trentmkelly/LessWrong-43k huggingface dataset:
Moloch games
by Chris van Merwijk — 2020-10-16T15:19:04.722Z

tl;dr: This post suggests a direction for modelling Molochs. The main thing this post does is to rename the concept of “potential games” (an existing concept in game theory) to “Moloch games” to suggest an interpretation of this class of games. I also define "the preferences of a Moloch" to generalize that notion (the preferences may be intransitive).

This post assumes that you have familiarity with game theory and the concept of a Moloch.

What do group dynamics want? If a society/group (the Moloch) wants things that are different from what the individuals want, how can we assign preferences or a utility function to that society/group that doesn't model what would be good for the aggregated preference of the individuals of the group, but that describes what the group dynamics is actually "trying" to achieve (even against the interest of its individual members)? Here is a suggested answer.

Intuition. A Moloch game is a game such that there is a utility function UM, called “the Moloch’s utility function”, such that if the agents behave individually rationally, then they collectively behave as a “Moloch” that controls all players simultaneously and optimizes UM. In particular, the Nash equilibria correspond to local optima of UM.

Not all games are Moloch games.

Definition. A game with finite number of players and for each player i a strategy space Xi is a cardinal Moloch game (in the game theory literature, a cardinal potential game), if there is a utility function UM:(∏i∈NXi)→R such that for all players i, and all strategies s−i for the other players,

ui(s′i,s−i)−ui(s′′i,s−i)=UM(s′i,s−i)−UM(s′′i,s−i)∀s′,s′′∈Xi

Intuitively, if you take any strategy-profile for all the players, and adjust the strategy of one player, then the Moloch's utility will increase/decrease by the same amount as the utility function of that particular player. Hence, intuitively, every player behaves always as if they are optimizing the Moloch's utility function.

The definition for an ordinal Moloch game replaces the condition with

ui(s′i,s−i)≥ui(s′′i,s−i) iff UM(s′i,s−i)≥UM(s′′i,s−i)∀s′,s′′∈Xi

Intuitively, UM represents the Moloch's preferences ordinally but not cardinally. Obviously, cardinal Moloch games are also ordinal Moloch games.

Example. The prisoners dilemma:

Player 2
Cooperate	Defect
Playe

...
Election Preparation
by jefftk — 2020-10-15T20:30:03.278Z

Historically, uncertainty about who is the rightful leader has often
led to violence. While I think the most likely outcome for the coming
election in the US is a peaceful transition from Trump to Biden, the
range of possibilities is wide enough that it's worth making some
preparations for worse outcomes.

The most likely risk to me seems to be supply chain disruptions. If
things go poorly, staying home is probably going to be your best
option, and you want to have whatever supplies you need on hand so
that you don't have to go out. This is always
good policy, but is especially important if there is a potential
disaster you can see coming.
Make sure you have enough food, refills on medicines, and spares for
critical items (glasses, medical equipment). If there are things that
you usually purchase in a "just in time" manner, buy ahead. Think
through things you might be going to want and consider getting them
now instead. Check in with friends and relatives and make sure
they're in an ok spot.

I think there is also some risk of rioting and fires, especially on
election night or perhaps after a court verdict is announced. If you
have a car, making sure you have a full tank of gas is worth it.
Aside from that, however, I think planning for riots is not that
different for planning for supply issues. If you would be considering
participating in riots, you would probably also want to plan in
advance for any gear you might want.

Someone who was much more risk averse than I am, or who anticipated a
much worse outcome, might consider making plans to be in a remote
area, or outside the country. I'd recommend against buying firearms:
there's a lot of practice that goes into using them well, and if you
don't know what you're doing you're probably going to make things
worse.

As someone who would like to see Biden elected, and expects you do as
well, I think the most important thing to do is to vote. A clear
victory is hard to dispute.
Covid 10/15: Playtime is Over
by Zvi — 2020-10-15T14:30:01.742Z

Previously: Covid 10/8: October Surprise

Last week the President got Covid-19, so the post was all about details and timelines. This week, the President has tested negative multiple times and my town closed its playground due to mask non-compliance, so let’s take a step back. A summary of the story so far, if you will, so that we can imagine where it will likely go from here.

A deadly pandemic falls upon the land. Hundreds of thousands or even millions may die. Huge percentages of all businesses may close, a large fraction of jobs may be lost, perhaps permanently. Social isolation threatens to radically decrease quality of life well beyond the loss of material prosperity. Tens of millions cannot pay their bills and face eviction. Impossible choices must be made.

Once all this is clear, the people divide into two camps, mostly along existing partisan lines.

One group claims their goal is to prevent economic disaster while saving lives. In practice, they act as if their goal was to have everyone ignore the pandemic, actively flouting all precautions and discouraging any countermeasures that might help.

