trentmkelly/LessWrong-43k huggingface dataset:
Ethernet Is Worth It For Video Calls
by jefftk — 2020-04-11T12:10:02.409Z

I recently ran ethernet to my

desk at

home, and I've been really
impressed with how much it helps for video calls. Not only are
garbled sections less common, I'm finding us talking over each other
less.

This makes a lot of sense: wifi's going to struggle more with latency
(lag) because the radio spectrum is a noisy shared space. I think I
hadn't realized how much of an effect a wired connection would have on
latency, or how much better a video call is when latency is lower.
This is essentially the same reason serious multiplayer gamers use
wired connections, but I hadn't been thinking of it that way.

The professional way to run ethernet is to use a roll of ethernet
cable, jacks, and a cable crimper. This lets you make very small
holes, just the size of the cable. I don't have these, it's not a
good time for borrowing things, and I didn't expect to be doing enough
ethernet for it to be worth it to buy one. So I got a long enough
cable for the whole run, erring on the "much too long" side, and made
holes big enough for the cable and jack. I was very careful of the
jack as I went, since if the jack got damaged I'd have needed to start
over.

The router was three rooms away, and I could run the cable through the
attic. I picked places at both ends that were relatively
inconspicuous, poked nails up through the ceiling in each place, found
the other ends of the nails in the attic, expanded the holes to be big
enough for the cable, ran the cable, and cleaned up the dust. My
laptop doesn't have an ethernet port, but I had an adapter. It took
me about an hour from deciding to run the cable to having everything
working.

While it's hard to quantify the effect on the calls, to check that I
wasn't imagining things I ran some latency tests with ping.
I picked an IP at my ISP and ran:

ping -c 256 -i 0.1 [IP]

This tells my computer to send 256 packets to that IP, one every
100ms, and time how long they take to come back. First I tested on a
relatively idle network, with my computer not doing anything and most
of my housemates asleep:

You can see that ethernet is generally a bit better than wifi, with
occasional blips, though even the blips aren't that bad. Then I
tested on a heavily loaded connection, by visiting a page with enough
images that it wouldn't finish downloading them before the test
stopped:

Now you can see t...
Curiosity: A Greedy Feeling
by DirectedEvolution — 2020-04-11T04:38:09.544Z

But what does the phrase “scientifically explicable” mean? It means that someone else knows how the light bulb works. - Eliezar Yudkowsky

In principle, I agree with the notion that it is unforgivable to not want to know, and not want to improve your map to match the territory. However, even the most curious person in the world cannot maintain equal curiosity about all things, and even if they could there are limits on time and energy. - Elizabeth

Rarely am I pulled by a specific desire to know. And most of my learning happens at those rare times. - Anna Salamon

Which question immediately sparks your specific desire to know?

1) Which enzymes are directly involved in the human transcription of lactase?

2) How do cells manufacture proteins?

3) Which theory is the best account of abiogenesis?

4) Is life inherently valuable?

5) If we could grow artificial human organs, would it be possible to cure aging by periodically replacing the worn-out parts of our bodies?

Without some research, I could not supply more than a rudimentary answer for any of these questions. But for me personally, #5 is the only one that sparks my curiosity.

Why? The first three questions represent different strata in the lake of systematized knowledge. If I ever needed an answer, I could look up fine-grained information on each of them. The fourth question is bottomless, and I know in advance that there will be no definitive answer. None of them suggest a pressing reason I'd want to know.

The last question is different. I can immediately see its practical and scholarly significance. Breaking it down into an array of tractable research questions, then determining what is known and unknown, would be an adventure.

In pursuing my inquiry to the limits of scientific knowledge, I would eventually arrive at strange questions, with a void where the answers should be. I'd never normally think to ask these strange questions, nor care particularly about the answers. Now they would be imbued with the significance of my original purpose.

Curiosity must have been a useful sensation for our ancestors, but a costly one. It motivates action, sometimes patterns of action that are tiring, dangerous, and require the efforts of the whole tribe. Learning is costly. So evolution shaped our curiosity into a getting feeling, a greedy feeling.

What is intrinsic motivation?

That makes curiosity sound l...
What We Owe to Ourselves
by  — 2020-04-11T01:34:22.730Z

[Cross-posted from Grand, Unified, Crazy.]

“You can never make the same mistake twice because the second time you make it, it’s not a mistake, it’s a choice.”
Steven Denn

Something that has been kicking around my mind for the last little while is the relationship between responsibility and self-compassion. A couple of people recently made some very pointed observations about my lack of self-compassion, and it provoked a strange sadness in me. Sadness because while I know that their point is true – I am often very hard on myself, to the detriment of my happiness – those thought patterns seem so philosophically necessary that I have been unable to change them. This post is my attempt to unpack and understand that philosophical necessity.

