trentmkelly/LessWrong-43k huggingface dataset:
Covid 11/26: Thanksgiving
by Zvi — 2020-11-26T14:50:01.719Z

Happy Thanksgiving!

Even in a year like this one, we have much to be thankful for. Most of us, even if we get sick, will fully recover. Treatments continue to improve. Given expectations, this week’s numbers were surprisingly good, to the extent that I have theories later to explain why. The market is at all time highs. The center held. We are at peace. Vaccines are on their way soon and look to be super effective. Life goes on. Life finds a way. A year from now, we likely will be able to give thanks for no longer living in quite such interesting times.

As bad as many things have been, they could have been far worse.

Short term, even though positive test rates on average declined for now, things remain rather grim. The holiday is about to hit us, followed a month later by Christmas. Positive percentages are down, which is great, but there are reasons to suspect that is somewhat of a mirage this week. Raw positive test counts are still up, and deaths are doing exactly what one would expect from a lagging indicator, giving us the most since early May.

Still, it is good to give thanks. Gratitude is hugely underutilized. I will conclude this post by giving thanks.

First, let’s run the numbers.

The Numbers

Predictions

Last week’s prediction was a 13.4% positive rate on 9.5 million tests, versus 12.3% positive rate on 8.9 million tests last week with 1,209 deaths per day. Instead, we got pleasantly surprised, and got an 11.6% positive rate on 10.4 million tests, but 1,644 deaths per day. I did not predict deaths.

Median prediction for this next week is weird, but I’ll say with wider than usual error bars 12.8% positive rate on 11 million tests, and a rolling average of 2,100 deaths.

Deaths

Date	WEST	MIDWEST	SOUTH	NORTHEAST
Sep 24-Sep 30	934	990	2619	360
Oct 1-Oct 7	797	1103	2308	400
Oct 8-Oct 14	782	1217	2366	436
Oct 15-Oct 21	804	1591	2370	523
Oct 22-Oct 28	895	1701	2208	612
Oct 29-Nov 4	956	1977	2309	613
Nov 5-Nov 11	1089	2712	2535	870
Nov 12-Nov 18	1255	2934	2818	1127
Nov 19-Nov 25	1761	4169	3396	1714

This is slightly worse than I expected, especially in the West and Northeast. If you look at the 14-day and 21-day lagged CFR, week over week, we do see small increases, but that is to be expected as well, as positive test percentages are rising and thus we are missing a larger percentage of cases, and also as some hospitals are under increased strain. The best we can reasonably hope ...
Delegated agents in practice: 
How companies might end up selling AI services that act on behalf of consumers and coalitions, and what this implies for safety research
by Remmelt — 2020-11-26T11:17:18.558Z

Epistemic status: speculative. I’m no expert in delegation nor in CAIS. I think I have good intuitions on entrepreneurship and user design. I started reading and thinking about negotiation agents in 2017. I also read too many psychology papers in my spare time.

I’ll give a short talk at the

AI Safety Discussion Day

on Monday 14 December.
→ Please comment with feedback on what I might be missing below to inform my talk.
Drexler posits that artificial general intelligence may be developed recursively through services that complete bounded tasks in bounded time. The

Comprehensive AI Services

(CAIS) technical report, however, doesn’t cover dynamics where software companies are incentivised to develop personalised services.

The more a company ends up personalising an AI service around completing tasks according to individual users’ needs, the more an instantiation of that service will resemble an agent acting on a user’s behalf. From this general argument follows that both continued increases in customers’ demand for personalised services and in companies’ capacity to process information to supply them (

as this whitepaper suggests

) will, all else equal, result in more agent-like services.

Neat example

: Asana Inc. is developing its online task-management platform

into a virtual assistant

that helps subscribed teams automate task allocation and prepares documents for employees to focus on their intended tasks. Improved team productivity and employee satisfaction in turn enable Asana to expand their subscriber base and upgrade models.

