trentmkelly/LessWrong-43k huggingface dataset:
Search versus design
by Alex Flint — 2020-08-16T16:53:18.923Z

This work was supported by OAK, a monastic community in the Berkeley hills. It could not have been written without the daily love of living in this beautiful community. The work involved in writing this cannot be separated from the sitting, chanting, cooking, cleaning, crying, correcting, fundraising, listening, laughing, and teaching of the whole community.

This write-up benefited from feedback from David Kristofferson, Andrew Critch, Jason Crawford, Abram Demski, and Ben Pence. Mistakes and omissions are entirely the responsibility of the author.

How is it that we solve engineering problems? What is the nature of the design process that humans follow when building an air conditioner or computer program? How does this differ from the search processes present in machine learning and evolution?

We study search and design as distinct approaches to engineering. We argue that establishing trust in an artifact is tied to understanding how that artifact works, and that a central difference between search and design is the comprehensibility of the artifacts produced. We present a model of design as alternating phases of construction and factorization, resulting in artifacts composed of subsystems that are paired with helpful stories. We connect our ideas to the factored cognition thesis of Stuhlmüller and Christiano. We also review work in machine learning interpretability, including Chris Olah’s recent work on decomposing neural networks, Cynthia Rudin’s work on optimal simple models, and Mike Wu’s work on tree-regularized neural networks. We contrast these approaches with the joint production of artifacts and stories that we see in human design. Finally we ponder whether an AI safety research agenda could be formulated to automate design in a way that would make it competitive with search.

Introduction

Humans have been engineering artifacts for hundreds of thousands of years. Until recently, we seem to have mostly solved engineering problems using a method I will call design: understanding the materials at hand and building things up incrementally. This is the approach we use today when building bridges, web apps, sand castles, pencil sharpeners, air conditioners, and so on.

But a new and very different approach to engineering has recently come online. In this new approach, which I will call search, we specify an objective function, and then set up an optimization ...
On Systems - Living a life of zero willpower
by Neel Nanda — 2020-08-16T16:44:13.100Z
Link: https://www.neelnanda.io/blog/mini-blog-post-19-on-systems-living-a-life-of-zero-willpower

(This post is about the mindset of thinking in systems and routines. This post is mostly from my perspective, but the technique is super subjective. I’ve written up a lesson plan more aimed more at teaching the tools for how to find systems for your problems)

Introduction

This is a post about systems and willpower. Willpower is a pretty fuzzy concept, for the purposes of this post I will define it as “that which is expended when I get myself to do something that isn’t the default action”. I find thinking in terms of willpower a key lens for examining my life, because I consider myself to be a person with unusually low willpower (at least, relative to my social circle of bullshit high-achievers). And this is really, really bad, because willpower is the obvious tool for taking the actions I want to take to achieve my goals. This post is my attempt to outline my various tools and hacks for getting around this, and taking the actions I care about anyway.

The key underlying idea here is that willpower is a limited resource. Every time I need to do something a bit unpleasant, every time I need to make a decision, I expend a bit of willpower. And when I run out of willpower, I just feel super tired, everything feels like it would take far too much energy, and it’s easy to fall into un-fun spirals of procrastination. This is especially bad, because these spirals of procrastination aren’t fun. There are “unproductive” things I can do that rejuvenate me, like going for a walk, meditating or reading a good book. But when I have zero willpower, I tend to do far less rejuvenating things, like scrolling endlessly through Reddit. It’s not that I’m torn between productivity and relaxation - it’s easy to fall into the trap of getting neither. So figuring out how to solve this is one of my key bottlenecks. And if you relate to the descriptions so far, I hope these tools can be useful to you too!

