trentmkelly/LessWrong-43k huggingface dataset:
Whence the symptoms of social media?
by KatjaGrace — 2020-10-27T07:30:01.010Z

Crossposted from world spirit sock puppet.

A thing I liked about The Social Dilemma was the evocative image of oneself being in an epic contest for one’s attention with a massive and sophisticated data-nourished machine, tended by teams of manipulation experts. The hopelessness of the usual strategies—like spur-of-the-moment deciding to ‘try to use social media less’—in the face of such power seems clear.

But another question I have is whether this basic story of our situation—that powerful forces are fluently manipulating our behavior—is true.

Some contrary observations from my own life:

The phenomenon of spending way too long doing apparently pointless things on my phone seems to be at least as often caused by things that are not massively honed to manipulate me. For instance, I recently play a lot of nonograms, a kind of visual logic puzzle that was invented by two people independently in the 80s and which I play in one of many somewhat awkward-to-use phone apps, I assume made by small teams mostly focused on making the app work smoothly. My sense is that if I didn’t have nonograms style games or social media or news to scroll through, then I would still often idly pick up my phone and draw, or read books, or learn Spanish, or memorize geographic facts, or scroll through just anything on offer to scroll through (I also do these kinds of things already). So my guess is that it is my phone’s responsiveness and portability and tendency to do complicated things if you press buttons on it, that makes it a risk for time consumption. Facebook’s efforts to grab my attention probably don’t hurt, but I don’t feel like they are most of the explanation for phone-overuse in my own life.

Notifications seem clumsy and costly. They do grab my attention pretty straightforwardly, but this strategy appears to have about the sophistication of going up to someone and tapping them on the shoulder continually, when you have a sufficiently valuable relationship that they can’t just break it off you annoy them too much. In that case it isn’t some genius manipulation technique, it’s just burning through the goodwill the services have gathered by being valuable in other ways. If I get unnecessary notifications, I am often annoyed and try to stop them or destroy the thing causing them.

I do often scroll through feeds for longer than I might have planned to, but the same goes for non-m

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Looking for Roommate in California
by xiaolongbao — 2020-10-27T05:18:41.185Z

Hi all, I'm sorry if this isn't the right place to post. Please redirect me if there's somewhere else this should go.

I'm posting on behalf of my friend, who is an aspiring AI researcher in his early 20's, and is looking to live with likeminded individuals. He currently lives in Southern California, but is open to relocating (preferably USA, especially California).

Please message jeffreypythonclass+ea@gmail.com if you're interested!
Dutch-Booking CDT: Revised Argument
by abramdemski — 2020-10-27T04:31:15.683Z

This post has benefited greatly from discussion with Sam Eisenstat, Caspar Oesterheld, and Daniel Kokotajlo.

Last year, I wrote a post claiming there was a Dutch Book against CDTs whose counterfactual expectations differ from EDT. However, the argument was a bit fuzzy.

I recently came up with a variation on the argument which gets around some problems; I present this more rigorous version here.

Here, "CDT" refers -- very broadly -- to using counterfactuals to evaluate expected value of actions. It need not mean physical-causal counterfactuals. In particular, TDT counts as "a CDT" in this sense.

"EDT", on the other hand, refers to the use of conditional probability to evaluate expected value of actions.

Put more mathematically, for action a∈A, EDT uses E(U|Act=a), and CDT uses E(U|do(Act=a)). I'll write edt(a) and cdt(a) to keep things short.

My argument could be viewed as using Dutch Books to formalize Paul Christiano's "simple argument" for EDT:

Suppose I am faced with two options, call them L and R. From my perspective, there are two possible outcomes of my decision process. Either I pick L, in which case I expect the distribution over outcomes P(outcome|I pick L), or I pick R, in which case I expect the distribution over outcomes P(outcome|I pick R). In picking between L and R I am picking between these two distributions over outcomes, so I should pick the action A for which E[utility|I pick A] is largest. There is no case in which I expect to obtain the distribution of outcomes under causal intervention P(outcome|do(I pick L)), so there is no particular reason that this distribution should enter into my decision process.

However, I do not currently view the argument as favoring EDT over CDT! Instead it supports the weaker claim that the two had better agree. Indeed, the Troll Bridge problem strongly favors CDT whose expectations agree with EDT over EDT. So, this is intended to provide a strong constraint on a theory of (logical) counterfactuals, not necessarily abolish the need for them. (However, the constraint is a strong one, and it's worth considering the possibility that this constraint is all we need for a theory of counterfactuals.)

The Basic Argument

Consider any one action a∈A for which edt(a)≠cdt(a), in some decision problem. We wish to construct a modified decision problem which Dutch-books the CDT.