The other group claims their goal is to save lives while preventing economic disaster. In practice, they act as if their goal was to destroy as much economic and social value as possible in the name of the pandemic as a Sacrifice to the Gods, and to pile maximum blame upon those who do not go along with this plan, while doing their best to slow down or block solutions that might solve the pandemic without sufficiently destroying economic or social value.

Is that unfair? Look around you. Think about all you’ve read, seen and heard since February. In this space and elsewhere. Decide for yourself.

How could this be? Systems that reward loyalty to the ingroup reward symbolic destructive action, while being suspicious of and therefore punishing constructive action that might be motivated by things other than loyalty to the ingroup. Morality has been reversed. Read my sequence on immoral mazes and my posts on simulacra levels for further explanation.

Thus a continuing dialectic that solves neither problem. That which favors death of things symbolically associated with the outgroup wins out. That which favors life has loyalty to life, so kill it. To stop the horrible outgroup, one must support the ingroup that much more. The dialectic continues.

The pandemic has enough ...
Evaluating expertise: a clear box model
by JustinShovelain — 2020-10-15T14:18:23.599Z

Context

Purpose of expertise modelling

To get what we value we must make good decisions. To make these decisions we must know what relevant facts are true. But the world is so complex that we cannot check everything directly ourselves and so must defer to topic “experts” for some things. How should we choose these experts and how much should we believe what they tell us? In this document, I’ll describe a way to evaluate experts.

Many of the problems in the world, be they political, economic, scientific, or personal, are caused by or exacerbated by making epistemic mistakes. We trust in the wrong advice and don’t seek out the right advice. We vote for the wrong politicians, believe the marketers, promote bad bosses, are mesmerized by conspiracy theories, are distracted by the irrelevant, fight with our neighbors, lack important information, suffer accidents, and don’t know the best of what has been discovered. If we accurately know what to do, how to do it, and why to do it, then we become more effective and motivated.

Types of expertise modelling

To evaluate these experts individually, we can use three methods: black box models, clear box models, or deferring further to other, “meta”, experts about these topic experts (see also

this

and

this

).

Black box/outside view of the expert: This type of modelling would be just looking at the expert’s prediction accuracy in the past without asking about detailed properties of how they come to those decisions. Their prediction accuracy is ultimately what we want to get at but sometimes track records are incomplete or don’t exist yet.
Clear box/white box/inside view of the expert/interpretability: This type of modelling looks inside and asks about the specific properties of the experts that make them accurate. This lets us gauge their opinions when we don’t have a predictive track record for them. It also lets us better estimate to what extent their expertise generalizes, points out possible ways they may err and how to fix these errors, and points out how to gain expertise ourselves and improve upon the state-of-the-art.
Social reputation/deference pointer: This strategy passes the buck of analyzing whether to believe an expert, to other, meta-experts; but, it still requires an ability to evaluate a meta-expert's ability to evaluate other experts, and so reduces to using black box or clear box models about the

...
Babble & Prune Thoughts
by abramdemski — 2020-10-15T13:46:36.116Z

This is an accounting of various thoughts I had when reading the Babble & Prune sequence.

Encouraging Babble

It is ironic, to me, that the Babble & Prune sequence ends with a call to exclude epistemic status tags from posts:

What happens to the reader when every post starts, "epistemic status: mostly true with a chance of rain?"

[...]

Instead of conditioning readers to hate us, I propose we return to a saner time, where the fact that your words are but a pale wavering shadow of the grand, mysterious truth in your heart is the default assumption about human communication. Where truth is a dance of successive approximations yet no step in that dance requires adult supervision. Where quibbles over certitude are banished to the comments section where they belong.

I interpret Alkjash as thinking that, if the standards were just lower in the first place, people would feel free to write more, which would get us further in the end (because the good stuff can bubble to the top).

Indeed, my impression is that the LessWrong team has worked to make LessWrong a space where people feel they can share raw thoughts rather than requiring everything to be carefully refined.

But in my opinion, the "epistemic status" flags, and similar tools, help rather than hurt.

The New Twitter Account Problem

There is a phenomenon -- let me know if you think of a better name -- which I call the new twitter account problem. My personal interaction with Twitter has been as follows:

Start a new twitter account. Follow a few people I like. Basically no followers. No pressure! I can say whatever I want! Dump some random thoughts into the new twitter account over the next few days.
Now I'm getting follows, likes, and shares. Positive reinforcement! This encourages me to keep it up.
Follows slowly climb, and I'm getting more and more interaction. Now I feel like there's something at stake, and I have to do my best. I write some good tweets, but I gradually tweet less and less.
I make an alt account for "worse thoughts", starting the cycle back at step 1. Gradually the alt account becomes my main account, and I have the same problem again, and need a third account, and a fourth... Meanwhile, the followers of my previous accounts wonder why I'm not active anymore.