It’s easy to slip into guilt/self-hate about this kind of thing, and seeing it as a personal weakness. But this is obviously dumb. Guilt is a mental mechanism that prompts me to choose to take actions by spending willpower on them. Guilt is an awful solution to lacking willpower. Guilt lives in my mind, while my goals live in the world - if guilt does not help me achieve my goals, guilt is a dumb emotion....
Partially Enlightened AMA
by grumpyfreyr — 2020-08-16T09:36:58.874Z

Read first:

The Curse Of The Counterfactual
Meditation, insight and rationality

Partially enlightened means my journey is far from over. I am not totally free of suffering, though I do find suffering very entertaining, whether it's other people's suffering or my own. I am suffering right now. It's, so funny.

Edit/clarification: it's not really suffering that's funny, it's perception of/belief in suffering. Suffering is in the map, not the territory.

Partially enlightened means I understand the true nature of the problem you are trying to solve (bias) and almost everything you discuss is redundant to me. I have overcome bias to a degree that is inconceivable to the ordinary mind. that from my perspective, there are no technical or social problems to solve - or any problems for that matter.

You can ask me anything, but that does not mean I will answer anything. My aim is to be helpful-as-I-understand-helpfulness, not helpful-as-you-understand-helpfulness. The unenlightened tend to ask (metaphorically) for weapons.

One upshot of corrected perception is a shift in motivation, which means I'm quite happy to leave others' curiosity unsatisfied, even when I have an answer.

A few points before we start:

Enlightenment being a state of mind (see upper left quadrant in Attacking enlightenment), there's no point any of us trying to prove or disprove anything.
Relatedly, there's no point in asking about my inner experience. If you could understand my state of mind, you would share my state of mind, permanently. Far from being a transient idea, enlightenment is non-reversible - there are some things you just can't unsee. In general it is better to ask questions about your own inner experience.
I don't find disagreeing with people to be a good use of time and attention, so anyone who takes up a contrary position will likely be left to die on that hill.

My motivation for doing this, is to increase the certainty of (or else disprove) my conclusion that in spite of all its accomplishments, the LW community has nothing to offer me and vice versa.
Becoming an EA-influencer on YouTube etc.
by culturechange — 2020-08-16T08:09:25.018Z

Hey, fellow EA people!

I am an effective altruist from Finland. I have noticed that not so many people have heard of effective altruism. I am aware of great people like Peter Singer and William McAskill who do some great research and influence the public discussion of EA. I still believe though that there could be even more talk about EA.

The problem I found is that I couldn’t find any single famous EA related YouTube/internet personalities other than Singer, McAskill, and other fellows who are academics in this field. If you think about veganism or climate change you could find many good content creator’s on YouTube. Earthling Ed is a great example of promoting veganism really effectively.

I think starting EA-related vlog or becoming an EA-related internet personality could be really effectively altruistic as then more people could become Effective altruists. Now the problem is that many people aren’t aware of the EA thoughts.

I would, therefore, encourage the EA-community members to take up to this challenge and maybe even someone to become an online influencer. I am also thinking about the option of starting my own YouTube channel dedicated to EA-related topics. I would be also keen to cooperate with people from all around the world. I think it would be pretty unique if we could have a YouTube channel related to EA and then have people from all around the world contributing to the making of the content.

Please let me know in the comments what you think about this suggestion and would you be interested to collaborate with me with the videos or maybe give tips on how to start the YouTube career etc. I will keenly wait for all of your comments. The good thing about globalization is that it could really be possible to have a global YouTube account with people uploading videos from all around the world with EA-related topics. The important thing would be to just have really good content so that people can relate to it.
The Human Condition
by Martin Sustrik — 2020-08-16T05:23:15.027Z

This is a transcript of a recording made on August 9th, 2020 at a polling station in Vitebsk, Belarus. Aside from being a nice illustation to Milgram experiment, I couldn't resist its literary appeal, its XIX. century, almost Chekhovian, feel and have written it down as if it was a play.

MEMBERS OF THE ELECTORAL COMMISSION No. 25 are in a room. The commission consists of of both men and women of various ages, all of them teachers at the local school.

SERGEY VIKTOROVICH, the head of the Oktyabrskiy electoral district, enters. He speaks in a deep, calm, a little bit concerned, some may say even sad, voice.

