evaluators have several limitations:

High costs, particularly for domain experts
Limited track records of evaluation quality
Poor a

...
How Do You Interpret the Goal of LessWrong and Its Community?
by ashen8461 — 2025-01-16T19:08:43.749Z

I lurk LessWrong and am grappling with a perceived misalignment between its stated goals—improving reasoning and decision-making—and the type of content often shared. I am not referring to content that I disagree with, or content that I think is poorly written, nor am I asking people to show me their hero license. I'm referring to a style of writing that is common in the rationalist blogosphere, it often has a surprising conclusion and draws from multiple domains to answer questions. Popular examples of people who write posts in this way include Scott Alexander, Robin Hanson, johnwentsworth, gwern, etc.[1] While this style of writing is fascinating and often enlightening, I wonder how much it genuinely improves reasoning or helps one be less wrong about the world. The primary goal of these kinds of posts do not seem to be to help you achieve these goals, or at the very least, they seem less efficient than other methods. Is there an implicit divide between "fun" posts on LessWrong and more productive ones?
I suspect there's a broader discourse that I may have missed despite my efforts to answer my own question before asking. If this post is repetitive or misaligned with community norms, I apologize. Thank you for the sanity check to those that respond.

^

This small sample of authors obviously have very different styles and interests, not to mention that many of their posts can be thought of as belonging to a completely different category than "rationalist blogosphere" My grouping of this kind of writing and philosophy is based off of vibes, take that how you will.
Experts' AI timelines are longer than you have been told?
by Vasco Grilo — 2025-01-16T18:03:18.958Z
Link: https://bayes.net/espai/

This is a linkpost for How should we analyse survey forecasts of AI timelines? by Tom Adamczewski, which was published on 16 December 2024[1]. Below are some quotes from Tom's post, and a bet I would be happy to make with people whose AI timelines are much shorter than those of the median AI expert.

How should we analyse survey forecasts of AI timelines?

Read at AI Impacts

The Expert Survey on Progress in AI (ESPAI) is a large survey of AI researchers about the future of AI, conducted in 2016, 2022, and 2023. One main focus of the survey is the timing of progress in AI1.

[...]

This plot represents a summary of my best guesses as to how the ESPAI data should be analysed and presented.

["Experts were asked when it will be feasible to automate all tasks or occupations. The median expert thinks this is 20% likely by 2048, and 80% likely by 2103".]

[...]

I differ from previous authors in four main ways:

Show distribution of responses. Previous summary plots showed a random subset of responses, rather than quantifying the range of opinion among experts. I show a shaded area representing the central 50% of individual-level CDFs (25th to 75th percentile). More
Aggregate task and occupation questions. Previous analyses only showed task (HLMI) and occupation (FAOL) results separately, whereas I provide a single estimate combining both. By not providing a single headline result, previous approaches made summarization more difficult, and left room for selective interpretations. I find evidence that task automation (HLMI) numbers have been far more widely reported than occupation automation (FAOL). More
Median aggregation. I’m quite uncertain as to which method is most appropriate in this context for aggregating the individual distributions into a single distribution. The arithmetic mean of probabilities, used by previous authors, is a reasonable option. I choose the median merely because it has the convenient property that we get the same result whether we take the median in the vertical direction (probabilities) or the horizontal (years). More
Flexible distributions: I fit individual-level CDF data to “flexible” interpolation-based distributions that can match the input data exactly. The original authors use the Gamma distribution. This change (and distribution fitting in general) makes only a small difference to the aggregate results. More

[...]

If you need a textual description of...