trentmkelly/LessWrong-43k huggingface dataset:
The Worst Form Of Government (Except For Everything Else We've Tried)
by johnswentworth — 2024-03-17T18:11:38.374Z

Churchill

famously called democracy

“the worst form of Government except for all those other forms that have been tried from time to time” - referring presumably to the relative success of his native Britain, the US, and more generally Western Europe and today most of the first world.

I claim that Churchill was importantly wrong. Not (necessarily) wrong about the relative success of Britain/US/etc, but about those countries’ governments being well-described as simple democracy. Rather, I claim, the formula which has worked well in e.g. Britain and the US diverges from pure democracy in a crucial load-bearing way; that formula works better than pure democracy both in theory and in practice, and when thinking about good governance structures we should emulate the full formula rather than pure democracy.

Specifically, the actual governance formula which is “worst except for everything else we’ve tried” is:

Give a de-facto veto to each major faction
Within each major faction, do pure democracy.

A Stylized Tale of Democracy

Let’s start with the obvious failure mode of pure democracy: suppose a country consists of 51% group A, 49% group B, and both groups hate each other and have centuries-long blood feuds. Some first world country decides to invade, topple the local dictator, and hold democratic elections for a new government. Group A extremist candidate wins with a 51% majority, promising to enact divine vengeance upon the B’s for their centuries of evil deeds. Group B promptly rebels, and the country descends into civil war.

This is obviously a stylized, oversimplified picture, but… well, according to wikipedia the three largest ethnic groups in Iraq are the Shiites (14 million), Sunni arabs (9 million), and Sunni Kurds (4.7 million), which would make the Shiites just over 50% (excluding the various smaller groups)[1]. In the 2005 elections, the Shiites claimed 48% of the seats - not quite a majority but close enough to dominate political decisions in practice. Before long, the government was led by

a highly sectarian Shiite

, who generally tried to limit the power of Sunnis and Kurds. In response, around 2013/2014, outright Sunni rebellion coalesced around ISIL and Iraq plunged into civil war.

Now, I’m not about to claim that this was democracy at its purest - the US presumably put its thumb on the scales, the elections were presumably less than ide...
Applying simulacrum levels to hobbies, interests and goals
by DMMF — 2024-03-17T16:18:54.522Z
Link: https://danfrank.ca/most-singers-become-singers-because-they-want-to-be-singers-not-because-they-want-to-sing/

One of the things I've been very confused by for most of my life is why it seems like few people truly care about the things they say they like. That is, they don't spend their spare time thinking about it; they don't read Wikipedia about it, let alone subreddits/blogs or actual books on the topic; they don't practice the thing, or they don't actively incorporate that thing into their life.

I recently came across an article by Jim Leff that crystallized a lot of thoughts in my mind:

"Everybody dreams of being on stage and singing The Note, or of being elected to high office and giving The Speech. We chase that image, and the specific details hardly matter. You know how Donald Trump loves the trappings of office but has no interest in the actual work of a president, doesn't think about issues, and skates through by winging it? …While I can't distill this point any further, I can cite a favorite pithy observation for the umpteenth time: Most singers become singers because they want to be singers, not because they want to sing. Politicians don't give The Speech out of a desire to inspire and lead. It's the antithesis: they become politicians because they want to be the guy giving The Speech."

I've recently been thinking a lot about Baudrillard's concept of simulacra levels, as I am trying to understand the political discourse around me. Applied here, simulacra levels refer to the idea of the different levels of why one may participate in a hobby/activity:

Level 1 is about authentically enjoying this thing. I.e., liking the Grateful Dead because you love the heady jams.
Level 2 is to do the thing because it aligns with the type of person you want to identify with, and will help you connect with like-minded people. I.e., liking the Grateful Dead because you are a hippie.
Level 3 is when you do the thing simply because you think it will provide a social benefit for doing so. I.e., liking the Grateful Dead because in your circles, it's cool to like the Grateful Dead.
Level 4 is when, for social reasons, you do something connected to the thing itself, but the thing itself is now completely detached from the original context. I.e., wearing a Grateful Dead shirt you bought at Urban Outfitters because it seems cool, even though you will never listen to the Grateful Dead.