SERGEY VIKTOROVICH: Good evening. Please, shut the door. We'll talk behind the closed door.

Are there only the members of the election commission here?

I think you are all aware of what's going on. I think you understand the reason why your school has been visited by the Chief of Staff of the Executive Office. Or maybe there's something that one of you does not understand? Am I wrong?

COMMISSION: Inaudible chatter.

SERGEY VIKTOROVICH: You all know? Good.

So tell me. How did it happen?

A VOICE FROM THE COMMISSION: We've counted what we've got.

SERGEY VIKTOROVICH: Great. Have all of you counted?

COMMISSION: Everyone did. Everyone has counted. And this is what we've got here, at the polling station.

SERGEY VIKTOROVICH: Good. How did the commission at the floor below counted?

COMMISSION MEMBERS: Mumbling.

SERGEY VIKTOROVICH: I see, you were not there. But don't you speak to each other?

FEMALE VOICE: Not yet. They were counting at their place and we were counting here.

SERGEY VIKTOROVICH: Well, colleagues, let's do the following...

I'll tell you that your colleagues have counted a little bit differently than you did.

They have inspected each ballot honestly and conscientiously. They have got, according to preliminary estimates, 75% for the third candidate. For the candidate who has got the most votes here, they've got something like 15%. That is consistent with the overall results in Oktyabrskiy district.

Therefore, I don't want you to be the only ones who will somehow - it's not clear whether guided by common sense, pride, sense of responsibility or whatever - stand out of the crowd.

I am, so to say, an old person. I am a contemporary of Viktor Tsoi. Even of Elvis Presley. I was born before he died. I know all those songs. Even Scorpions I know very well. But today we are not in a...
The Wrong Side of Risk
by gilch — 2020-08-16T03:50:03.900Z

Part 4 of the Inefficient Markets sequence.

[Formerly entitled How to Pick the Wrong Side,
which on reflection, I felt was too clickbaity.
I am not your financial advisor!
For educational purposes only.
Read part 1 first.]

The Basic Idea of Insurance

You want protection from a risk.
An insurer with deeper pockets offers to take that risk off your hands,
for a price.

Make no mistake,
the insurer is doing this for profit.
You are indeed paying to spread the risk around,
and your money will go to help the unfortunate.
But the insurers take in much more premium than they pay out in claims.
Is that fair or efficient?
Are they exploiting you?

Money is not the same thing as utility.
If there is something for sale that you want more than your money,
you can pay for it with your money.
Now you have less money.
This happens all the time,
and we capitalists don't think it's wrong.
It's just business.

The big market players are not simply maximizing returns.
They're investing other people's money,
and the other people want a tolerable level of volatility
more than they want optimal Kelly bets.
Their utility is not their money.
They might need their money for something else later,
at a time they find hard to predict.
If a fund has a large drawdown,
most investors will panic and bail.

Options

Insurance also exists for stocks.
They're called "put option contracts".
The fund manager pays a premium to the market
for the right, but not the obligation (the option)
to dump a certain amount of stock at an agreed-upon strike price,
within a certain time frame.
If the manager exercises that right,
the insurer is then obligated to buy the shares at the strike
even if that's far above the current fair-market price.

Make no mistake,
the insurer is doing this for profit.
Why offer the contract at all,
if the expected value is zero?
The insurers take in much more premium than they pay out in claims.
They don't offer contracts that would be a bad deal for them.
The higher the risk, the more expensive the contract.
But the fund manager doesn't have the choice.
He has investors to satisfy,
and they cannot tolerate too much risk.

So you see,
over time,
money flows from the investors to the insurers.

The options market is open to retail traders.
You too can buy insurance.
You too can be the insurer.

Which side is the better deal?
What do you want?

Bonds

A bond is a kind of loan.
Some entity,
often ...
On Need-Sets
by Marcello — 2020-08-15T23:25:50.814Z

This is a toy psychological theory which tries to explain why gratitude practices and stoicism have good effects.

