trentmkelly/LessWrong-43k huggingface dataset:
The Law of Least Effort Contributes to the Conjunction Fallacy
by curi — 2020-08-09T19:38:11.091Z

Continuing the theme that the “Conjunction Fallacy” experimental results can be explained by social dynamics, let’s look at another social dynamic: the Law of Least Effort (LoLE).

(Previously: Can Social Dynamics Explain Conjunction Fallacy Experimental Results? and Asch Conformity Could Explain the Conjunction Fallacy.)

The Law of Least Effort says:

the person who appears to put the least amount of effort out, while getting the largest amount of effort returned to him by others, comes across as the most socially powerful.

In other words, it’s higher status to be chased than to chase others. In terms of status, you want others to come to you, rather than going to them. Be less reactive than others.

Visible effort is a dominant issue even when it’s easy to infer effort behind the scenes. Women don’t lose status for having publicly visible hair and makeup which we can infer took two hours to do. You’re not socially permitted to call them out on that pseudo-hidden effort. Similarly, people often want to do learning and practice privately, and then appear good at stuff in front of their friends. Even if you can infer that someone practiced a bunch in private, it’s often socially difficult to point that out. Hidden effort is even more effective when people can’t guess that it happened or when it happened in the past (particularly childhood).

To consider whether LoLE contributes to the Conjunction Fallacy experimental results, we’ll consider three issues:

Is LoLE actually part of the social dynamics of our culture?

If so, would LoLE be active in most people while in the setting of Conjunction Fallacy research?

If so, how would LoLE affect people’s behavior and answers?

Is LoLE Correct Today?

LoLE comes from a community where many thousands of people have put a large effort into testing out and debating ideas. It was developed to explain and understand real world observations (mostly made by men in dating settings across many cultures), and it’s stood up to criticism so far in a competitive environment where many other ideas were proposed and the majority of proposals were rejected.

AFAIK LoLE hasn’t been tested in a controlled, blinded scientific setting. I think academia has ignored it without explanation so far, perhaps because it’s associated groups/subcultures that are currently being deplatformed and cancelled.

Like many other social dynamics, LoLE is complica...
Social Interfaces
by thoughtfulmadison — 2020-08-09T18:13:47.290Z

Programmers are familiar with navigating interfaces and protocols. Whether it’s ASCII, a function signature, an OOP interface, HTTP, or gRPC, these kinds of interfaces are ubiquitous, exist at all levels of abstraction, and are necessary for connecting distinct modules to form a coherent system.

I've been musing about the ways that culture, laws, and authority act as dynamic social interfaces. These structures seem to emerge as solutions to social coordination problems. Different solutions have different advantages and disadvantages.

Large groups have coordination problems

Many families, communes, and kibbutzes demonstrate a successful kind of anarcho-communism - there is a high degree of trust, and individuals get along through mutual aid and without formal codes. One explanation is to consider that the ad-hoc coordination exhibited in small groups works because of a kind of empathic simulation. Each individual has a highly accurate predictive model of social interaction within the group; given virtually any scenario and a subgroup, an individual can simulate how the subgroup will react to the situation. I speculate that the ability to accurately anticipate behavior is the essence of “trust”. (This sentiment seems core to expressions like “I don’t like him, but I trust him”).

However, we see empirically that the social cohesion of unstructured groups tends to dissolve as the number of members exceeds about 150. Robin Dunbar’s research on primate brain size and social groups suggests that these problems are due to fundamental cognitive limits on Homo sapiens ability to process information. This makes sense given the model of trust presented above. As the number of members in the group increases, the size of the set of possible interactions undergoes a combinatorial explosion. At some point, the cognitive load to grok it is too much. At this point, group trust sharply decreases. As simple experiments in game theory show, trustless coordination is expensive. More is different.

