trentmkelly/LessWrong-43k huggingface dataset:
Combining the best of Georgian and Harberger taxes
by Yair Halberstadt — 2021-08-12T05:55:46.424Z

Epistemic status: this probably would be a bad idea, but has some really nice theoretical properties that I hope somebody can find a way to preserve whilst making this a good idea.

I find both Georgian land taxes and Harberger taxes to be fascinating proposals to improve the way we tax land. I'll start off with a brief overview of both, then discuss benefits and advantages of both, suggest a model to combine some of the benefits of both, and analyze the combined approach. Finally I suggest areas for future research.

A Brief overview of Georgian Land Taxes

As seen on AstralCodexTen.

The key principle of Georgian land taxes is you tax natural resources at a rate such that their market price is 0.

In other words, if I own a piece of land, and build a house on it, then the government taxes the value of the land, but not the value of the house - so two identical pieces of land in the same area with different buildings on them get taxed at the same rate.

How high is that rate? At exactly the rate such that if I'd built nothing on the land I would be neutral between:

Giving it away to someone else for free so that he will pay the taxes on it instead of me.
Building a house on it and charging people rent to live in the house.

This feels right from an ethical perspective - you put effort into building stuff on the land, and you should reap the rewards of your labour. But the land belongs to everyone, and we should all share equally in natures bounty - so any benefit you get directly from the land should be given back to the people (or in practice, the government).

However it's also got a lot of economic advantages too:

Economic Advantages

Unlike all other taxes, the supply of natural resources is fixed, and so taxes on them do not distort the market at all - supply of land remains exactly the same, and willingness to buy land does too. The tax to the government over time exactly equals the previous interest adjusted cost of buying the land, so the cost of using land remains exactly the same as it would be if there were no taxes. Thus you can replace a certain percentage of current market distorting taxes with this distortion free tax, increasing total production.
There's no incentive to hold onto land for investing purposes, since the price of land is fixed at 0, no matter if the area becomes more valuable. This encourages land to be used, rather than left fallow for 20 years til

...
Framing Practicum: Bistability
by johnswentworth — 2021-08-12T04:51:53.287Z

This is a

framing practicum

post. We’ll talk about what bistability is, how to recognize bistability in the wild, and what questions to ask when you find it. Then, we’ll have a challenge to apply the idea.

Today’s challenge: come up with 3 examples of bistability which do not resemble any you’ve seen before. They don’t need to be good, they don’t need to be useful, they just need to be novel (to you).

Expected time: ~15-30 minutes at most, including the Bonus Exercise.

What’s Bistability?

The classic picture of bistability is a marble in a double bowl:

The marble has one stable equilibrium on the left, and another on the right. Although the marble has a whole continuum of possible positions, when left to its own devices for a while it will settle down to one of just two positions.

My own head-canonical examples of bistability come from digital electronics. One is the signal buffer: it turns a sorta-low voltage (like 1 V) and into an unambiguously low voltage (like 0.01 V), or a sorta-high voltage (like 4 V) into an unambiguously high voltage (like 4.99 V). One stable equilibrium is at 5 V, the other is at 0 V, and all other voltages get pushed toward one of those two. This is crucial to building large digital circuits: without buffering, 5 V would decay to 4 V then 3 V as we pass through one gate after another, and eventually we wouldn’t be able to tell whether a voltage is supposed to be high or low.

Another electronic example is the latch, one of the standard low-level memory elements in digital circuits. You can think of a latch sort of like the marble-in-a-double-bowl, but with two extra features:

The state of the marble can be read out. One “bowl” represents “0”, and the other “1”.
An input signal can switch the “marble” from one state to the other.

So, to “write” a bit into the memory element, we push the system into the desired “bowl” (i.e. basin of attraction). It then stays in that state indefinitely, and we can read out the stored bit as many times as we like until it is “overwritten” (i.e. the state is set again).

What To Look For

In general, bistability (and multiple stability) should come to mind whenever an analogue system (i.e. a system with continuous state variables) has discrete behavior. In particular, it’s usually necessary for lossless transmission/storage of discrete information - a system with a single stable equilibrium has no long-term mem...
Erratum for "From AI to Zombies"
by Valentin2026 — 2021-08-12T04:39:05.779Z

Is there any erratum for the "From AI to Zombies" book? There are so many essays, and many of them are written more than 10 years ago. It seems very likely that since then the errors or imprecisions were discovered.

To be specific, I have a very low belief in the chapter on quantum mechanics. It discusses just Copenhagen and many-worlds interpretation, ignoring all others that were already existing at this moment. What about Quantum Bayesianism, for example?

And two more personal accounts:

1) A couple of years ago I was at the conference, where few talks discussed this quite famous gedankenexperiment. When they were looking at different interpretations, according to them the many-world one was quite vaguely formulated, not allowing to make a definitive answer in the problem they considered.