While growing up, I was exposed to a lot of skateboarders. I remember at one point being confused as to why...
What is the best argument that LLMs are shoggoths?
by JoshuaFox — 2024-03-17T11:36:23.636Z

Where can I find a post or article arguing that the internal cognitive model of contemporary LLMs is quite alien, strange, non-human, even though they are trained on human text and produce human-like answers, which are rendered "friendly" by RLHF?
To be clear, I am not asking about the following, which I am familiar with:

The original of the shoggoth meme and its relation to H.P. Lovecraft's shoggoth
The notion that the space of possible minds is very large, with humanity only a small part
Eliezer Yudkowsky's description of evolution as Azathoth, the blind idiot god, as a way of showing that "intelligences" can be quite incomprehensible
The difference in environments between the training and the runtime phase of an LLM
The fact that machine-learning systems like LLMs are not really neuromorphic; they are structured differently from human brains (though that fact does not exclude the possibility of similarly on a logical level)

Rather, I am looking for a discussion of evidence that the LLMs internal "true" motivation or reasoning system is very different from human, despite the human output, and that in outlying environmental conditions, very different from the training environment, it will behave very differently. A good argument might analyze bits of weird inhuman behavior to try to infer the internal model.

(All I found on the shoggoth idea on LessWrong is this article contrasts the idea of the shoggoth with the idea that there is no coherent model, but does not explain why we might think that there is an alien cognitive model. This one likewise mentions the idea but does not argue for its correctness.)

[Edit: Another user corrected my spelling: shoggoth, not shuggoth.]
Invitation to the Princeton AI Alignment and Safety Seminar
by Sadhika Malladi — 2024-03-17T01:10:53.885Z

We're thrilled to invite you to attend the virtual Princeton AI Alignment and Safety Seminar (PASS)!

Ensuring safe behavior by aligning increasingly capable models is crucial, and PASS offers a virtual, collaborative platform for researchers from various backgrounds and institutions to explore these vital issues. Bi-weekly talks will be live-streamed, with opportunities for audience engagement and recordings shared via our PLI-Info YouTube channel. Our inaugural lineup features esteemed experts including Paul Christiano, Aleksander Madry, Dan Hendrycks, Irene Soleiman, John Schulman, and Jacob Steinhardt. Stay informed and receive seminar reminders by joining our mailing list: https://tinyurl.com/pass-mailing

Our first talk will be on Tuesday, March 19th at 2pm Eastern Time. The livestream will be here, and a recording will be posted to the channel afterwards. Please submit your questions for our speakers! Paul Christiano from the Alignment Research Center will be talking about Catastrophic Misalignment of Large Language Models. The abstract is below.

I’ll discuss two possible paths by which AI systems could be so misaligned that they attempt to deceive and disempower their human operators. I’ll review the current state of evidence about these risks, what we might hope to learn over the next few years, and how we could become confident that the risk is adequately managed.
Anxiety vs. Depression
by Sable — 2024-03-17T00:15:08.255Z
Link: https://affablyevil.substack.com/p/anxiety-vs-depression

I have anxiety and depression.

The kind that doesn’t go away, and you take pills to manage.

This is not a secret.

What’s more interesting is that I just switched medications from one that successfully managed the depression but not the anxiety to one that successfully manages the anxiety but not the depression, giving me a brief window to see my two comorbid conditions separated from each other, for the first time since ever.

What follows is a (brief) digression on what they’re like from the inside.

Depression

I’m still me when I’m depressed.

Just a version of me that’s sapped of all initiative, energy, and tolerance for human contact.

There are plenty of metaphors for depression - a grey fog being one of the most popular - but I often think of it in the context of inertia.

Inertia is matter’s tendency to keep doing what it’s doing, until some outside force comes and overturns the mattress. An object at rest will stay at rest until someone tells it to get out of bed, and an object in motion will stay in motion until it’s told to calm the f*ck down.

