trentmkelly/LessWrong-43k huggingface dataset:
The Humanitarian Economy
by  — 2024-11-12T18:25:09.557Z

In the past ten years, I have been developing ideas to resolve key issues that I have encountered in my own life, and in the lives of the people around me. In probing these issues for their root causes, I have identified the threat and reality of economic deprivation as the primary motivator of everyday suffering. Just a few of the issues that this current work resolves:

1. Non-voluntary family participation

2. Non-voluntary work

3. Economic entrapment of intimate partner violence sufferers

4. Exploitative working environment and compensation dynamics

5. Food deserts

6. Under and over development

7. Multinational capital concentration, and subsequent self-determination violations

8. Product quality and decency issues

9. Environmental damage and non-systemic thinking

No one system so far alleviates these issues. This one will.

(i)

Beginning in the early 1990s, certain national banks started to experiment with money creation as a means of achieving certain economic goals. The national bank of Japan came up with the quirky and elegant term “quantitative easing” for this process, and various other central banks picked up the process for their own goals.

QE really picked up speed after the 2008 housing crisis, when the US Fed utilized QE to bail out the financial system. Conventional thinking up until that point, at least in the US, was that creating money for this purpose would be wildly inflationary and so out of bounds for any prudent central bank.

The results tell a different story. If anything, QE was deflationary. Subsequent QEs have borne this point out, with the most recent academic discourse about the actual effects of QE on the broader economy being undecided.

The current financial system elite as embodied by the US Fed and their discourse, talks with two mouths. On the one hand, when it comes to real human needs like social programs and direct assistance, they advocate for rigid “financial discipline”, talking about debt and taxes and interest rates, and on the other, when their colleagues in banking are in distress, printing money to bail them out.

We now live in an era where central banks have tested the tenets of MMT[1] in microcosm, to the benefit of their closest allies, and the capacity to utilize monetary policy for humanitarian ends now demonstrably exists in the hands ...
Current Attitudes Toward AI Provide Little Data Relevant to Attitudes Toward AGI
by Seth Herd — 2024-11-12T18:23:53.533Z

Epistemic status: Sudden public attitude shift seems quite possible, but I haven't seen it much in discussion, so I thought I'd float the idea again. This is somewhat dashed off since the goal is just to toss out a few possibilities and questions.

In Current AIs Provide Nearly No Data Relevant to AGI Alignment, Thane Ruthenis argues that current AI is almost irrelevant to the project of aligning AGIs. Current AI is simply not what we're talking about when we worry about alignment, he says. And I halfway agree.[1]

By a similar token, we haven't yet seen the thing we're worried about, so attitudes now provide limited data about attitudes toward the real deal. It looks to me like people are rarely really thinking of superhuman intelligence with human-like goals and agency, and when they are, they usually find it highly concerning. We've tried to get people to think about powerful, agentic AGI, but I think that's largely failed, at least among people familiar with AI and ML.

People are typically bad at imagining hypothetical scenarios, and we are notoriously shortsighted. People who refuse to worry about AGI existential risks appear to be some combination of not really imagining it, and assuming it won't happen soon. Seeing dramatic evidence of actual AGI, with agency, competence, and strange intelligence, might quickly change public beliefs.

Leopold Aschenbrenner noted in Nobody’s on the ball on AGI alignment that the public's attitude toward COVID turned on a dime, so a similar attitude shift is possible on AGI and alignment as well. This sudden change happened in response to evidence, but was made more rapid by nonlinear dynamics in the public discourse: a few people got very concerned and told others rather forcefully that they should also be very concerned, citing evidence; this spread rapidly. The same could happen for AGI.

As Connor Leahy put it (approximately, maybe):[2] when we talk to AI and ML people about AGI x-risk, they scoff. When we tell regular people that we're building machines smarter than us, they often say something like "You fucking what?!" I think this happens because the AI/ML people think of existing and previous AI systems, while the public thinks of AIs from fiction - which actually have the properties of agency and goal-directedness we're worried about. This class of people won't change their beliefs but rather their urgency, i...
Basics of Handling Disagreements with People
by Camille Berger  — 2024-11-12T17:55:08.143Z