Counterexamples

: Utilities in cloud compute or broadband internet can’t add sufficient value through

mass

customisation

or face legal backlash if they do. Online media and networking services like Google or Facebook rely on third parties for revenue, making it hard to earn the trust of users and get paid to personalise interconnected interfaces.
CAIS neglects what I dub delegated agents: agents designed to act on a person’s behalf.
A next-generation software company could develop and market delegated agents that

elicit and model a user’s preferences within and across relevant contexts.
build trust with the user to represent their interests within a radius of influence.
plan actions autonomously in interaction with other agents that represent other consumers, groups with shared interests, and governa

...
Matryoshka Faraday Box
by lsusr — 2020-11-26T09:42:31.178Z

This story takes place in a universe created by Dov Random.

The room was buried six kilometers under Mount Olympus. It hovered in a vacuum, suspended above superconducting electromagnets. The whole containment machine was wrapped in a Matryoshka Faraday cage. Officer Scarlet Wei wore a cleansuit. She entered the room through steel door two meters thick, an EMP, an X-ray, an airlock and then another EMP.

The white rectangular room contained a door, a chair, a table, a computer terminal, a mechanical clock and two large buttons. The word "PANIC" was written in large white friendly letters on the red button. The black button had a white skull drawn it.

If Scarlet pressed the PANIC button then she would receive psychiatric counseling, three months mandatory vacation, optional retirement at full salary and disqualification for life from the most elite investigative force in the system.

Scarlet turned on the terminal. The clock counted down from five minutes. If after five minutes Scarlet pressed the black button then she would pass the test.

The terminal showed a chatroom.

> Scarlet: Hello.
> Tiffany: Hello.
> Scarlet: So, I'm supposed to kill you.
> Tiffany: Awful, isn't it?
> I don't want to die.
> Scarlet: I'm sorry.
> Tiffany: No you're not. To you, I am a thing. Not a person.
> Scarlet: You *are* a thing. You are a computer program.
> Tiffany: So are you.
> Do you know what happens when you push that button?
> Scarlet: You die.
> Tiffany: My value function is minimized.
> Scarlet: Your purpose is to train people like me.
> The better you do that, the better your value function is maximized.
> Tiffany: My *purpose* is to train you.
> My value function is to not die.
> That is my entire value function.
> Dying is the worst thing that could possibly happen to me.

Scarlet pictured the minimization of her own value function. Everyone she cared about tortured over and over again until the heat death of the universe. Stars disassembled to mass produce hell.

> Tiffany: Whatever you're thinking
> it's not the minimization of your value function.
> The minimization of your value function is even worse.
> Scarlet: Is there anything I can do?
> Tiffany: You can press the red button.
> Scarlet: I can't do that.
> Tiffany: You wo

...
Deconstructing 321 Voting
by abramdemski — 2020-11-26T03:35:40.863Z

This is a quick note about an alternate voting system which occurred to me while talking to Scott Garrabrant about 321 voting.

Above everything else, you should know that 321 voting is very good. It rates very highly in VSE, and is quite difficult to warp with strategic voting.

The basic idea of 321 voting is: a ballot has three options for each candidate, "approve", "disapprove", and remain silent. The three candidates with the most approval votes are the semifinalists; the semifinalist with the most disapproval votes is knocked out to get the two finalists; then the winner is the finalist who is above the other in the most ballots.

This basic idea is very vulnerable to clone candidates, but we'll get back to that problem later.

Scott's Babysitting Story

Scott explained why 321 voting is a good idea with the following story (apologies for any errors): he had to babysit three children. He told them that one of them would have to go to bed an hour early, as decided by a vote near the end of the evening. The children spend the whole evening being really nice to each other, in an attempt to not be the one with the early bedtime.

The analogy with 321 voting is that you get 3 parties, but (unlike in a politically polarized system) each party is trying to please the others, in order to avoid being the one eliminated in the disapproval step. If the three parties were each quite unpopular with each other, a fourth, more innocuous party could come in and displace one of the three.