Normally, inertia is pretty easy to overcome, for one’s own self. Want something done? Just get up and do it.

When I’m depressed, though, inertia is this huge, comfortable pillow that resists all attempts to move it. Want to do something? Does it involve getting out of bed? If so, no thank you, that sounds hard. Hungry? Meh, I can eat later. Have to go to work? That sounds exhausting, and there’s this big pillow that just won’t move between me and ever leaving this bed, and maybe I’ll just call in mentally ill today.

The funny thing is that this inertia appears at every level of movement and cognition.

On a normal day, ‘get out of bed’ is a single action. I think it, then I do it.

On a depressed day, ‘get out of bed’ is a long, complicated string of actions, each of which has its own inertia and must be consciously micromanaged. I have to life this arm, maneuver this hand, flex that finger, push with shoulder, bring knee up, twist body, and so on. Each action is distinct, and each has its own inertia to be fought.

On a really bad day, each of those actions must be micromanaged, until I’m literally flexing individual muscles one at a time in sequence to move, as if my body were an anatomically correct puppet my brain had to steer one nerve-impulse instruction at a time.

Of course, this applies to thoughts, too - deciding to do any...
Celiefs
by TheLemmaLlama — 2024-03-16T23:56:07.193Z

We have "aliefs" and "beliefs" - let me introduce "celiefs": something that we worry *has a high chance of being true*, but aren't quite convinced of.

Often this is something that society/experts/someone you admire says is true, but you don't see the reasoning behind.

We may look for evidence that might convince us of the celief, or behave as if we already believe the celief; this is not exactly performative, but more like an act of "hedging" -- so that if the celief turns out to be true, we've avoided causing harm. We would do this regardless of whether people see it, but it can still feel "disingenuous" since we haven't quite internalized the celief that we're acting on.

____________________________

This seems like it might be the difference between OCD themes and attenuated* delusions: You alieve your attenuated delusions while you celieve your OCD theme

* attenuated delusions meaning delusions you're capable of questioning. They become full-blown delusions sometimes. But they seem categorically similar, so I feel like the correct line to draw is [alief vs celief] rather than ["truly believe it" vs "know rationally that it's false"]

_____________________________

Some celiefs you might hold include:

vaccines work/covid is real
global warming is real
gender/race is a social construct
racism/sexism/etc exists
victims are telling the truth
homosexuality is bad/a sin
you will go to hell for doing bad things
i am the real abuser
i'm faking my mental illness for attention
i'm virtue signaling; only pretending to care/understand/be sorry/etc
my intrusive thoughts are who i am deep down
i was abused because i wanted it

Celiefs can be good or bad; sometimes it's good to hedge your bets on something you don't know much about and trust the people who have lived/studied the thing, but celiefs are also how people gaslight you.

I would classify anything that you maladaptively act upon but want to work through in therapy as a celief rather than a belief (if you really believe it, you wouldn't want to work on trying to not believe it, because from your perspective that would be deluding yourself)
My PhD thesis: Algorithmic Bayesian Epistemology
by Eric Neyman — 2024-03-16T22:56:59.283Z
Link: https://arxiv.org/abs/2403.07949

In January, I defended my PhD thesis, which I called Algorithmic Bayesian Epistemology. From the preface:

For me as for most students, college was a time of exploration. I took many classes, read many academic and non-academic works, and tried my hand at a few research projects. Early in graduate school, I noticed a strong commonality among the questions that I had found particularly fascinating: most of them involved reasoning about knowledge, information, or uncertainty under constraints. I decided that this cluster of problems would be my primary academic focus. I settled on calling the cluster algorithmic Bayesian epistemology: all of the questions I was thinking about involved applying the "algorithmic lens" of theoretical computer science to problems of Bayesian epistemology.

Although my interest in mathematical reasoning about uncertainty dates back to before I had heard of the rationalist community, the community has no doubt influenced and strengthened this interest.