Our ability to feel compassion is intimately tied to our judgement of responsibility in a situation. If you get unexpectedly laid off from your job, that’s terrible luck and most people will express compassion. However, if you were an awful employee who showed up late and did your job poorly, then most people aren’t going to be as sympathetic when you finally get fired. As the saying goes: you made your bed, you lie in it. More abstractly, we tend to feel less compassion for someone if we think that they’re responsible for their own misfortune. This all tracks with my lack of self-compassion, as I have also been told that I have an overdeveloped sense of personal responsibility. If I feel responsible for something, I’m not going to be very compassionate towards myself when it goes wrong; I’m going to feel guilt or shame instead.

Of course, this raises the question of what we’re fundamentally responsible for; the question of compassion is less relevant if I actually am responsible for the things that are causing me grief. People largely assume that we’re responsible for our own actions, and this seems like a reasonable place to start. It makes sense, because our own actions are where we have the clearest sense of control. While we can control parts of the outside world, that process is less direct and less exact. Our control over ourselves is typically much clearer, though still not always perfect.

If we assume that we have control over ourselves and our actions, this means that we also have responsibility for ourselves and our actions. If we a...
In Defense of Politics
by ChristianKl — 2020-04-10T19:26:50.747Z

I wrote most of the following post in 2013 and cleaned up the draft to publish it now. If the post feels a bit dated, that's why.

Politics is seen as the

mindkiller

. Alyssa Vance from

http://rationalconspiracy.com

argues:

Politics is suspicious as the best means to ends for other reasons. [...] It’s also zero-sum, and extremely competitive. So much human and social capital is going there already, yours probably won’t make a dent.

Is that true? Is it impossible for the very smart person without much resources to make a dent?

Years ago I was talking with someone from an East European country about how they demonstrate to get rid of their government. When asked for a detailed background on the reasons of why the particular government should go they said that the reasons aren't well described by any English source.

I suggested that instead of spending their time being the 10,001 person attending a demonstration they should write up the reasons why the government is bad in a detailed manner and publish it in the Guardian's Comment is free section.

In that case, knowledge of the politics of the country and good writing skills would have been enough to make a dent.

When it comes to whether their government steps down, obviously it matters how other countries see the situation in the country. For someone who thinks that the government should step down, it should be obvious that it's important that the best reasons why the government should step down should be available in English.

If you look at how Mubarak lost political power in Egypt, people in the West who thought their media informed them didn't really understand the situation.

They were unaware of the relevant politics. They didn't know that according to

US embassy cables released by wikileaks

:

Academics and civilian analysts painted a portrait of an Egyptian military in intellectual and social decline, whose officers have largely fallen out of society's elite ranks. They describe a disgruntled mid-level officer corps harshly critical of a defense minister they perceive as incompetent and valuing loyalty above skill in his subordinate

The Egyptian military runs part of the Egytian economy. The IMF pushed for typical Washington Consensus policies and as a result a lot of private business came into Egypt and made money. What happened to the military?

Lee Sustar wrote in Febru...
App-Based Disease Surveillance After COVID-19
by RedMan — 2020-04-10T18:52:52.941Z

With the smartphone apps for location and contact tracing being normalized for fighting coronavirus, it opens up space for using the same techniques to fight other diseases.

HIV, Syphilis, and drug resistant gonorrhea are obvious candidates because they do not have non-human hosts.

Instrumentation would be easy. Generate a database entry when an individual is diagnosed with one of these pathogens, acquire phone data via disease surveillance authorities, use machine learning directed at that data to identify plausible intimate contacts, and send notifications with testing requirements, thrown against a database of most recent tests.

Mandate response (in the usa this would be analogous to a subpoena) to a notification (appearing at a clinic for testing and treatment) and enforce it as aggressively as corona isolation.

From an ethics standpoint, if app based corona tracing is ethical, this is ethical too. From an effectiveness standpoint, this would likely aid in the eradication of two scourges (Syph, GC) and the close control of a third (HIV).

Please let me know why I'm wrong, or alternatively, if this could be expanded even further to trace other social ills.
How to evaluate (50%) predictions
by Rafael Harth — 2020-04-10T17:12:02.867Z

I commonly hear (sometimes from very smart people) that 50% predictions are meaningless. I think that this is wrong, and also that saying it hints at the lack of a coherent principle by which to evaluate whether or not a set of predictions is meaningful or impressive. Here is my attempt at describing such a principle.

What are predictions?

Consider the space of all possible futures:

If you make a prediction, you do this:

You carve out a region of the future space and declare that it occurs with some given percentage. When it comes to evaluating the prediction, the future has arrived at a particular point within the space, and it should be possible to assess whether that point lies inside or outside of the region. If it lies inside, the prediction came true; if it lies outside, the prediction came false. If it's difficult to see whether it's inside or outside, the prediction was ambiguous.