My argument requires an assumption that the actio...
Announcing Data Secrets Lox: An Alternative to Slate Star Codex Open Threads
by quanticle — 2020-10-27T04:24:25.079Z

In light of the shutdown of Slate Star Codex, and in particular, the lack of new SSC Open Threads, much of the SSC community has moved to a new forum: Data Secrets Lox. Data Secrets Lox is a sort of "permanent open thread" for the SSC readership, with many of the same commenters and cultural norms as the Slate Star Codex comments.

If you enjoyed the Slate Star Codex commentariat, please join us at Data Secrets Lox!
Book review: Age Later
by PeterMcCluskey — 2020-10-27T04:21:12.428Z
Link: http://www.bayesianinvestor.com/blog/index.php/2020/10/21/age-later/

Book review: Age Later, by Nir Barzilai.

Books by serious researchers on how to defeat aging are now coming out
almost as fast as I have time to read them.

This one mostly aims to enable us live in good health to 115, preferably
via a few simple pills.

Age Later is fairly similar to Sinclair's
Lifespan.
At least, the differences are small compared to how they differ from
Aubrey de Grey's Ending
Aging.
I'm a bit concerned by this, since anti-aging research has not yet
demonstrated enough results to justify converging on a single strategy.
Maybe that's just an artifact of who's writing books?

The book has only a little bit of theorizing about the causes of aging
and about why we should expect it to be curable. Barzilai endorses
Sinclair's unimpressive attempts at a theory.

Barzilai waits until the last page to mention an argument that aging
can, in principle, be fully reversed (as opposed to delayed). To wit,
that fetal cells start with an age of zero, even though the egg and
sperm show clear signs of being as old as the parents.

Studies of Centenarians

A fair amount of the book is devoted to evidence from centenarians.

Barzilai provides plenty of examples which indicate that they have far
from perfect genes and lifestyles. It's unlikely that we can get much
in the way of useful advice from this. E.g. exercise clearly helps some
people live longer, while others get can away without it. Since I can't
tell which category I'm in, I treat exercise as necessary.

One questionable example:

Most striking, two of the centenarians had variants that are a major
risk factor for Alzheimer's (APOE4) - the textbooks say they should
have been suffering from dementia at age seventy and dead at eighty

I suggest that Barzilai look for a better textbook. Experts who study
pre-agricultural tribes say that people there don't get dementia. I'm
pretty sure that's due to lifestyles, not a shortage of APOE4. Also,
APOE ε4 Is Not Associated with Alzheimer's Disease in Elderly
Nigerians. APOE4
seems well adapted for the lifestyles of many of our distant ancestors,
but not so well adapted to the lifestyles of the most developed
countries. Presumably, the APOE4 centenarians had enough features of
ancestral lifestyles to meet their particular needs.

Centenarian biomarkers seem to be a more interesting topic. High
humanin and HDL levels in
centenarians might hint at some promising interventions.

C

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On the Dangers of Time Travel
by lsusr — 2020-10-27T03:57:31.700Z

It has been obvious for decades to anyone who understands quantum mechanics that that the scientific consensus on theoretical physics is wrong. General relativity is background independent. Quantum field theory is background dependent. They cannot both be correct.

According to the Copenhagen interpretation of thermodynamics, entropy is emergent from time. Anyone with with half a Noble Prize in Physics can tell that this is backwards. Time is emergent from entropy.

Everything that can be said to physically exist, from an unobserverable wave function to living cat, is a macrostate. A random walk along microstates evolves in the direction of higher entropy macrostates even in the absence of time. In this way, entropy is more fundamental than time.

Putting entropy before time explains why all quantum fields locally maximize proper time. It solves the problem of Baryon asymmetry and dissolves the semantic stopsign at the Big Bang.

If you have worked out the details of quantum gravity for yourself then you have seen in your equations exactly how to build a time machine.

The best theoretical physicists have managed to suppress this technology. In a historically unprecedented conspiracy, they have not published anything useful for decades.

While the physicists buy time, the rest of us must invent systems to maximize the benefits of time travel while minimizing risk. As a consequence of this progress, there is a nonzero Bayesian probability we could turn on a time machine without instantly destroying the multiverse. But no weight of electronic paper discussing time travel safety can prevent a malevolent actor uninterested in safety.

As a last line of defense, the cosmic speed limit is below 88 everywhere in the solar system, it is illegal to buy plutonium in a drugstore and phone booths have been quietly disappeared. But we cannot expect such flimsy mechanisms to hold forever as technology advances.