The most striking example of this influence is Scott Aaronson's blog post Common Knowledge and Aumann's Agreement Theorem, which I ran into during my freshman year of college.[1] The post made things click together for me in a way that made me more intellectually honest and humble, and generally a better person. I also found the post incredibly intellectually interesting -- and indeed, Chapter 8 of my thesis is a follow-up to Scott Aaronson's academic paper on Aumann's agreement theorem.

My interest in forecast elicitation and aggregation, while pre-existing, was no doubt influenced by the EA/rationalist-adjacent forecasting community.

And Chapter 9 of the thesis (work I did at the Alignment Research Center) is no doubt causally downstream of the rationalist community.

Which is all to say: thank you! Y'all have had a substantial positive impact on my intellectual journey.

Chapter descriptions

The thesis contains two background chapters followed by seven technical chapters (Chapters 3-9).

In Chapter 1 (Introduction), I try to convey what exactly I mean by "algorithmic Bayesian epistemology" and why I'm excited about it.

In Chapter 2 (Preliminaries), I give some technical background that's necessary for understanding the subsequent technical chapters. It's intended to be accessible to readers with a general college-level math background. While the nominal purpose of Chapter 2 is to intro...
How people stopped dying from diarrhea so much (& other life-saving decisions)
by Writer — 2024-03-16T16:00:47.830Z
Link: https://youtu.be/ll9myMeFU3g

Rational Animations made this video collaborating with 80,000 Hours. The script has been written by Benjamin Hilton as an adaptation of part of the 80,000 Hours career guide, by Benjamin Todd. I have included the full script below.

It’s easy to feel like one person can’t make a difference.

The problems the world faces seem so vast, and we seem so small. Sometimes even the best of intentions aren't enough to make the world budge.

Now, it’s true that many common ways people try to do good have less impact than you might think at first.

But some ways of doing good have allowed certain people to achieve an extraordinary impact. How is this possible? And what does it mean for how you can make a difference?

We’ll start by looking at doctors — and end up at nuclear war.

Many people train to become doctors because they want to save lives! And, of course, their work is very important. But how many lives does a doctor really save over the course of their career? You might assume it's in the hundreds or thousands. But the surprising truth is that, according to an analysis carried by Dr Greg Lewis — a former medical doctor — the number is far lower than you'd expect.

Since the 19th century, life expectancy has skyrocketed. But that’s not just because of medicine. There are loads of contributing factors, like nutrition, improved sanitation, and increased wealth. Estimating how many years of life medicine alone saves is really difficult.

Despite this difficulty, one attempt — from researchers at Harvard and King’s College London — found that medical care in developed countries increases the life expectancy of each person in these countries by around 5 years.

Most developed countries have around 3 doctors per 1,000 people. So, if this estimate is right, each doctor saves around 1,666 years of life, over the course of their career. Using the World Bank’s standard conversion rate of 30 extra years of healthy life to one “life saved,” that’s around about 50 lives saved per doctor!

But that’s actually a substantial overestimate.

Doctors are only one part of the medical system, which also relies on nurses and hospital staff, as well as overhead and equipment. And more importantly, there are already a lot of doctors in the developed world. So if you don’t become a doctor, someone else will be available to perform the most critical procedu...
Transformative trustbuilding via advancements in decentralized lie detection
by trevor — 2024-03-16T05:56:21.926Z
Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3680134/

Although the emergence of functional lie detection would be an obvious total paradigm shift for the entire court system, the author didn’t seem to realize that this is also an obvious total paradigm shift for much bigger things, e.g. hiring, high-trust friend groups, an immune system for deceptively aligned humans, discouraging harmful behavior, nihilistic profiteering, and/or excessively extreme self interest.

Although centralization of power is a classic concern, broader open decentralized access could easily facilitate a new era of high-trust social dynamics within and between smaller groups.

So bear in mind, whenever the author says this is about courts, you’re allowed to think about whatever other use cases might come to mind, not just courts. This is about trust, cooperation, taken to an extreme level that we have never seen before on Earth, and plausibly can’t imagine until it happens. What kind of questions could you ask someone (or have them ask you) if you wanted to honestly build trust and collaborate? What problems in the world would vanish, perhaps preemptively? Probably a large majority.