Now consider the following two predictions:

A coin I flip comes up heads (50%)
Tesla's stock price at the end of the year 2020 is between 512$ and 514$ (50%)

Both predictions have 50% confidence, and both divide the future space into two parts (as all predictions do). Suppose both predictions come true. No sane person would look at them and be equally impressed. This demonstrates that confidence and truth value are not sufficient to evaluate how impressive a prediction is. Instead, we need a different property that somehow measures 'impressiveness'. Suppose for simplicity that there is some kind of baseline probability that reflects the common knowledge about the problem. If we represent this baseline probability by the size of the areas, then the coin flip prediction can be visualized like so:

And the Tesla prediction like so:

The coin flip prediction is unimpressive because it assigns 50% to a subset of feature space whose baseline probability is also 50%. Conversely, the Tesla prediction is impressive because it assigns 50% to a subset of future space with a tiny baseline probability. Thus, the missing property is the "boldness" of the prediction, i.e., the (relative) difference between the stated confidence and the baseline probability.

Importantly, note that we can play the same game at every percentage point, e.g.:

A number I randomize on random.org falls between 15 and 94 – 80%

Even though this is an 80% prediction, it is still unimpressi...
The Value Is In the Tails
by fylo — 2020-04-10T16:53:23.064Z

I have a friend who makes a (great) living as a professional gambler. He's originally from outside the US, but was living there during 2016 and, like everyone else in our friend group, started following the election. Since he loves to gamble, he also decided to bet on the election.

I'm not sure what his political leanings are exactly, but he's a sensible guy and made fun of Trump like the rest of us. But he also ended up betting on Trump to win, and won enough money to pay for a trip to Houston to watch the Super Bowl live in January (flights+hotel+tickets...I told you he does well).

When I asked him why he bet on Trump, he said he didn't really understand American politics, but that it seemed extremely complicated, with random things like whether it rains in certain parts of Pennsylvania potentially being important. If it's extremely complicated and arbitrary, then it's probably also hard to model. The projections he saw had the most likely outcome being a moderate win by Hilary, but since he didn't trust the models, he figured the value was in the tails: the models are likely off, which likely affects the tails more than the mean. So a landslide win by Hilary or a Trump victory seemed undervalued by gambling markets. He wished he could hedge his bets by betting on both outcomes (as opposed to a moderate Hilary win), but the only option he had was to bet on Trump to win.

This logic has stuck with me ever since: in the face of large uncertainty, we're probably getting the tails wrong more than the mean. The value is in the tails.

For a fast-moving, highly uncertain crisis -- like COVID-19 --the value being in the tails means that we're probably underestimating the risk. We're probably getting the worst-case scenarios, and the odds of them happening, wrong, and we should be weighing our expectations more heavily towards worst-case scenarios than what models, expert assessments, etc. tell us. The virus could suddenly mutate (like SARS did in a good way), there could be compounding natural disasters, the economic recovery could look more like an L than a U.

I don't claim to know how we should be responding to the epidemic, in terms of stopping the spread of the virus or combating its economic impacts, but whatever we do, we should assume the virus' damage will be worse than we think.
The One Mistake Rule
by Zvi — 2020-04-10T14:50:00.413Z

Epistemic Status: The Bed of Procrustes

If a model gives a definitely wrong answer anywhere, it is useless everywhere.

This principle is doubtless ancient, and has doubtless gone by many names with many different formulations.

All models are wrong. That does not make them useless. What makes them useless is when they are giving answers that you know are definitely wrong. You need to fix that, if only by having the model more often spit out “I don’t know.”

As an example of saying “I don’t know” that I’m taking from the comments, if you want to use Newtonian Physics, you need to be aware that it will give wrong answers in relativistic situations, and therefore slightly wrong answers in other places, and introduce the relevant error bars.

Of course, a wrong prediction of what is probably going to happen is not definitely wrong, in this sense. An obviously wrong probability is definitely wrong no matter the outcome.

The origin of this particular version of this principle was when me and a partner were, as part of an ongoing campaign of wagering, attempting to model the outcomes of sporting events.

He is the expert on sports. I am the expert on creating models and banging on databases and spreadsheets. My specialty was assuming the most liquid sports betting market odds were mostly accurate, and extrapolating what that implied elsewhere.

First we would talk and he would explain how things worked. Then I would look at the data lots of different ways and create a spreadsheet that modeled things. Then, he would vary the inputs to that spreadsheet until he got it to give him a wrong answer, or at least one that seemed wrong to him.