Epistemic Status: This is a collection of useful heuristics I’ve gathered from a wide range of

books and workshops

, all rather evidence-based (robustness varies). These techniques are designed to supplement basics of rationalist discourse, helping facilitate interactions—mostly with those unfamiliar with rationalist thought, especially on entry-level arguments. They may also be useful in conversations between rationalists on occasion. This is also a minimal viable product for an upcoming sequence that will dive into the analysis of well-managed disagreements. Details are intentionally left out.
Tl;dr: Rephrase, ask questions, do not presume your conversation partner shares your epistemology (i.e way of coming to conclusions, in general), ask them for real-world counter-examples, share personal experiences both ways as a means to get clearer, check what kinds of blindspots their own motivation presumes, dovetail interests with brainstorming, and also, all of what I’ve just said is merely pointing to a specific state of mind. You can get to this state of mind only with some form of introspection.
Arguing is sometimes wonderful. Yet sometimes it derails, or flat-out fails. Circumstances in which arguing fails tend to involve people who are not actively displaying rationality. LessWrong has done a lot to teach how to mutually progress on such disagreement. Yet this is only a very small community -the Rest of the World, aka People, still hasn't read the Sequences.
Unproductive disagreement with people can lead to poor impression, pig-headedness, stress, anger, and sometimes worse. There has already been numerous discussions, on this forum, of ways to avoid getting there: there is already a

book review

on How Minds Change, then

I spent too much time breaking down good disagreements to teach how to do it

. But there wasn't a short document that was summarizing the key takeaways. This serves as that document.
Ethical Caveat:
This post presumes that you follow ethical advice such as:
1-Being earnestly truth-seeking
2-Getting the consent of your partner beforehand to question their beliefs
3-Not harassing people who don't want to talk
4-Choosing the right context (most of the times, 1:1 conversations)
5-Choosing the right person (not a hierarchical subordinate, expect conversations to be harder with a family member)
6-Choosing the right topic (probably...
Registrations Open for 2024 NYC Secular Solstice & Megameetup
by Joe Rogero — 2024-11-12T17:50:10.827Z

On December 14th, New York City will have a Secular Solstice. Solstice is a holiday for people comfortable with uncomfortable truths and who believe in good. Secular Solstices take place in many cities around the world, but for us New York City is the best place for it. The first Solstice started here, amid towers that reach for the sky and glitter like stars in the night. Now a tradition spanning over a decade, rationalists from across North America—and sometimes further afield—will come together to sing about humanity's distant past and the future we hope to build.

From the evening of December 13th to the morning of December 16th, NYC will also be the home of the Rationalist Megameetup. We will have sleeping space (Friday, Saturday, and Sunday nights) for those from out of town, as well as meeting spaces to congregate in. Historically the Megameetup has had calibration games, live podcasting, and the ever-popular lightning talks. There's been scheduled replications of papers, unscheduled lectures on poetry, and more interesting conversations than anyone has counted.

Solstice and Megameetup will both be at the Sheraton Brooklyn New York Hotel, 228 Duffield Street Brooklyn.

Last year's experiment was whether Megameetup could survive a transition into a conference hotel. The answer was a clear "YES", and we predictably hit capacity on that space like we have every space we've been in since 2019. This year we're back, bigger than before, and with a conference space large enough that Megameetup can host Solstice.

Solstice and Megameetup

registrations

are combined, though you can register for only one if you like. Use the

payment page

to pick which combination of Solstice and Megameetup events you prefer. We have arranged a hotel block of rooms at a discount, the link for which will be active soon. If we've run out of rooms in the block, you might try booking with the hotel directly. If you do, let them know you're with the New York City Rationalist Megameetup.

We hope to see you there!

-Skyler & The 2024 Megameetup Team
2025 Q1 Pivotal Research Fellowship (Technical & Policy)
by Tobias H — 2024-11-12T10:56:24.858Z

We’re excited to announce that applications are now open for our

2025 Q1 Pivotal Research Fellowship

, a 9-week program designed to enable promising researchers to produce impactful research and accelerate their careers in technical AI safety, AI governance, and biosecurity.

About the Fellowship

The Pivotal Research Fellowship is hosted in London at the

London Initiative for Safe AI

(LISA). It offers a unique opportunity for early-career researchers to collaborate with experienced mentors, engage in workshops and seminars, and build a strong network within the AI safety research community in London and beyond.

Dates: February 3rd to April 4th, 2025
Application Deadline: November 21st, 2024

Apply here

.

Fellows receive:

Direct mentorship from established researchers
Access to LISA, working alongside leading researchers in AI safety
£5000 stipend, plus meals, travel support, accommodation, and compute costs

This marks our 5th research fellowship, building on a strong track record of supporting researchers in tackling important questions about the safety and governance of emerging technology.

Looking back on our 2024 Research Fellowship

(We plan on releasing a more in-depth retrospective in the upcoming weeks.)