Your "need-set" is all the things you need. More specifically, your need-set is the collection of things that have to seem true for you to feel either OK or better.

Broadly, we have two kinds of motivation: positive and negative. Positive motivation is when you want something and try to move towards it. Negative motivation is when you want to avoid something and try to move away from it. Positive motivation is much more detailed in its targeting and tries to do as well as it can. Negative motivation is often faster and scrambles to find any acceptable solution to the problem. From the inside, positive motivation often feels relaxed or enthusiastic, while negative motivation often feels frozen or frantic.

When you have everything in your need-set, you generally experience positive motivation. Here, you pursue things that are not in the need-set that are just nice-to-have. Conversely, when something in your need-set is missing, you generally experience negative motivation. When something you really need is missing, you may not care so much how you solve the problem, just that it goes away.

The need-set expands and contracts adaptively. When you have something good for a long time, and it seems very reliably there it often gets added to the need-set. This is called "taking things for granted". When you lose something in your need-set and finally, after attempts to get it back, give up, the thing drops out of the need-set. This process often gets called "grieving". Of course, this is oversimplified; these are not the only processes whereby things enter and exit the need-set.

In the modern world, negative motivations are overused. This is partially because the environment we evolved in is far harsher than the one we find ourselves in today. As such, negative motivations seem, to a significant extent, selected for running away from lions, avoiding getting killed by the other tribe members, and the like. However, in the industrialized world, we have basically no remaining natural predators (the ones we see tend to be locked in cages for our amusement) and violence is at very low levels. As such, because of our (comparatively) vast wealth and cushy lifestyles, we have many opportunities to take things for granted, thereby creatin...
My Understanding of Paul Christiano's Iterated Amplification AI Safety Research Agenda
by Chi Nguyen — 2020-08-15T20:02:00.205Z

Crossposted from the EA forum

You can read this post as a google docs instead (IMO much better to read).

This document aims to clarify the AI safety research agenda by Paul Christiano (IDA) and the arguments around how promising it is.

Target audience: All levels of technical expertise. The less knowledge about IDA someone has, the more I expect them to benefit from the writeup.

Writing policy: I aim to be as clear and concrete as possible and wrong rather than vague to identify disagreements and where I am mistaken. Things will err on the side of being too confidently expressed. Almost all footnotes are content and not references.

Epistemic Status: The document is my best guess on IDA and might be wrong in important ways. I have not verified all of the content with somebody working on IDA. I spent ~4 weeks on this and have no prior background in ML, CS or AI safety.

I wrote this document last summer (2019) as part of my summer research fellowship at FHI. I was planning to restructure, complete and correct it since but haven’t gotten to it for a year, so decided to just publish it as it is. The document has not been updated, i.e. nothing that has been released since September 2019 is incorporated into this document. Paul Christiano generously reviewed the first third to a half of this summary. I added his comments verbatim in the document. Apologies for the loss of readability due to this. This doesn’t imply he endorses any part of this document, especially the second half which he didn't get to review.

Purpose of this document: Clarifying IDA

IDA is Paul Christiano’s AI safety research agenda.[1] Christiano works at OpenAI which is one of the main actors in AI safety and IDA is by many considered the most complete[2] AI safety agenda.

However, people who are not directly working on IDA are often confused about how exactly to understand the agenda. Clarifying IDA would make it more accessible for technical people to work on and easier to assess for nontechnical people who want to think about its implications.

I believe that there are currently no resources on IDA that are both easy to understand and give a complete picture. Specifically, the current main resources are:

the “Iterated Amplification” sequence which is a series of curated posts by Paul Christiano that can be quite difficult to understand,

this post by Ajeya Cotra and this video by Robert Miles which ar

...
Does crime explain the exceptional US incarceration rate?
by braces — 2020-08-15T18:27:08.578Z

Open Philanthropy motivates their criminal justice grants with sentences like this: "The United States incarcerates its residents at a higher rate than any other major country. "

This sounds bad, but conservatives argue that this is because of our uniquely high crime rate. I didn't see any straightforward research looking at incarceration and crime rates across countries, so I did some simple analysis below.