Then he’d point out the wrong answer and explain why it was definitely wrong. I could either argue that the answer was right and change his mind, or I could accept that it was wrong and go back and fix the model. Then the cycle repeated until he couldn’t find a wrong answer.

Until this cycle stopped, we did not use the new model for anything at all, anywhere, no matter what. If a new wrong answer was found, we stopped using the model in question until we resolved the problem.

Two big reasons:

If we did use the model, even if it was only wrong in this one place, then the one place it was wrong would be the one place we would disagree with the market. Fools and their money would be soon parted.

Also, if the model was obvio

...
Organizing a Group Buy of Flour
by jefftk — 2020-04-10T14:00:02.550Z

We just had a huge shift from people eating out to eating in, and now
a lot more people are baking, so we and a lot of people I know have
had trouble finding grocery stores with flour in stock. The
residential supply chain is struggling to keep up with demand. On the
other hand, the commercial supply chain is massively under-utilized:
so many restaurants that had been buying 50lb bags of flour regularly
are now buying none. What if those of us with households that go
through a lot of flour bought some from commercial sources? Not only
would we have flour, but there would be less pressure on residential
supplies and so more for others as well!

I looked around, and I found that Webstaurant would ship a
pallet of flour, 50 bags of 50lbs each, for $1,081
or $0.43/lb. I wrote to friends, wrote to work mailing lists, posted
on FB, and found other people that were interested. Enough people
wanted flour that I decided to place the order when it was only about
half accounted for, since I was getting about 10 more people each day.

Unfortunately, between placing the order and them shipping it they ran
out of stock:

Not only were they out of the flour I'd ordered, they were out of
all-purpose flour entirely. I considered ordering high-gluten flour,
since a lot of people wanted flour for making bread, but bread isn't
the only thing people cook and coordinating back with everyone would
be a lot of work.

One of my coworkers pointed out that Baldor, a local specialty foods
distributor, was now making home deliveries as long as you'd order at
least $250 worth. Their flour was a bit fancier (King Arthur Sir
Galahad, which is commercial King Arthur All-Purpose) and so more
expensive, but their shipping was cheaper so it was still only $0.56/lb. I
placed an order for 27 bags on Wednesday and wrote to people letting
them know about the change and asking if they wanted to cancel their
order; none of them did.

Thursday morning I set an old pallet out on our porch and put plastic
sheeting on it, so I'd be able to fully wrap the bags. They arrived
an hour later, and they were great about doing a fully contactless
delivery. They carried the bags up, put them on the pallet, and
left.

I wrapped the bags in plastic to keep them dry and keep animals out:

I told people they'd arrived, people paid me via paypal/zelle/check,
and people started...
Asymptotically Unambitious AGI
by michaelcohen — 2020-04-10T12:31:53.947Z

Original Post:

We present an algorithm [updated version], then show (given four assumptions) that in the limit, it is human-level intelligent and benign.

Will MacAskill has commented that in the seminar room, he is a consequentialist, but for decision-making, he takes seriously the lack of a philosophical consensus. I believe that what is here is correct, but in the absence of feedback from the Alignment Forum, I don't yet feel comfortable posting it to a place (like arXiv) where it can get cited and enter the academic record. We have submitted it to IJCAI, but we can edit or revoke it before it is printed.

I will distribute at least min($365, number of comments * $15) in prizes by April 1st (via venmo if possible, or else Amazon gift cards, or a donation on their behalf if they prefer) to the authors of the comments here, according to the comments' quality. If one commenter finds an error, and another commenter tinkers with the setup or tinkers with the assumptions in order to correct it, then I expect both comments will receive a similar prize (if those comments are at the level of prize-winning, and neither person is me). If others would like to donate to the prize pool, I'll provide a comment that you can reply to.

To organize the conversation, I'll start some comment threads below:

Positive feedback
General Concerns/Confusions
Minor Concerns
Concerns with Assumption 1
Concerns with Assumption 2
Concerns with Assumption 3
Concerns with Assumption 4
Concerns with "the box"
Adding to the prize pool

Edit 30/5/19: An updated version is on arXiv. I now feel comfortable with it being cited. The key changes:

The Title. I suspect the agent is unambitious for its entire lifetime, but the title says "asymptotically" because that's what I've shown formally. Indeed, I suspect the agent is benign for its entire lifetime, but the title says "unambitious" because that's what I've shown formally. (See the section "Concerns with Task-Completion" for an informal argument going from unambitious -> benign).
The Useless Computation Assumption. I've made it a slightly stronger assumption. The original version is technically correct, but setting β is tricky if the weak version of the assumption is true but the strong version isn't. This stronger assumption also simplifies the argument.
The Prior. Rather than having to do with the description length of the Turing machine simulating the envi

...