Mediated trust

The solution to trust and coordination problems is the introduction of external structures to mediate the interaction. For example, the prisoners dilemma is easily solved in the real world by two key mediators:

The mob boss, who decrees that finks will sleep with the fishes
The mobster’s code, which suggests that “

...
Existential Risk is a single category
by Rafael Harth — 2020-08-09T17:47:08.452Z

A lot of people speak in terms of "existential risk from artificial intelligence" or "existential risk from nuclear war." While this is fine to some approximation, I rarely see it pointed out that this is not how risk works. Existential risk refers to the probability of a set of outcomes, and those outcomes are not defined in terms of their cause.

To illustrate why this is a problem, observe that there are numerous ways for two or more things-we-call-existential-risks to contribute equally to a bad outcome. Imagine nuclear weapons leading to a partial collapse of civilization, leading to an extremist group ending the world with an engineered virus. Do we attribute this to existential risk from nuclear weapons or from Bio-Terrorism? That question is neither well-defined, nor does it matter. All that matters is how much each factor contributes to [existential risk of any form].

Thus, ask not "is climate change an existential risk," but "does climate change contribute to existential risk?" Everything we care about is contained in the second question.
Can we expect more value from AI alignment than from an ASI with the goal of running alternate trajectories of our universe?
by Maxime Riché — 2020-08-09T17:17:24.093Z

If we have an ASI, which goal is to efficiently model and run alternate trajectories of our universe (including the future) (scholastically and a high number of times), then the value of our universe would equals its expected value, right?

Can we reasonably expect to achieve more than that from AI alignment?
If not, should we simply aim for this? (Programming an ASI to model and run alternate universes may take advantage of the fact than the law of physics are constant)
What are the problems in this reasoning?

(Edited after comment by steve2152 and comment by naimenz)

Some details added for clarification :

To be more precise, what I have in mind is that the ASI is an agent which goal is:

to model the sentient part of the universe finely enough to produce sentience in an instance of its model (and it will also need to model the necessary non-sentient "dependencies")
and to instantiate this model N times. For example, playing them from 1000 A.D. to the time where no sentience remains in a given instance of modeled universe. (all of this efficiently)

An instance of the modeled universe would not be our present universe. It would be "another seed", starting before that the ASI exists and thus it would not need to model itself but only possible ("new") ASI produced inside the instances.

In the scenario I had in mind, the ASI would fill our universe will computing machines to produce as many instances as possible. (We would not use it and thus we will not need interface with the ASI)

Possible problems:

This ASI may produce a lot of alternate universe instances where an ASI (produced inside the instance) will also start to run instances of modeled universe. This would probably be pretty bad since in our universe, the history before ASI is net-negative.
This doesn't solve the problem of aligning the ASI with the goal described above. This only replaces "aligning AGI with humans values" by "aligning AGI to run instances of our universe". Yet, this seems to ease the problem by having a simpler objective: "predict the next step of the sentient part of the universe in a loop". (Finally, I don't know how, but we may use the fact that physics laws are constant and unchangeable, to my knowledge.)
10/50/90% chance of GPT-N Transformative AI?
by human_generated_text — 2020-08-09T00:10:26.117Z

In Developmental Stages of GPTs, orthonormal explains why we might need "zero more cognitive breakthroughs" to reach transformative AI, aka "an AI capable of making an Industrial Revolution sized impact". More specifically, he says that "basically, GPT-6 or GPT-7 might do it".

Besides, Are we in an AI overhang? makes the case that "GPT-3 is the trigger for 100x larger projects at Google, Facebook and the like, with timelines measured in months."

Now, assuming that "GPT-6 or GPT-7 might do it" and that timelines are "measured in months" for 100x larger projects, in what year will there be a 10% (resp. 50% / 90%) chance of having transformative AI and what would the 50% timeline look like?
Towards a Formalisation of Logical Counterfactuals
by Bunthut — 2020-08-08T22:14:28.122Z

Introduction

This is an attempt to build a basis for formalising logical counterfactuals. It's not workable as is, but I think it can potentially solve the problem of "outthinking the counterfactual".

For causal counterfactuals, we build a directed acyclic causal graph. We then modify the value of the node representing the condition, and recompute the value of the descendent nodes. I try to mirror this apporach.