We might even already be deep into a technological overhang, where transformation will materialize after a few technical breakthroughs, or perhaps just any effort at all towards applied research by serious, thoughtful, and pragmatic individuals. The current reputation of lie detectors not working basically revolves around the fact that they were first invented ~a century ago (hence the name "polygraph"; it was the coolest thing you could possibly do at the time with multiple graphs). So it's not particularly surprising that our civilization remained mediocre, in the context of such incredible capabilities existing but being so amazing that they were pursued way too early.

This paper (Using Brain Imaging for Lie Detection: Where Science, Law and Research Policy Combine) was published in 2012 and the world has changed a lot since then (sadly, with no room-temperature superconductors, which would facilitate large-scale deployment of fMRI hats). Since this is a snapshot of the state of brain research in a specific point in time (albeit a truly, truly excellent snapshot), I’ve sprinkled reminders throughout that this is from 2012.

Abstract

Progress in the use of functional magnetic resonance imaging (fMRI) of the brain to evaluate deception and differenti

...
Strong-Misalignment: Does Yudkowsky (or Christiano, or TurnTrout, or Wolfram, or…etc.) Have an Elevator Speech I’m Missing? 
by Benjamin Bourlier — 2024-03-15T23:17:37.531Z

[Intro Note: (1) this "post" is, technically, a "question", for which there's a separate category on LW. I debated posting it as a "question", but it also involves considerable argumentation for my own views. Ideally there'd be some in-between "question/post" category, but I opted for "post"? I understand if a reader thinks this should have been categorized as a "question", though, and would appreciate criteria considerations for how to distinguish these categories on the site in the comments--maybe "dialogue" would be better? (2) My goal in posting on LW is to become less wrong, not to persuade, get upvotes, etc. My recent first post was significantly downvoted, as I expected. I naively expected some debate, though--in particular, I expected someone to say, like, "Metzinger and Benatar have already argued this". Anyway, I've revisited site norm guidelines to check my cynicism. I'm trying, sincerely, to write "good content". I'm sure I can do better. I don't mind being downvoted/buried, and I don't mind rude comments. I would, though, genuinely appreciate rational/logical explanations as to why, if I am "not good", or am producing "low quality content", this is so. Please, don't just passively bury my arguments/questions without offering any explanation as to why. That's all I ask. I maintain several controversial philosophical views. I'm not a contrarian or provocateur, but simply a heretic. I can list my controversial views: I support anti-natalism and am against intelligence-augmentation (see my first post); I support free, voluntary access to euthanasia; I am pro-impulsive/irrational-suicide-prevention, but I believe this can only be achieved for suicidally depressed people via existential-pessimism/depressive-realism (that is, I maintain a theory of suicide prevention not endorsed by CBT-dominant psychology, according to which "depression" is deemed inherently delusional--I don't think it is, not necessarily); I think genocide and abuse in general are causally explainable in terms of Terror Management Theory (TMT); I think along the lines of Ellul's technological pessimism (my future predictions are all quite negative); I think along the lines of Kahneman's epistemological pessimism (my view of "intelligence" and "knowledge" is pessimistic, and my predictions regarding "education" are all quite negative); and, perhaps most controversially, I am sympathe...
Introducing METR's Autonomy Evaluation Resources
by Megan Kinniment — 2024-03-15T23:16:59.696Z
Link: https://metr.github.io/autonomy-evals-guide/index.html

This is METR’s collection of resources for evaluating potentially dangerous autonomous capabilities of frontier models. The resources include a task suite, some software tooling, and guidelines on how to ensure an accurate measurement of model capability. Building on those, we’ve written an example evaluation protocol. While intended as a “beta” and early working draft, the protocol represents our current best guess as to how AI developers and evaluators should evaluate models for dangerous autonomous capabilities.

We hope to iteratively improve this content, with explicit versioning; this is v0.1.