LessWrong 1.0 had a similar problem. The frontpage got "too good" for people to feel like they could really post on. The "discussion post" was i...
Babble challenge: 50 ways of hiding Einstein's pen for fifty years
by Bird Concept — 2020-10-15T07:23:48.541Z

Here we go again. Time to

become stronger

.

This week’s challenge:

The year is 1855. You’ve been given a pen that Albert Einstein will use in 1905 to pen his series of “miracle papers” — after you’ve sold it to him. You know this.

Yet evil forces are conspiring to obtain the pen.

You must hide it, for fifty years.

You have 1 hour to come up with 50 ways.

Looking back

Here are the champions who made it to 50 last week, with stars indicating their streak:

★★ gjm, Vanilla_cabs, Slider, Tetraspace grouping, Harmless, jacobjacob

★ ursusminimus, haydenblord@gmail.com, Bucky, johnswentworth, Yonge, Mark Xu, Jay Anthony, Richard_Kennaway, CptDrMoreno, arxhy, magfrump, athom, ike, Dan Weinand, Jsevillamol, Ericf, ryan_b

Big kudos to everyone.

We did it again.

In fact, we did even more last week — 26 answers — compared to 25 in the week before. That’s a lot. In fact, I went through the archives, and I think the babble challenges are among the top 3 most popular LessWrong questions ever. Together they even have more answers than

the massive covid thread

.

This fills me with excitement and ambition.

We’ve made a discovery.

Who knew that there was all this latent excitement for doing weekly rationality challenges? That so many people were willing to actually roll their sleeves up, and show up every week to test the limits of our art?

There’s a spark here waiting to be fanned into a flame. Imagine where we could go if we keep this up.

Moving forwards

I’m now entering week 3 out of the 7-week babble streak I committed to. If you want more regularity in practicing your creativity, feel free to post a comment committing to also going all the way to 7.

I have some interesting plans for future weeks. But for now, my model is that for this technique to really affect my cognition, I just have to do it a lot. So, the goal of this week is simply to build up routine and consistency.

A bit more on that model:

First, I think I must build a stable “mental button”. I want to get to the point where, if it’s needed, I can choose to babble. I can press the button to generate ideas even if I feel stuck. And I can trust that they will come.

Then, I must practice pressing the button until it becomes automatic. Such that whenever I find myself in a situation where it’s needed, my mind reflexively starts babbli...
Is Stupidity Expanding? Some Hypotheses.
by David Gross — 2020-10-15T03:28:07.170Z

To be explained: It feels to me that in recent years, people have gotten stupider, or that stupid has gotten bigger, or that the parts of people that were always stupid have gotten louder, or something like that.

I’ve come up with a suite of hypotheses to explain this (with a little help from my friends). I thought I’d throw them out here to see which ones the wise crowd here think are most likely. Bonus points if you come up with some new ones. Gold stars if you can rule some out based on existing data or can propose tests by which they might be rendered more or less plausible.

The hypotheses come in two broad families: 1) my feeling that stupid is expanding is an illusion or misperception, and 2) stupid is expanding and here is why:

A: I Am Misperceiving an Expanding Stupidity And Here’s Why

I have become more attuned to stupidity for [reasons], so even though there is no more of it than usual, it stands out more to me.[1]
What used to look like non-stupidity was actually widespread conformity to a common menu of foolishnesses. Today the cultural beacons of respectable idiocy have been overthrown and there is increasing diversity in foolishness. Divergent fools seem more foolish to each other when in fact we’re all just as stupid as we’ve always been.
I’m running in stupider circles than I used to for some reason, while in general things haven’t changed much.
I am the one getting stupider, or was stupid all along, and so I don’t have the cognitive strength to accurately judge the stupidity level around me, and just happen to be thinking it is getting worse because I don’t know any better.[2]
People aren’t getting any stupider, it’s just that the AI of the bots I’m mistaking for people on-line isn’t all that good yet or isn’t designed to emulate smartness.
They’re not getting stupider; I’m just getting more conceited, and attributing stupidity to others is one way that’s playing out.
People ordinarily use different modes of thinking in different communications contexts. In some, finding the truth is important and so they exhibit rational intelligence. In others, decorative display, ritual, asserting dominance or submission, displaying group allegiances, etc. are more important and so they use modes more appropriate to those things. It’s not that people are getting stupider, but that these forms of communication that do not broadcast intelligence (a) are more am

...
The Colliding Exponentials of AI
by Vermillion — 2020-10-14T23:31:20.573Z

Epistemic status: I have made many predictions for quantitative AI development this decade, these predictions were based on what I think is solid reasoning, and extrapolations from prior data.

If people do not intuitively understand the timescales of exponential functions, then multiple converging exponential functions will be even more misunderstood.