The nodes of our new graph will of course be propositions, and the edges inferences. There are problems however. An inference can have multiple antecedents, and we cant just represent this by giving them all and edge to the consequent, because there can also be multiple ways to infer that proposition, and it makes much more sense for multiple incoming edges to mean that. The graph also won't be acyclic, so even if we found a way to recompute along one edge, we could get different outcomes depending on how we move through the graph. To resolve this, we need to look at logic a bit differently.

I'm using a formulation of logic as outlined by Donald Hobson here. TLDR: All inference rules have only one antecedent. They are substitutions which lead to a logically equivalent statement. Since logical equivalence is symmetrical we will make an undirected graph, which is simpler. Our graphy will have one node for every grammatical proposition of the theory, and an edge between any two conneced directly by an inference rule.

A proof of a proposition x is then a path through the graph from ⊤ to x.

Logical Counterfactual of a Set Conditional

Now, how do we solve the cyclicality? By cutting of so much that you cant go around the conditioning statement. Its clear that we can't change just that statement, because you could trivially do all the same proofs from it's double negation. So to begin we will define the condition not as a single statements but a set of them that is modified. Some definitions:

e: A single proposition.

C: A set of propositions such that every proof of e contains at least one element of C, and that there is no subset of C that can be removed without losing this property, and which doesn't contain e.

B: The set of all propositions that have a proof not containing any element of C.

G: The set of all propositions which are in C or whichs negation is in C.

For K⊂G, a K-proof ...
The Fusion Power Generator Scenario
by johnswentworth — 2020-08-08T18:31:38.757Z

Suppose, a few years from now, I prompt GPT-N to design a cheap, simple fusion power generator - something I could build in my garage and use to power my house. GPT-N succeeds. I build the fusion power generator, find that it works exactly as advertised, share the plans online, and soon the world has easy access to cheap, clean power.

One problem: at no point did it occur to me to ask “Can this design easily be turned into a bomb?”. Had I thought to prompt it with the question, GPT-N would have told me that the design could easily be turned into a bomb. But I didn’t think to ask, so GPT-N had no reason to mention it. With the design in wide use, it’s only a matter of time until people figure it out. And so, just like that, we live in a world where anyone can build a cheap thermonuclear warhead in their garage.

This scenario highlights a few key constraints which I think are under-appreciated in alignment today.

Sharing Information is Irreversible

I’ve heard people say that we can make AI safe(r) by restricting the AI’s action space to things which we can undo. Problem is, sharing information is irreversible; once the cat is out of the bag, there’s no getting it back into the bag. And if an AI can’t share information, there’s very little that it can do. Not much point in an AI which just can’t do anything observable at all. (One could design an AI to “move in mysterious ways”, but I have trouble imagining that it ends up safer that way.)

This is a problem when information itself is dangerous, e.g. knowledge of how to build a thermonuclear warhead in one’s garage.

Humans Are Not Safe

Two key properties of humans:

We do not have full introspective understanding of our own wants
We do not have the processing power to fully understand the consequences of changes

Sometimes, we get something we thought we wanted, and find out that we don’t want it after all. Either we misunderstood our own wants, or misunderstood the full implications of the change.

Most of the time, this isn’t that huge an issue. We lose some money and/or time, but we move on.

But if a human is capable of making large, irreversible changes to the world, then the problem becomes more serious. A human with access to powerful AI - even something as conceptually simple as GPT-N - is capable of making large irreversible changes, and they do not have the processing power to fully understand the implications of thos...
Evaluating Opus
by jefftk — 2020-08-08T16:40:05.679Z

Several months ago, I proposed a
bucket brigade approach to singing with friends over the Internet.
Recently, Glenn and I have been working on an implementation (prototype source
code). We can't use WebRTC (I
think) because we need fine grained control over latency, so we're
doing everything manually. Which raises the question of compression.

CD quality audio, which your browser is happy to give you, represents a
second of audio with 44,100 ("44.1kHz") 16bit samples. It's possible
to send this raw over the internet, but that's a lot of bandwidth:
88,200 bytes per second in each direction, or 1.4 Mb/s. That's not
completely nuts, but many people on Wi-Fi are in environments that
won't be able to handle that consistently.