We must build a temporal displacer first, before the enemy does.
Security Mindset and Takeoff Speeds
by DanielFilan — 2020-10-27T03:20:02.014Z

About this post

This post is a stylized transcript of a conversation between Rohin Shah and Daniel Filan, two graduate students at CHAI, that happened in 2018. It should not be taken as an exact representation of what was said, or even what order topics were brought up in, but it should give readers a sense of what was discussed, and our opinions on the topic of conversation at the time of the discussion. It also should not be assumed that any of the points brought up are original to Rohin or Daniel, just that they represent our thinking at the time of the conversation. Notes were taken by Rohin during the conversation, and Daniel took the lead in writing it into a blog post.

The conversation was precipitated when Rohin noted that researchers at CHAI, and in AI alignment more broadly, diverged in their attitudes towards something like security mindset, that we will just call security mindset despite being somewhat different to what is described in the linked blog post.

Some researchers at CHAI are very concerned about building an axiomatic understanding of artificial intelligence and proving solid theorems about the behaviour of systems that we are likely to build. In particular, they are very concerned about expecting benign behaviour without a formal proof to that effect, and believe that we should start worrying about problems as soon as we have a story for why they will be problems, rather than when they start manifesting. At the time of the conversation, Daniel was one of these researchers, who have what we’ll call “security mindset”.

In contrast, some other researchers believe that we should focus on thinking about what extra machinery is needed to build aligned AI, and try building that extra machinery for current systems. Instead of dealing with future anticipated problems today and developing a theory that rules out all undesired behaviour, these researchers believe that we should spend engineering effort to detect their occurence and fix problems once we know that they occur and have more information about them. They think that rigour and ordinary paranoia are important, but less important than security mindset advocates claim. At the time of the conversation, Rohin was one of these researchers.

During a prior conversation, Rohin noted that he believed that security mindset was less important in a world where the power of AI systems gradually increase...
A Correspondence Theorem
by johnswentworth — 2020-10-26T23:28:06.305Z

I’ve been

thinking lately

about formalizations of the

Correspondence Principle

- the idea that new theories should reproduce old theories, at least in the places where the old theories work. Special relativity reduces to Galilean relativity at low speed/energy, general relativity reduces to Newtonian gravity when the fields are weak, quantum mechanics should reproduce classical mechanics at large scale, etc. More conceptually, it’s the idea that flowers are “real”: any model which does a sufficiently-good job of predicting the world around me should have some kind of structure in it corresponding to my notion of a flower (though it may not be ontologically basic).

I want theorems telling me when my models are of the right kind, and sufficiently-well-nailed-down, that I can expect some kind of correspondence along these lines to apply for any future theory (assuming the future theory has sufficiently strong predictive power). Ideally, this would allow us to take a model and extract the “generalizable” information from it, construct some universal representation of certain components of the model which lets us find the “corresponding” components in any other model with sufficiently-good predictive performance on the same data. (

This problem

is one example of a potential application.)

This post introduces one such theorem. We’ll show that a (particular type of) correspondence theorem applies in exactly those cases where our model is able to make deterministic predictions about the relationship between some observable variables.

I've tried to keep the hairiest of the math in the appendices and the "key ideas from the math" section. If you want the key ideas with minimal math, then skip those sections.

The Claim

Here’s the setup. We have two random variables, X1 and X2, and we have enough data that we can perfectly figure out their joint distribution P[X1,X2]. We don’t necessarily know what physical process generates these variables - i.e. we don’t know the true underlying generative model. You can imagine some scientific experiment where we can collect lots of independent samples of X1,X2, then brute-force count how often each (X1,X2) pair occurs in order to estimate P[X1,X2], but we don’t have any way to experimentally probe the “internals” of the experimental setup. In other words, it's the traditional setup from frequentist ...
Top Time Travel Interventions?
by abramdemski — 2020-10-26T23:25:07.973Z

I encourage people to treat this as an exercise and avoid looking at the other answers before posting your own. (Maybe use spoiler blocks?) This is more for fun than for serious. However, it may potentially serve as an analogy to help think about what the top modern-day interventions might be.

The challenge: you have one opportunity to go back in time and change something, for the good of all humankind. Use your upvotes wisely; it's how we'll judge success. My suggestion: upvote based on what you think would actually do good; strong upvote what you think works best. If you want to give kudos for other reasons, such as insightfulness, I suggest using a comment instead.

You don't have magical powers to change anything you want (so for example, you can't just "prevent the agricultural revolution"; you have to have a plan to do that). However, you do have the ability to take modern technology and resources back with you. For simplicity, though, let's keep it to one time-travel event -- your machine is single-use-only and you can't afford to build two. (You could bring the science of time travel back with you, but I don't know if that's a good idea...)

For the sake of the thought experiment, pretend that you can actually change things via time travel, giving rise to a new timeline (rather than there only being one consistent timeline, like we'd expect of real time travel).

What do you do, to do the most good?

Stretch goals: solve the problem under harsher constraints, such as time travel machines with restricted ranges. Block key things most important to your strategies so far, and see what you can still do.