In 2024 we hosted 15 fellows:

7 in AI governance
6 in technical AI safety
2 in biosecurity

The fellowship received high ratings with 9.17/10 for overall value and 9.33/10 for recommendation likelihood (Net Promoter Score: 88).

Here’s what 2024 fellows say about their experience with the Pivotal Research Fellowship:

“The Fellowship has been transformative for my career and personal development. Most importantly, I had the incredible opportunity to be mentored by a leading expert and go from idea development to paper submission.”
“The fellowship allowed me to work with top AI safety researchers – a great privilege early in my career! People were surprised at what can be accomplished in two months, including me.”
“Pivotal Research Fellowship opened the door to AI governance, enabling me to conduct impactful research in this field and connecting me to the broader AI governance community and new opportunities.”
“Pivotal shifted my career: I'm now working on a startup for white box model access and will join GovAI as a Winter Fellow. Being at LISA connects you with top AI safety researchers and places you on the radar of leading organizations.”
“Pivotal’s appr

...
Theories With Mentalistic Atoms Are As Validly Called Theories As Theories With Only Non-Mentalistic Atoms
by Lorec — 2024-11-12T06:45:26.039Z

[ This is supposed to be a didactic post. I'm not under the impression that I'm saying anything genuinely new. Thanks to Stephen Wolfram. ]

I'm about an hour in to the Yudkowsky-Wolfram discussion [AI-generated transcript from which I'm quoting]. Wolfram thinks we should not fear AI doom very much in particular. I think he is wrong. It seems to me like the cause of Wolfram's hesitancy to buy into the AI doom idea is a premise that theories with only non-mentalistic atoms are the only valid or allowed theories of how the world works. This is a false premise, but I want to get into what I mean by a premise that theories containing mentalistic atoms are not allowed and how it seems to be constraining the set of claims Wolfram allows himself to make, before I say why it is a wrong premise.

Examples of what I mean:

Example 1 | Wolfram doubts the idea that it's possible to measure intelligence on a single unified scale or axis.

[Wolfram:] So the question then is, you know, one thing one could take the point of view is there’s this kind of single index of smart. I mean, I think people, you know, in the 1930s,people wanted to invent kind of an index of general intelligence. They called it g for humans, which I’ve never really believed in [ . . . ] There are somethings I’m pretty good at doing where I feel I’m pretty smart. There are other things where I know I’m pretty dumb, and it’s... it’s kind of... it’s not really a, a sort of single index.

Wolfram grants that it's possible for individuals to be "smarter" than other individuals, or able to out-predict or beat them, in local, individual cases.

We all know that constructing a single-axis scale for any attribute we care to name, is logically possible. What Wolfram must be objecting to, is the idea that such an axis might be objective for intelligence - where of course we could rank, eg, possible states of a system, objectively by, say, kinetic energy.

So Wolfram grants that we can receive atoms of sense-data - individual facts of experience such as whether Alice can beat Bob at chess - that tell us something about intelligence. And it's trivial that of course we can create a single intelligence axis that has Alice and Bob and everyone else somewhere on it, whether or not that axis has anything to do with reality. What Wolfram must be objecting to, is the idea that we can, from our individual atoms of sense-data, const...
The lying p value
by kqr — 2024-11-12T06:12:59.934Z
Link: https://entropicthoughts.com/the-lying-p-value

Quick check: do you agree or disagree with the following statement:

If a study finds a result significant at a p=0.05 level, that means they have followed a methodology which produces this conclusion correctly 95 % of the time.

Yes or no? Keep that in mind, and we’ll get back to it.

I’m reading the Fisher book where he popularised the p-value[1], and I noticed he’s actually quite sensible about it:

The value for which P=0.05, or 1 in 20, is 1.96 or nearly 2; it is convenient to take this point as a limit in judging whether a deviation is to be considered significant or not. Deviations exceeding twice the standard deviation are thus formally regarded as significant. Using this criterion we should be led to follow up a false indication only once in 22 trials, even if the statistics were the only guide available.

He is talking here about the normal distribution, and saying that if you have two dice that somehow generate numbers from the normal distribution, and you get an unexpectedly large value from the d6, you should double check that you are not accidentally throwing the d20. Makes complete sense.

It turns out that many situations in hypothesis testing are equivalent to “Wait am I still holding a d6?” so this is a useful rule of thumb.

But! In science there are so many other things that can go wrong. For example, Bakker and Wicherts[2] found that 15 % of the studies they looked at drew the wrong conclusion due to making dumb mistakes in computing the significance threshold.

Think about that! The significance test pales in comparison.