One way to do better is to just throw away data. Instead of taking
44,100 samples every second, just take a quarter of that (11,025).
Instead of using sixteen bits per sample, just send the eight most
important ones. This is a factor of eight smaller at 175 kb/s round
trip, but compare:

(CD Quality: 44.1kHz, 16bit)

(Reduced: 11kHz, 8bit, undithered)

This doesn't sound great: there are some weird audio artifacts that
come from rounding in a predictable way. Instead, people would
normally dither it:

(Reduced: 11kHz, 8bit, dithered)

This sounds much more realistic, but it adds a lot of noise. Either way,
in addition to sounding awkward this approach also uses more bandwidth
then would be ideal. Can we do better?

I wrote to Chris Jacoby, and he suggested I look into the Opus codec. I tried it out, and
it's pretty great:

(Opus: 64 kb/s)

(Opus: 32 kb/s)

(Opus: 24 kb/s)

(Opus: 16 kb/s)

All of these are smaller than the reduced version above, and all of
them except the 16 kb/s sound substantially better.

In our use case, however, we're not talking about sending one large
recording up to the server. Instead, we'd be sending batches of
samples off every, perhaps, 200ms. Many compression systems do better
if you give them a lot to work with; how efficient is opus if we give
it such short windows?

One way to test is to break the input file up into 200 ms files,
encode each one with opus, and then measure the total size. The
default opus file format includes what I measure as ~850 bytes of
header, however, and since we control both the client and the server
we don't have to send any hea

...
How much is known about the "inference rules" of logical induction?
by Eigil Rischel — 2020-08-08T10:45:09.029Z

Context: Logical Induction is a framework that makes sense of intuitively plausible statements like "the probability that the 10101010th digit of π is odd is about 0.5".

People often do this sort of informal reasoning about mathematical conjectures. Like "The Collatz conjecture has been checked up to 268, and held for all those - updating on this, I increase my likelyhood that the conjecture is true in general".
Logical induction seems to provide, in principle, a set of rules that such updates should follow. How many of these rules are known?

Some example rules that seem very plausible (here all my variables are implicitly natural numbers):

The observation that ϕ(n0) is true does not decrease the likelyhood of ∀nϕ(n).

Updating on the observations "ϕ(n) for all 0≤n≤N", the probability of ∀nϕ(n) goes to 1 as N→∞

Do these hold for logical inductors?
The Manual Economy
by  — 2020-08-07T22:29:47.384Z

[An attempt at fiction in the style of Scott Alexander. With bits of Lewis Carroll and Douglas Adams thrown in for good measure. Cross-posted from Grand, Unified, Empty.]

The hallucination started out so normally, I completely forgot that I was tripping.

I was at the dentist, and I had just had my teeth cleaned. You know the drill, the hygienist goes through your teeth with this little spray nozzle that gets into all the cracks and cavities you pretend don’t exist when you’ve got a brush in there. Then they make you hold some disgusting not-quite-mint not-quite-water in your mouth, and swish, and spit. And spit. And spit. And after about the third blessed mouthful of real water, you can vaguely taste something other than not-quite-mint, until your salivary glands give up the ghost entirely and your mouth turns into the Sahara desert.

As I said, it was weirdly normal for a trip. I’d been expecting unicorns, or aliens, or a sky made up of funky colours and mystical cactus people who could factor large numbers. But I was at the dentist. If I’d wanted a trip to the dentist, I would have just gone to the dentist. It would have been cheaper, and probably better for my teeth.

The entire dental experience was so totally normal I completely forgot I was tripping until I went to pay, and I couldn’t find my credit card. Or any cash. My wallet had a driver’s license and various other identification cards, but no payment at all. The receptionist smiled at me politely.

“Is everything alright? Can I help you”?

I winced. “I’m sorry, I seem to have misplaced all my money, I’m not going to be able to pay my bill today”.