2) About five years ago I talked with my friend about "From AI to Zombies". He was studying interpretations of quantum mechanics way more than I did. He said something like "Great book but the quantum mechanics chapter is over-simplified".
A Response to A Contamination Theory of the Obesity Epidemic
by skot523 — 2021-08-12T04:23:56.569Z
Link: https://goodtosell.substack.com/p/a-response-to-a-contamination-theory

EDIT: 8/12 added a paragraph with a link to my post with more stats under the regression

Copied and pasted in its entirety from my blog

Time to try my hand at another unsolvable crisis of the modern world. It is my opinion that something doesn’t add up about the increase in obesity and in all metabolic disorders in industrialized countries. There are a bevy of different theories out there, and it was my initial intuition that the problem, like many others plaguing complex systems, was multi-faceted. In addition, if there was an easy solution, epistemic humility would force me to contend with the fact that I’m just a layman in terms of nutrition, and other people should have stumbled upon the solution.

I’ll lay my biases out right now: I didn’t have a particular horse in this race diet-wise (as you can see from my initial reaction to the LessWrong post), but I definitely do want this to be an easy fix. Something along the lines of the prospect of plastics building up in us with no recourse is not a pleasant one to think about for me, I’d much rather we could just substitute an ingredient here or there.

Nevertheless, there is a theory that is so compelling that I would be remiss not to give my take here.

First, it is important to appreciate that there is something really weird (the Peery paper) about obesity in the modern world (PDF warning). The good people of LessWrong also seem to think so. I highly recommend skimming both those articles before you go forward with mine. I very much agree with their assessment of the weirdness of the epidemic. I also think our current explanations are quite lacking.

Where There’s Smoke

I’ll cut to the chase, I think the smoking gun in this whole thing is the addition of vegetable oils to our diet. I go into it a bit in my comment here, but all that info will be the same as this post.

Firstly, I highly recommend reading this series of posts by Jeff Nobbs. He is more responsible for the meat and bones of this post than I am, I’m just relating it to the Peery paper and musing a bit. It lays out an excellent and compelling case for at least looking at vegetable oils as the culprit.

Throughout our decades-long battle with chronic disease, Americans have closely followed everything the CDC, AHA, and USDA have told us to do. We're smoking less, drinking less, exercising more, eating less saturated fat and sodium, and eating more fruits and

...
Some criteria for sandwiching projects
by dmz — 2021-08-12T03:40:37.720Z

I liked Ajeya's
post
a lot, and I think the alignment community should try to do sandwiching projects along
the lines she describes. Here I wanted to flesh out some potential criteria
for a good sandwiching project; there's not too much original thinking
here but I found it helpful to write out. Most of the criteria are
actually about the chosen domain, not the plan for attacking it.

Pieces we need

An aligned metric

Our chosen task needs to come with an aligned evaluation metric based on
some expert humans or another source of ground truth. We'll use this to
evaluate how well our models do.

A narrowly superhuman model

We need a model that is capable of doing better on the task than the
labelers who will provide our training data. (One way to check this is
to train a model using the aligned metric as a training signal, although that could be expensive.)
There are a few ways the labelers might be worse than the model:

We might limit them to cap the amount of thinking time they have or
the amount of input they can see. The hope is that their
capability relative to the model thus becomes analogous to the
capacity of unrestricted future humans relative to fully
superhuman models; I think artificial restrictions will typically
make the analogy a bit strained, but we should still learn a lot.

We might pick labelers that lack domain expertise relevant to the
task. Ajeya's post suggests coding, translation, economics, or physics; other possible domains include law or medicine. The hope is that this is analogous to a future with
superhuman models that have knowledge and concepts that humans
don't. If set up well, I think this could make for a very
interesting challenge. However, it might be hard to find
sufficiently powerful models for now.

Headroom on the aligned metric

Baseline techniques for the task should fall short of optimal
performance (given only access to the labelers, not the aligned metric).
Moreover, they should fall short primarily because the objective is
misaligned, not merely because the model is incapable. There's a weaker
and a stronger version of this criterion:

It might be the case that increasing the model's capability (by
increasing capacity or pretrained knowledge) does improve
performance on the aligned metric, but much better performance is
possible at a fixed level of capability. In other words, a more
aligned objective allocates cap

...
Request for comment on a novel reference work of understanding
by ender — 2021-08-12T00:06:12.962Z

Summary of Post / TLDR;

Idealogs is a new kind of reference work for explaining complex, controversial topics.

The objective of the project is to establish, preserve, and share the sum total of mankind’s understanding.

The problems we are focused on:

A society oversaturated with information, much of it meaningless

A well-founded, but misguided obsession with finding the perfect answer, at the expense of the more productive, meaningful challenge of finding the right question.