Regardless of what level of significance is used in the hypothesis test, regardless of accuracy effects from selection pressure, the base rate of getting the most fundamental maths of the last step right is only 85 %. Then other problems are piled on top of that[3], so no, a significant result at p=0.05 means nothing. It’s just a sign that you might be holding another die and it is time to double-check. (E.g. through replication, or further investigation.)

^

Statistical Methods for Research Workers; Fisher; Oliver & Boyd; 1925.

^

The (mis)reporting of statistical results in psychology journals; Bakker, Wicherts; Behaviour Research Methods; 2011.

^

Consider for example the Forbes report of 88 % of spreadsheets containing errors.
Modeling AI-driven occupational change over the next 10 years and beyond
by 2120eth — 2024-11-12T04:58:26.741Z

Hello everyone! Occasional lurker, first time poster here (working in government tech ops, writer in my free time). I learned a lot from this forum when I wrote an exploratory piece about 6 key AI variables to watch last October.

Since then, I've taken a deeper dive into how quickly occupations typically change each decade (going all the way back to 1870!) to get a better sense of what a reasonable timescale for AI-driven automation of labor looks like. There was an interesting debate between Ajeya Cotra and Jason Crawford a few weeks ago about whether this would take years or decades.

I take Jason's position on this (decades), but that still leaves me predicting change much more quickly than the official U.S. government projections, which I've found to be extremely conservative, especially given predictions like Leopold Aschenbrenner's re: AGI in 2027.

My most recent piece focuses on three occupations I think might actually grow faster even if we see powerful AI emerge in the next decade. I see these ones as archetypes of the three types of work I could see continuing to exist for some time to come:

Jobs where people are needed to be personally accountable for factual accuracy in fields where there will continue to be emerging knowledge (e.g. biologists, legal experts, etc.)
Jobs where having a human is inherently valuable to the customer (therapists/counselors, and personal service workers among others)
Jobs that require significant management decisions to be made by a directly accountable individual (managers, whether directly by regulation or downstream of it, or entrepreneurs)

For now, I've left out "jobs that require physical work, specific expertise and can perform in unpredictable environments" as I see this as a bit of a question mark over the very long run. But I'm interested in doing a more specific breakdown of this sort of work in the future.

This list is perhaps a broader one than the one that @Roger Dearnaley proposed a few months ago, but I'm interested in further modeling this out in a way that hopefully helps improve official estimates and government readiness for the possible job market impacts of AGI (e.g. in these three occupations). I'd love to connect with anyone else who is working in this space, or is aware of any funding available for this type of research.

I'd also appreciate any feedback on how I've broadly categorized these AGI-proof jobs...
The Packaging and the Payload
by Screwtape — 2024-11-12T03:07:37.209Z

I.

As I've run and studied meetups, there's a useful metaphor that's become more important to how I think about them. For most meetups, there's the packaging, and a payload, and these are related but useful to approach separately. Allow me to expand.

The payload is the thing you actually want. If you order some socks off Amazon, the payload is the socks. If you take a college class, the payload is the information you wanted to learn. If you went on the internet to find pictures of cute kittens, the payload is the image of an adorable feline.

The packaging is the wrapper and delivery mechanism for the payload. If you order some socks off Amazon, the packaging is the box they came in. If you take a college class, the packaging includes the professor and the lecture hall and to a lesser extent the dorm room and the cafeteria. If you went on the internet to find pictures of cute kittens, the packaging is everything on the website that isn't cute kitten.

This makes placecats.com the platonic ideal of a website

Thinking about them as separate but related parts may not be carving at any joint in physical reality, but I find it a useful distinction.

II.

Start with the payload. Almost everyone does.

The payload changes completely depending on your field. Socks, scientific discoveries, action movies, and your twitter feed are not the same. [Citation needed.] What part of the thing you're trying to get or offer is the goal? Are there differences in quality, or is one pretty much like another?

This is what almost everyone pays attention to. It's the most visible part, and if you didn't have the payload there would be no point to any other part of the process. If you want to improve the payload, you find domain experts in that specific domain. Maybe you find specialists in sub-domains; a textiles expert isn't as useful as a clothing expert who isn't as useful as a socks expert. If the idea of a socks expert seems silly, consider a college lecture where you might have a professor who is really good at explaining, say, circuit theory or the baroque period of architecture.

The payload matters. In one sense, it's the only thing that matters. If there was no payload, there would be no point to anything else in the process. Nobody bothers setting up lecture halls and registration for information nobody cares for anyone else to learn. Amazon is not in the habit of...