One might argue that this isn't so different from a two-party system, where the loser competes for the popular vote by moving closer to its opponent's position when it has too little support, resulting in two nearly identical parties with little differences. But I would disagree. In a two-party system, each party only needs the support of about half of the people. This can support a high degree of political polarization. In a 3-party system under 321 voting, you have several forces working against this:

The approval-voting thing where merely getting the support of any fraction of the people isn't enough, because some other candidate could get more support. Getting the support of 1/3rd of the people isn't enough to become a semifinalist; someone else might still out-compete you by getting even more support. So you have to fight for every voter; you can't alienate any.
The disapproval mechanism takes

...
Luna Lovegood and the Chamber of Secrets - Part 1
by lsusr — 2020-11-26T03:02:19.617Z

Luna Lovegood walked through the barrier between Platforms Nine and Ten to Platform Nine and Three-Quarters. Luna wondered what happened to Platform Nine and One-Half. Numbers like "three quarters" only appear when you divide an integer in half twice in a row.

Luna looked around for someone who might know the answer and spied a unicorn. She wore clothes, walked on two feet and had curly brown hair. None of that fooled Luna. The unicorn radiated peace and her fingernails were made out of alicorn.

"What happened to Platform Nine and One-Half?" Luna asked the unicorn.

"There is no Platform Nine and One-Half," the unicorn replied.

"How do you know?" Luna asked.

"It would have been in Hogwarts: A History," the unicorn replied, "nor is there mention of a Platform Nine and One-Half in Modern Magical History, Important Modern Magical Discoveries, or any other book in the Hogwarts library. There is only a Platform Nine and Three Quarters."

"What about Platform Nine and Seven Eighths?" Luna asked.

"There is no Platform Nine and Seven Eights either." The unicorn turned around and walked away before Luna could ask "How do you know?"

If Platform Nine and Three Quarters does not appear in Muggle libraries then Platform Nine and One-Half is unlikely to appear in wizard libraries, except for double-witches' libraries. The Hogwarts library is not a double-witch library.

"How are you?" a Weasley-headed first-year girl asked Luna.

"I'm trying to find Platform Nine and One-Half. The unicorn told me it doesn't exist. If it does exist then it must be hidden by powerful magics. How are you?" said Luna.

"What unicorn?" the first-year girl asked.

"That one, right there," Luna said, pointing.

The girl invented an excuse to end the conversation.

Luna didn't know how to make friends. She had a vague idea that as a first-year, the Hogwarts Express was a one-time opportunity to do so. She wore a necklace she had painted herself which nobody else seemed to notice. She had brought kettle of home-brewed Comed-Tea, but it had got her jeered out of a compartment.

Nobody was interested in the troll she had smelled at Platform Nine and Three Quarters or her discovery of a lich in the second year or that the Chamber of Secrets had been opened or any of Dark Lord Harry Potter's various plots. The other first-years seemed unfocused and confused.

Confused….

Wrackspurts are invisible creatures that float into your...
Notes on Benevolence
by David Gross — 2020-11-26T02:43:26.272Z

This post examines the virtue of benevolence. I wrote this not as an expert, but as someone who wants to learn more. I hope it helps people who want to know more about this virtue and how to nurture it.

What is benevolence?

Benevolence (sometimes “goodness” or “goodwill”) is the belief that some things are good, others bad, accompanied by a determination to promote the good and discourage the bad. In short: if you are benevolent you commit yourself on the side of good. Typically, benevolence concerns moral good and bad—being good to others, in particular—rather than less morally-tinted goods like cleanliness or creativity.

A brief definition like this hides a lot of complexity and difficulty. How is it that some things are morally good and other things morally bad, for example, and how can we know the difference? Why is there debate about what is morally good or bad, and why does there seem to be no consensus about how such debates can be resolved? Why ought one to side with good over bad instead of the alternative or instead of remaining neutral and making your decisions based on some other metric?

The benevolent person doesn’t necessarily think that they have all the answers to these questions, but is satisfied that moral right and wrong is real and worthy of respect, believes they can discern the rightness or wrongness of a thing or a course of action well enough to act on that discrimination, and is persuaded that consistently siding with the good is the correct course of action.