A media ecosystem that overwhelmingly incentivizes entertainment at the expense of public affairs reporting

Our solution:

An online collection of crowdsourced, user-edited articles (akin to Wikipedia) which summarize and analyze the major writings, claims, and questions which underlie controversial subjects of interest.

Like Wikipedia, this is a noncommercial, nonprofit, user-driven, and user-managed project whose fortunes ride on finding a community of volunteers who believe in and are passionate about the idea. The success of this project hinges on fostering a community similar to that of LessWrong, where contributors are individuals who are interested in the pursuit of understanding itself, and the pursuit of sharing that understanding with others. Consequently, I think this community would uniquely appreciate this project and have interesting things to say about it.
The site is accessible at https://www.idealogs.org, and I would love to hear your thoughts, reactions, comments below :)

Introduction

Hi! Over the past four years I have been developing an idea for an online repository of understanding in my free time, gradually transforming the concept from an abstraction to a production-ready website. I am excited to announce that the project has now reached a stage where it is ready for a wider audience, and I am reaching out to the LW community in particular because I believe you are in a unique position to provide feedback and evaluation of the product itself and the philosophical ideas underpinning it. This is not a promotion, but instead:

A collection of metaphysical ideas that I have spent a large chunk of my life thinking about and pursuing, which at last have merged into a tangible system with potential to bring real change to the world.

A request for genuine feedback on both the finished product and the ideas underpinning it.

Observations

Observation 1: Knowledge vs

...
Might intelligence decrease among humanity?
by throwawayaccount111 — 2021-08-12T00:05:56.387Z

A common belief among members of this community seems to be that long-term, humans are likely to increase in intelligence, knowledge, and general problem-solving ability. I would like to take a moment to argue for the opposite position. This is not a strongly held belief of mine, but as I don’t think I’ve seen this argument mentioned explicitly here before, it seems worthwhile to present a steel-manned version of it.

The argument for long-term increased human intelligence tends to rest on a few broad assumptions (some of these may be contingent on each other and some may not; I am not making a strong effort to further classify these assumptions):

genetic engineering for human enhancement will become available or even commonplace in the future. This, and better understanding of mental health care in general, will likely increase average intelligence.
Current and future technology will allow for better interfacing with the world’s existing body of knowledge, leading to more informed decision-making and more effective problem-solving.
Human knowledge and useful techniques tend to build on each other from generation to generation, and will continue to do so, allowing for work “on the shoulders of giants”.

All of these possibilities seem quite likely, and I don’t wish to directly argue against any of them. However, there is a massive competing factor that may shape the evolution of humanity, which I have not yet seen discussed in any depth: population growth dynamics.

The fact of the matter is, intelligent, well-educated people don’t tend to have that many children. There are countless possible factors for this, but it seems plausible to attribute this in part to belief (smarter people tend to have atheistic, more pessimistic outlooks on the future, on average), in part to effective contraceptive usage, and in part due to work culture (“having children in *this* economy? With these work hours??”). In contrast, less intelligent people tend to have far more children. Again, the exact factors are hard to know with any confidence, but it seems like this is due in large part to taking more spontaneous risks (thereby leading to reduced likelihood of using birth control), higher religiosity (many religions hold that having as many children as possible is a Divine Mandate, regardless of how hard it is on the family), and lesser concern about long-term financial iss...
What is the problem?
by Carlos Ramirez — 2021-08-11T22:33:04.435Z

First post in sequence AI Defense in Depth: A Layman's Guide

AI Risk for Cavemen

A parable:

A caveman is looking at a group of cavemen shamans performing a strange ritual that summons many strange, inscrutable, and increasingly useful daemons. Some of the shamans say they're going to eventually summon a daemon so powerful that it could solve all problems, now and forever. But they warn that if this same daemon has no heart, just like every other daemon that has ever been summoned, it might devour the whole world because of unfathomable daemon urges. Other shamans say that this cannot happen, that the ritual cannot bring a daemon so powerful into the world. Besides, some of these second group of shamans claim, even a daemon so powerful would not eat the world because it would necessarily care about cavemen, in spite of being a daemon, due to being so powerful.

The first group of shamans points out that power does not require a heart, and that nobody has any idea how to give a daemon a heart. The second group of shamans ignores them. All the shamans continue the ritual. Increasingly more powerful daemons are being summoned, and the concerned group warns the World-Devourer could show up much sooner than anyone had thought.

The caveman wonders which of the shamans are right. He also wonders why the ritual continues as is. It’s like no one listens to the concerned shamans. If they’re right the world will be eaten! What are they thinking? The caveman wonders whether the shamans can be trusted.

A Primer on Long-term Thinking

Any sufficiently advanced technology is indistinguishable from magic.