One-line summary: the US's incarceration rate is still surprisingly high accounting for its homicide rate.

Update on 8/16/2020: Crossposting from here:

We don’t have an incarceration problem—we have a crime problem…The critics of ‘mass incarceration’ love to compare American incarceration rates unfavorably with European ones. Crime is inevitably left out of the analysis.

That’s from Heather MacDonald.

It’s true that the US incarceration rate is rarely presented next to crime rates. For instance, a famous statistic is that the US has around 20 percent of the world’s prisoners, but we typically don’t hear people follow that with our crime victimization numbers.

So to what extent is this all a crime problem? A simple way to test this idea is to see, at the country level, how our incarceration rate scales with our crime rate compared to other countries.

I couldn’t find these plots from some basic googling so I tried doing it myself. The incarceration data is from Wikipedia and the homicide data is from the World Bank, in both cases using the most recent data available. I believe data tends to be better for homicide rates; this is meant to be a proxy for crime broadly.

Here’s the incarceration rate against the homicide rate for all countries that were in both datasets:

Incarceration rate vs. homicide rate for all countries from both datasets.

The green line shows the fitted values from regressing the incarceration rate on the homicide rate. The regression suggests that the incarceration rate increases by 7.1 (standard error = 1.9) when the homicide rate increases by 1, and the R-squared is 0.10.

So incarceration definitely increases with crime, but based on the R-squared and a visual assessment of the points, this isn’t a very tight fit.

And yes, the US in an enormous outlier. Below I restrict to places with 3-7 homicides for every 100k people so that it’s easier to see the countries that are similar to the US.

Incarceration rate vs. homicide rate for countries simil

...
Self-Similarity Experiment
by Dawn Drescher — 2020-08-15T13:19:56.916Z

Summary: Some of the people on earth who are most similar to you are likely your own person moments from other points in time. Your degree of similarity to them informs (though I haven’t worked out how) what the density is of you-like computation in the universe. This question is interesting for evidential cooperation as I hope that it can help to disentangle evidential cooperation from infinite ethics. Here I tested how similar my decisions in the board game Othello are today compared to 2015. The result was that I chose the same move in 57% of positions for a peculiarity of 0.41 (explained below). The 2015 move was among the 2020 plausible moves in 76% of positions for a plausibility of 0.52 (explained below). (Cross-posted from Impartial Priorities.)

Motivation

I’ve become interested in what algorithms or computations are and what constitutes their similarity to understand better how large a universe would have to be for evidential cooperation in large worlds (ECL, or formally “multiverse-wide superrationality,” MSR) to be interesting. Here is an insightful article on the topic. This post only documents a self-experiment I conducted to form some intuitions for the topic. It doesn’t contain any qualitative insights.

In particular it seems to me that either (1) the universe is infinite in some way or (2) it is not. If it’s not, (a) it may be too small for ECL to be relevant or (b) it may be big enough. In case ii.a, ECL does not go through; in case ii.b, ECL is fine. But in case i, which is maybe most likely, there’s a sense in which it is more exposed to infinite ethics than all the rest of aggregative consequentialism in that it both depends and is threatened by infinity. Aggregative consequentialism is only threatened by infinity. This could be alleviated if it turned out that the expected gains from trade from ECL are considerable even in a universe that is only, say, “15 million times as large as the volume we can observe.” The article suggests that this size and even much greater finite sizes are plausible. Unfortunately, this is mostly about the volume of space and not about the amount of energy in it.

Please see the summaries by Caspar Oesterheld or Lukas Gloor for an introduction to evidential cooperation in large worlds. I’ll give a quick, narrative introduction in the following.

Another World

In the following, I’ll try to sketch the idea behind ECL...