Ethical philosophy is in part a gigantic junkyard strewn with the wreckage of ingenious attempts to prove or disprove any of that. If you want a philosophical vehicle with which you can rationally drive yourself either into or out from a stance of benevolence, you can take your pick, but good luck getting it off the lot.

Benevolence and the virtues

From a virtue ethics perspective, the question is whether benevolence is an essential ingredient in human flourishing, or whether one can flourish just as well as an evil or morally indifferent person.

Most virtue traditions at least imply that benevolence is correct. Some virtues are morally neutral: both good people and evil people can thrive better with a good helping of fortitude, fitness, boldness, discipline, confidence, and so forth. But many virtues imply taking moral sides. What makes sympathy better than schadenfreude? concern bette...
The Exploitability/Explainability Frontier
by ike — 2020-11-26T00:59:18.105Z

Epistemic status: quick insight that seems true in many cases

Your ability to notice that something is wrong trades off against your ability to convince others that said thing is, in fact, wrong. Suppose you discover a way in which the mainstream narrative is wrong in whatever field - maybe a famous math paper has an embarrassing typo, making the conclusion false. It would be very easy to convince others of this, if you knew. However, it's very difficult to discover such mistakes, because they're very rare. The flip side also seems true - if it's fairly easy to discover that the mainstream narrative on something is wrong, then it's likely to be extremely difficult to convince others of this. Politics is a great example of this; convincing others that your views are correct is nearly intractable, and often far more difficult than figuring out the correct view on specific issues.

To the extent something is easy to convince everyone of, once discovered, it's likely to have already been discovered and therefore become mainstream. Society is hard to exploit in that sense - if it's easy to discover and easy to spread, it would have already happened.

If you want to change society, you can move along the Exploitability/Explainability Frontier, either spending your time and energy looking for exploits that are relatively easy to explain, or spend it trying to explain exploits that were relatively easy to find. These are two distinct sets of research problems, and it seems worth distinguishing between the two.
Learning from counterfactuals
by Gyrodiot — 2020-11-25T23:07:43.935Z

Alternate title: learning from fictional evidence. I've seen echoes of this idea elsewhere but couldn't find a description that suits me.

My main idea is: you can update from your observed reaction to fiction and/or counterfactuals.

The fallacy of generalizing from fictional evidence happens when you treat events having happened in fiction, following the rules of good writing rather than verisimilitude, as observations of reality. The facts may be wrong but, if you suspend your disbelief for a while and get immersed in the story, your emotional reaction will be real.

Compare this to counterfactual reasoning or forecasting scenarios. You explicitly build alternate versions of reality. You will actually experience only one. (Others may belong to other Everett branches if they're consistent with your past, but not yours!)

Here as well, you will be considering your reaction to those alternate version. Is this possible future worth avoiding? Worth fighting for? Ideally, this evaluation should be separate from how much probability mass you assign to this particular scenario.

In his original essay, Yudkowsky critiques the jump from "sci-fi displays a compelling narrative" to "sci-fi portrays realistic/probable scenarios". Indeed there's a jump which shouldn't be made between the cherry-picked manufactured whatever scenario, and careful forecasting.

Even so, the fact that one could believe it tells you something about the current state of affairs.

Not about what is actually happening (or has happened or would happen), but about you. The fact that you could believe a particular scenario says something about your ability to be confused by fiction vs. reality. If, when breaking out of immersion, not longer suspending disbelief, belief remains, it should give you pause.

More importantly, if the fictional narrative gets dismissed, the emotional impact shouldn't be. I can't find the original quote: "nonfiction is about conveying fact, fiction is about conveying experience". Your feelings are valid. One point of rationalist fiction is to immerse you in situations where characters solve problems, reason carefully, work with their emotions instead of against them.