-- Arthur C. Clarke

Back here in our apparently wholly natural world, we have invented something like magic. It is called science, and on the whole it has worked out pretty well so far.

Climate change is a very thorny problem, and it is not looking like we will manage to fix it. While it will hurt, a lot, it is unlikely to kill us. The best shamanic estimate is 1/1000 chance of human extinction per century.

But even so. Not great.

What if we had taken the problem seriously when we first acknowledged it, we wonder? Could we have prevented this? Maybe. But even then, it would have been painful. In the 60s, greenhouse gas (GHG) emitting technologies were already thoroughly embedded into every aspect of civilization. It would have been better to have handled it the...
Automating Auditing: An ambitious concrete technical research proposal
by evhub — 2021-08-11T20:32:41.487Z

This post was originally written as a research proposal for the new AI alignment research organization Redwood Research, detailing an ambitious, concrete technical alignment proposal that I’m excited about work being done on, in a similar vein to Ajeya Cotra’s “The case for aligning narrowly superhuman models.” Regardless of whether Redwood actually ends up working on this proposal, which they may or may not, I think there’s still a lot of low-hanging fruit here and I’d be excited about anybody giving just the auditing game, or the full automating auditing proposal, a try. If you’re interested in working on something like this, feel free to reach out to me at evanjhub@gmail.com.

Thanks to Buck Shlegeris, Chris Olah, Gabriel Goh, Paul Christiano, and Kate Woolverton for helpful comments and feedback.

The proposal

Step 1: The auditing game for language models

From “Chris Olah’s views on AGI safety:”

One of the OpenAI Clarity team’s major research thrusts right now is developing the ability to more rigorously and systematically audit neural networks. The idea is that interpretability techniques shouldn’t have to “get lucky” to stumble across a problem, but should instead reliably catch any problematic behavior. In particular, one way in which they’ve been evaluating progress on this is the “auditing game.” In the auditing game, one researcher takes a neural network and makes some modification to it—maybe images containing both dogs and cats are now classified as rifles, for example—and another researcher, given only the modified network, has to diagnose the problem and figure out exactly what modification was made to the network using only interpretability tools without looking at error cases. Chris’s hope is that if we can reliably catch problems in an adversarial context like the auditing game, it’ll translate into more reliably being able to catch alignment issues in the future.

Of all current transparency and interpretability objectives, I think that progress on the auditing game most closely tracks what I actually care about. Thus, I think the best place to start for an ambitious transparency and interpretability project is to focus on making progress on the auditing game.

Furthermore, I’m most excited about this work in the context of language models—not only because I expect language models to be closer to AGI than anything else we could currently work w...
Don't walk through the fire! Walk through the fire!
by Icarus Gallagher — 2021-08-11T19:38:32.603Z

alkjash writes about how following the rule 'walk through the fire' pretty much always makes one weaker if followed, so you should not follow it.

Isusr writes about how following the rule 'walk through the fire' can pretty consistently make one stronger if followed, so [given some preconditions, writes Isusr] you maybe should follow it.

This reads on the face of it like a deontic dilemma. Not all deontic-dilemmas-as-parsed-by-humans, just like not all questions-about-matters-of-fact-as-parsed-by-humans, can be dissolved. But I think this one can.

Don't walk-through-the-fire as a rule.

Walk through the fire in the sense that if you see a Fire that it looks like 'OH imma need to walk through that fire', WALK THROUGH IT.

In school, my brain was trained to associate [not-walking-through whatever flaming hoops those Evil Teachers laid out before me [homework, after-school activities, doublethink]] with the immediate feedback of Teacher disapproval, which triggered guilt. So my brain got in the habit of automatically walking-through-the-fire. You see something painful that it looks like you might feel guilty if you don't do? Do it. Don't ask questions about how it will help you. Ha ha. The Evil Teachers are in control. And the rule worked, back then, because they were.

Later, I got free of the teachers. I realized that the person I had been, following that rule, was insane. I learned to love-things, care-about-things, reach-for-things, independently of whatever anybody else thinks about me. [I still faceplant a lot, but less than I did. Tsuyoku naritai.] And it is in this place, psychologically, that I can rationally apply a Walk-Through-Fire rule - by noticing when it feels like a certain Something will be painful, and yet it is something-to-be-done. To these Fires, I strive to give my brain the rule "Oh, that's a fire? WALK THROUGH IT." Scheduling an oil change, and giving friends tough news, have been Fires.

At the beginning of Atlas Shrugged, Eddie Willers is returning to his job at the subtly decaying Taggart Transcontinental.

"No, thought Eddie Willers, there was nothing disturbing in the sight of the city. It looked as it had always looked. He walked on, reminding himself that he was late in returning to the office. He did not like the task which he had to perform on his return, but it had to be done. So he did not attempt to delay it, but made himself ...