There was a confused pause. A giant hand walked past waving an umbrella and whistling show tunes. The receptionist winked at me with both eyes at once. I suddenly knew, somehow, that I didn’t need to pay, so I turned and walked out the door. Across the street was a bank, so I floated forward until I was inside.

The bank, like the dentist, seemed totally normal. There were no lines, but that was expected for mid-afternoon on a Tuesday. I rolled over to one of the tellers.

“Excuse me”, I said, “I seem to have lost my credit card, can you help me”?

There was another confused pause. The bank teller turned into a giant hand and flew away. The entire bank bui...
Is Wirecutter still good?
by Ben Pace — 2020-08-07T21:54:06.141Z

I have heard from several friends I trust that Wirecutter is no longer very reliable since being acquired by the New York Times in 2016, and that their Wirecutter-advised purchases have become pretty mediocre in the last year or two.

I'd be interested in people making some of that case, as answers to this post, including things like talking about purchases they made or basic errors they found in the reviews, as I don't have strong, publicly verifiable evidence on this at the minute.

This is a biased post, I'm writing this with the hope of helping propagate this info if it's true, which I suspect it is but am not confident of. Please give whatever answers you feel are most relevant.
Are Americans Becoming More Depressed?
by calebo — 2020-08-07T15:57:09.735Z

The madness of depression is, generally speaking, the antithesis of violence. It is a storm indeed, but a storm of murk. Soon evident are the slowed-down responses, near paralysis, psychic energy throttled back close to zero. Ultimately, the body is affected and feels sapped, drained.

William Styron

Are American's becoming more depressed? To be more specific, has the prevalence of major depressive disorder increased over the past few decades? It's typical to hear the answer: yes.

There are a number of related and interesting questions here:

What predictions can we make about the growth of mental health expenditure?

Are Americas over-diagnosed for mental health disorders?

Are do mental health disorders have still have too much stigma surrounding them?

Are humans able to adapt to happily adapt to modern life? Or would were we better off as hunter-gathers on the savannah?[1]

Looking at depression trends is relevant to each. But before getting too distracted, here's a simple question to start with: did the prevalence of major depressive disorder in America rise or fall from the 90s to early 2000s?

One simple way to answer questions of this form is to look at a snapshot of survey responses and compare generations. If you did that and you read the following:

Members of Generation Z, born between the mid-1990s and the early 2000s, had an overall loneliness score of 48.3. Millennials, just a little bit older, scored 45.3. By comparison, baby boomers scored 42.4. The Greatest Generation, people ages 72 and above, had a score of 38.6 on the loneliness scale.[2]

Then you'd conclude that Americans are becoming more lonely. This would be a mistake. Someone's loneliness may change throughout their life. Being a teenager may just be a lonely affair. What one wants to do is measure a population across time, not at a snapshot. Ideally, you'd give a representative part of the population the same survey across time. Unfortunately, that's rather elusive.

The first thing I found was the frequently cited study, The Epidemiology of Major Depressive Disorder. This study provides a history of the National Comorbidity Survey (NCS) conducted in 1990-1992 and its follow up a decade later. The prevalence of the first NCS survey was high: 8.6% of respondents said that they experienced depression over the past year. However, there are two reasons to think that this estimate is off: firs...
I'm looking for research looking at the influence of fiction on changing elite/public behaviors and opinions
by Timothy Underwood — 2020-08-07T13:49:58.743Z

The context of the question is that I'm a self published novelist, and I've decided that I want to focus the half of my time that I'm focusing on less commercial projects on writing books that might be directly useful in EA terms, probably by making certain ideas about AI more widely known. I at some point decided it might be a good idea to learn more about examples of literature actually making an important difference beyond the examples that immediately came to my mind -- which were Uncle Tom's Cabin, Atlas Shrugged, Methods of Rationality and the way the LGBTQ movement probably gained a lot of its present acceptance through fictional representation.

I've found some stuff through academia.edu searches (like this journal article describing the results of a survey of readers of climate change fiction), but it seems like there is a good chance that the community might be able to point me in useful directions that I won't quickly find on my own.