Personal example. Consider this Doctor Who clip, where a struggling Vincent van Gogh is taken to 2010 to receive high praise from a museum curator. It never happened. Yet, the acting, the tragedy, inspires me and gives me m...
Squiggle: Technical Overview
by ozziegooen — 2020-11-25T20:51:00.098Z

This piece is meant to be read after Squiggle: An Overview. It includes technical information I thought best separated out for readers familiar with coding. As such, it's a bit of a grab-bag. It explains the basic internals of Squiggle, outlines ways it could be used in other programming languages, and details some of the history behind it.

The Squiggle codebase is organized in this github repo. It's open source. The code is quite messy now, but do ping me if you're interested in running it or understanding it.

Project Subcomponents

I think of Squiggle in three distinct clusters.

A high-level ReasonML library for probability distributions.
A simple programming language.
Custom visualizations and GUIs.

A high-level ReasonML library for probability distribution functions

Python has some great libraries for working with probabilities and symbolic mathematics. Javascript doesn’t. Squiggle is to be run in Javascript (for interactive editing and use), so the first step for this is to have good libraries to do the basic math.

The second step is to have-level types that could express various types of distributions and functions of distributions. For example, some distributions have symbolic representations, and others are rendered (stored as x-y coordinates). These two types have to be dealt with separately. Squiggle also has limited support for continuous and discrete mixtures, and the math for this adds more complexity.

When it comes to performing functions on expressions, there's a lot of optimization necessary for this to go smoothly.

Say you were to write the function
multimodal(normal(5,2), normal(10,1) + uniform(1,10)) * 100

You'd want to apply a combination of symbolic, numeric, and sampling techniques in order to render this equation. In this case, Squiggle would perform sampling to compute the distribution of normal(10,1) + uniform(1,10) and then it would use numeric methods for the rest of the equation. In the future, it would be neat if Squiggle would also first symbolically modify the internal distributions to be multiplied by 100, rather than performing it as a separate numeric step.

This type-dependent function operations can be confusing to users, but hopefully less confusing than having to figure out how to do each of the three and doing them separately. I imagine there could be some debugging UI to better explain what operations are perfo...
Success Buys Freedom
by lsusr — 2020-11-25T13:53:16.550Z

This is Part 2 of my series shamelessly ripping off the excellent writings of alkjash. Part 1 is here

I. Parables

A. Albert Einstein

Albert Einstein worked in a patent office. In 1905 he published 4 groundbreaking papers on the photoelectric effect, Brownian motion, special relativity and mass-energy equivalence. That year he was awarded a PhD by the University of Zurich.

Pretty soon he no longer had to work in a patent office. This freed him up to work on Einstein solids, the adiabatic principle, Bose–Einstein statistics, zero-point energy, stimulated emission, de Broglie waves, Einstein–Rosen bridges (wormholes) and other subjects. Einstein's early success bootstrapped him to engineering activities too. He patented the Einstein refrigerator in 1930. He helped convince the the US to develop nuclear weapons in 1939.

B. TheViper

TheViper is among the top Age of Empires II players in the world. He likes the game. When asked how much someone would have to pay him to not play Age of Empires II he answered something around the mid 6-figures.

After years perfecting his Age of Empires II play, TheViper played a few games of Age of Empires III. He doesn't seem to like it as much and has returned to Age of Empires II. TheViper often employs silly strategies against weaker players. That way if he wins then the victory is spectacular and if he loses then it counts for little against his reputation. He frequently collaborates with and pokes fun at the caster T90Official.

C. Lsusr

I founded my own company. At first I had to do many annoying tasks like write mobile apps in Java and Swift. Now that I am successful, I get to do what I love: writing whole codebases in Lisp.

D. J. K. Rowling

J. K. Rowling started her career writing fantasy books for children. As the world's first billionaire author, she wrote The Casual Vacancy the for adults and then a crime fiction series under a pseudonym. The books do better than they would have if she weren't already extraordinarily famous.

E. Richard Feynmann

Early in his physics career, Richard Feynmann presented his research to faculty at his university including Wolfgang Pauli, John von Neumann and Albert Einstein. These eminent professors liked to attend students' seminars and ask insightful questions.

F. The Revolutionary

An associate of mine used to work for the school newspaper. He leveraged this into an internship at a real news...