Currently there are three exponential trends acting upon AI performance, these being Algorithmic Improvements, Increasing Budgets and Hardware Improvements. I have given an overview of these trends and extrapolated a lower and upper bound for their increases out to 2030. These extrapolated increases are then combined to get the total multiplier of equivalent compute that frontier 2030 models may have over their 2020 counterparts.

Firstly...

Algorithmic Improvements

Algorithmic improvements for AI are much more well-known and quantified than they were a few years ago, much in thanks to OpenAI’s paper and blog AI and Efficiency (2020).

OpenAI showed the efficiency of image processing algorithms has been doubling every 16 months since 2012. This resulted in a 44x decrease in compute required to reach Alexnet level performance after 7 years, as Figure 1 shows.

Figure 1, Compute to reach Alexnet level performance, OpenAI

OpenAI also showed algorithmic improvements in the following areas:

Transformers had surpassed seq2seq performance on English to French translation on WMT’14 with 61x less training compute in three years.

AlphaZero took 8x less compute to get to AlphaGoZero level performance 1 year later.

OpenAI Five Rerun required 5x less training compute to surpass OpenAI Five 3 months later.

Additionally Hippke’s LessWrong post Measuring Hardware Overhang detailed algorithmic improvements in chess, finding that Deep Blue level performance could have been reached on a 1994 desktop PC-level of compute, rather than the 1997 supercomputer-level of compute that it was, if using modern algorithms.

Algorithmic improvements come not just from architectural developments, but also from their optimization library’s. An example is Microsoft DeepSpeed (2020). DeepSpeed claims to train models 2–7x faster on regular clusters, 10x bigger model training on a single GPU, powering 10x longer sequences and 6x faster execution with 5x communication volume reduction. With up to 13 billion ...
Legalize Blackmail: An Example
by Tim Liptrot — 2020-10-14T21:18:40.765Z

This post is an example of the disutility of outlawing blackmail. It is an illustration of the argument made by Robin Hanson here

Background - Sallie Mae is a US company. For background, see here, pp. 807

On November 9, 2005, former Sallie Mae employee Michael Zahara filed a federal lawsuit against the company, alleging that it had a pattern and practice of granting forbearance in a purposeful effort to increase total student loan debt. On October 29, 2008, permission was granted to his legal counsel to withdraw from the case, citing "From counsel’s perspective, a breakdown in trust has resulted from the discovery that Relator has been arrested for extortion, the circumstances surrounding that arrest, and Relator’s failure to disclose the arrest to counsel."[36][37] On March 12, 2009, the court ruled "dismissal without prejudice" because "the plaintiff has failed to obtain substitute counsel by the deadline."[38] Zahara was seeking new counsel.[38]

Zahara was later exonerated of all charges, but was not able to resume the suit.

From a utilitarian perspective, whether Zahara did attempt to extort SM is of no relevance. Whether SM was purposefully inflating total student loan debt (which was in its interest), is massively important to the US federal budget, and to those students. Had blackmail been legal, we could better have policed Sallie Mae's behavior. This has convinced me to agree with Robin Hanson that blackmail should not be outlawed.
Libertarianism, Neoliberalism and Medicare for All?
by Logan Zoellner — 2020-10-14T21:06:08.811Z

I suspect there are a fair number of people on this site who self-identify as libertarian or neo-liberal.

This question is more for neo-liberals--those who believe "the market should do what markets are good at, governments should do what markets are bad at"-- but I would appreciate a libertarian perspective as well.

I have a basic intuition that goes like the following:

If the government is going to mandate something, it should also pay for it.

*****

For example, rather than mandating a minimum wage, it would be preferable if the government were to provide a minimum income--and pay for it using government funds. This provides the benefit of guaranteeing people a certain level of income, but avoids the drawback of tying people to certain jobs and mandating that those whose skills are worth less than the minimum wage remain unemployed.

Applying this same logic to health care, it seems one would conclude that "Medicare for all" is superior to a Public Option or requiring that employers pay for their employees health care.

The intuition is this: if the government has already identified a minimum level of health care, there is no additional benefit to privatizing the task of buying that health care. If coverage for a certain treatment is mandatory, then it becomes an inelastic good--demand no longer depends on price--therefore the only thing that matters is negotiating power. By negotiating "on behalf of us" the government has the most negotiating power possible and hence should be able to get the best prices.

This heuristic has the additional benefit of forcing the government to internalize the costs associated with its policy. No longer can the government create unfunded mandates only to discover they have a devastating ripple effect across the rest of the economy.

*****

So my question is: does this heuristic seem correct? What are some obvious drawbacks or counter-examples? What are some unintuitive cases where this heuristic could be applied--perhaps with foreseeable good or bad results? How would this be codified into law?

One interesting case is, how would this heuristic apply in the case of "negative mandates"? For example "emitting carbon dioxide is forbidden" is a foreseeable government mandate, but the best policy is generally agreed to be a carbon-tax. Perhaps this simply means t...