I think this problem is challenging for some specific reasons, but I'll put them behind a spoiler block for those who want to just dive into it.
ETA: I also posted a similar challenge on the EA forums.

I'm specifically interested in this challenge because of X-risk. I used to think that, in order to the most good, you basically take as much scientific knowledge as you can, as far back as you can, and try to teach it to people or something. But it's quite plausible that that just brings X-risk nearer, for a wide variety of sciences and technologies one might try to smuggle back.
Similarly, you can just try to do basic good for people -- averting large historical disasters, etc. But again, this might just accelerate progress, giving humans the power to create global cat

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Is Success the Enemy of Freedom? (Full)
by alkjash — 2020-10-26T20:25:50.503Z
Link: https://radimentary.wordpress.com/2020/10/26/is-success-the-enemy-of-freedom-full/

I. Parables

A. Anna is a graduate student studying p-adic quasicoherent topology. It’s a niche subfield of mathematics where Anna feels comfortable working on neat little problems with the small handful of researchers interested in this topic. Last year, Anna stumbled upon a connection between her pet problem and algebraic matroid theory, solving a big open conjecture in the matroid Langlands program. Initially, she was over the moon about the awards and the Quanta articles, but now that things have returned to normal, her advisor is pressuring her to continue working with the matroid theorists with their massive NSF grants and real-world applications. Anna hasn’t had time to think about p-adic quasicoherent topology in months.

B. Ben is one of the top Tetris players in the world, infamous for his signature move: the reverse double T-spin. Ben spent years perfecting this move, which requires lightning fast reflexes and nerves of steel, and has won dozens of tournaments on its back. Recently, Ben felt like his other Tetris skills needed work and tried to play online without using his signature move, but was greeted by a long string of losses: the Tetris servers kept matching him with the other top players in the world, who absolutely stomped him. Discouraged, Ben gave up on the endeavor and went back to practicing the reverse double T-spin.

C. Clara was just promoted to be the youngest Engineering Director at a mid-sized software startup. She quickly climbed the ranks, thanks to her amazing knowledge of all things object-oriented and her excellent communication skills. These days, she finds her schedule packed with what the company needs: back-to-back high-level strategy meetings preparing for the optics of the next product launch, instead of what she loves: rewriting whole codebases in Haskell++.

D. Deborah started her writing career as a small-time crime novelist, who split her time between a colorful cast of sleuthy protagonists. One day, her spunky children’s character Detective Dolly blew up in popularity due to a Fruit Loops advertising campaign. At the beginning of every month, Deborah tells herself she’s going to finally kill off Dolly and get to work on that grand historical romance she’s been dreaming about. At the end of every month, Deborah’s husband comes home with the mortgage bills for their expensive bayside mansion, paid for with “Dolly money,” a...
Does playing hard to get work? AB testing for romance
by amplemaple — 2020-10-26T15:29:21.960Z

Motivation

I have long wondered if I would be more romantically successful if I played hard to get. In a majority of my relationships I pretend to be less interested in my (female) to increase their interest in me. Because I am unusually affectionate, excitable and gregarious, playing hard to get (PHTG) moves me toward the modal behavior.

I recently moved to a coastal US city and experimented with texting strategies on dating apps. I switched to low effort, easy-to-respond-to texts, and greatly increased my dates/week rate. I now go on about two dates a week. I worry that when I meet someone that I really like, I get too excited and signal "desperate" or "low status". So only less exciting women attend the second date. This could extend the girlfriend search and force me to settle for a bad match.

The Intuition

In a date, women have to assess lots of behavioral factors about a partner. Unfortunately, dates do not offer real-time tests of problem-solving, social, physical and mental health skills. You just learn if the person is an interesting talker. So women want to infer about partner's behavioral traits from limited information.

One mechanism that female primates (including human women) have evolved is to prefer men who are high in status. Becoming high status requires those social and mental health attributes that women want, so status is correlated with effectiveness (presumably it also had direct benefits in the evolutionary environment). Women therefore evolved to be more attracted to high status men. My favorite dating blog puts it

Men can easily create [the impression that they are lower status than their partner] by playing out too many low status behaviors, making women feel like they're on a pedestal. Women are evolutionarily programmed to lose attraction for men who make them feel this way.

But women need honest signals of status (signals which are difficult to fake). A great signal would be how my peers treat me, but this signal is unavailable on a date. Instead women can only judge my status from surface signals and my reactivity.

Reactivity

To avoid reinventing the wheel, I'll quote Grotesman's practical definition here in full.

When you feel reactive in an interaction, your brain is saying, “this person is interesting and important; give them your undivided attention”. Your behaviors will have the characteristic signs of low status: anxiet

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