trentmkelly/LessWrong-43k huggingface dataset:
Should I floss?
by willbradshaw — 2019-12-24T16:06:27.379Z

[Content note: This post seems to have ended up somewhere between a very long question and a very uncertain post, so I'm not sure where it belongs.]

I don't floss, and have never managed to maintain any interdental cleaning habit for more than a few weeks. Apart from enduring the standard admonitions from the dentist every six months or so, this has not yet caused me any issues. However, I'm starting to feel I should either start flossing (or using some alternative method) or decide not to, rather than just feeling vaguely guilty about it. So here I am to seek advice.

The main reason I'm not sure what I should do here is that when it comes to flossing, we seem to be in the unusual situation where the preponderance of evidence runs squarely against the very strongly stated position of basically every dentist and dental association in the world.

The dental profession seems to be unanimous in its belief that everyone should absolutely floss, and its stated reasons for believing this make intuitive sense: the bacteria that damage your teeth and gums don't care where they grow, and if you don't clean in between your teeth they'll happily accumulate there and cause progressive damage over time. Also flossing is cheap and easy and, like, teeth are really important y'all, don't take the risk.

The trouble is, the empirical support for this position just isn't there. There doesn't actually seem to be much evidence that flossing improves, well, anything really. The biggest recent story on this is this AP broadside from 2016, which claims that there is little evidence for any benefits from flossing, and what evidence there is is weak and low-quality; you can find links to the most-relevant recent studies there. But there seem to have been concerns about the evidence base for flossing going back decades, which dentists have ignored because the impact of flossing seems so obvious to them.

Last time I looked into this a few years ago I found a great post from some dental association being like "okay we admit we're really confused about the results coming out of these studies, but seriously we dentists can all tell the difference between people who floss and those who don't and the mouths of those who do look much better". I can't find it now, which makes me sad, because 100% of the rest of the response to these evidentiary concerns is dreadful. "[W]hile the effectiveness of flo

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Funk-tunul's Legacy; Or, The Legend of the Extortion War
by Zack_M_Davis — 2019-12-24T09:29:51.536Z

(A traditional folk tale of the rashunuhlist people, as told by Jessica Taylor, and literarily and mathematically adapted by the present author.)

In the days of auld lang syne on Earth-that-was, there was a population of agents playing the Nash demand game under a replicator dynamic with uniform random encounters. Whenever two agents met, each of them would name a number between 0 and 10. If the two numbers added up to 10 or less, both agents would receive of payoff of the number they named. But if the two numbers added up to more than 10, both agents would receive nothing. Agents that received higher payoffs left more descendants in the next generation, who took after their parents, as children do.

At first, the population was composed of a humble race of agents called the ceedeetee. When two of the ceedeetee met each other, each would name the number 5, and receive a payoff of 5, and all was well.

Then one day, a simple race of 9-bots invaded the land. The 9-bots would always name the number 9! When a ceedeetee agent met a 9-bot, she would reason causally: "Well, the other agent is going to name 9, so I had better name 1 if I want any payoff at all!"

And the subpopulation of 9-bots grew and grew, and the subpopulation of ceedeetee agents dwindled, until there were only one-fifth as many ceedeetee agents as there were before the 9-bot invasion.

(Because in a population with fraction p ceedeetee agents, and fraction (1−p) 9-bots, the ceedeetee agents get an average payoff of 5p+(1−p), and the 9-bots get an average payoff of 9p, leading to an equilibrium at 4p+1=9p⟹p=15 with all agents receiving an average payoff of 95=1.8.)

Then one day, during a meeting with her conspecific Cuhzil, a ceedeetee agent named Funk-tunul decided she had had enough.

"Why do we let these invaders take over all but a fifth of our ancestral homeland? They threaten to destroy the entire surplus of the interaction unless we name the number 1! It's extortion!" said Funk-tunul. "Surely something must be done."

"What can be done?" said Cuhzil. "All of the ceedeetee are already playing our optimal strategy when we meet a 9-bot. The 9-bot always names 9, so we always name 1—there's no way to do better."

"Perhaps," said Funk-tunul, her output channels blinking deep in thought. "Perhaps not."

"You're crazy," said Cuhzil. "Anyway, we haven't yet named the number 5 during this meeting. Are you ready?"

"A

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What are you reading?
by eigen — 2019-12-24T00:11:52.101Z

In my short-form, I write:

[...] This is way more obvious and way more clear in Inadequate Equilibria. Take a problem, a question and deconstruct it completely. It was concise and to the point, I think it's one of the best things Eliezer has written; I cannot recommend it enough.

Just finished Inadequate Equilibria. Now, I'm reading:

The Big Picture from Sean Carroll (which seems a really, really good companion to The Sequences.) I'm at chapter 17/50, and I'm really enjoying it so far; it's an ambitious book though!
In fiction I picked up UNSONG from Scott Alexander; I am almost finished with the first book, and I love it (I liked most of his fiction, already.)

What are you reading?
Might humans not be the most intelligent animals?
by Matthew Barnett — 2019-12-23T21:50:05.422Z

The idea that humans are the most intelligent animals on Earth appears patently obvious to a lot of people. And to a large extent, I agree with this intuition. Humans clearly dominate the world in technological innovation, control, communication, and coordination.

However, more recently I have been acquainted with some evidence that the proposition is not actually true, or at the very least is non-obvious. The conundrum arises when we distinguish raw innovative capability, from the ability to efficiently process culture. I'll explain the basic case here.

Robin Hanson has sometimes pointed to the accumulation of culture as the relevant separation between humans and other animals. Under this view, the reason why humans are able to dominate the world with technology has less to due with our raw innovation abilities, and more to do with the fact that we can efficiently process accumulated cultural information and build on it.

If the reason for our technological dominance is due to raw innovative ability, we might expect a more discontinuous jump in capabilities for AI, since there was a sharp change between "unable to innovate" and "able to innovate" during evolutionary history, which might have been due to some key architectural tweak. We might therefore expect that our AIs will experience the same jump after receiving the same tweak.

If the reason for our technological dominance is due to our ability to process culture, however, then the case for a discontinuous jump in capabilities is weaker. This is because our AI systems can already process culture somewhat efficiently right now (see GPT-2) and there doesn't seem like a hard separation between "being able to process culture inefficiently" and "able to process culture efficiently" other than the initial jump from not being able to do it at all, which we have already passed. Therefore, our current systems are currently bottlenecked on some metric which is more continuous.

The evidence for the cultural accumulation view comes from a few lines of inquiry, such as

Feral children lack an innovating culture to learn from, and are correspondingly 'unintelligent' from our point of view. This is despite the fact that feral children hold more-or-less the exact same raw innovative capabilities as normal humans. For Genie, one feral child, "Doctors found it ext

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Offset Norms
by jefftk — 2019-12-23T21:30:02.084Z

One of the responses to last week's post about

climate change was asking whether,
if you donate to the

AMF or another
charity that saves lives, should you buy carbon offsets for the
estimated emissions that causes?

I see this as a question of norms. The strongest case I see for
offsetting here, is if you think people have an obligation to make
their choices carbon neutral. Perhaps anyone who makes a decision
which entails emitting greenhouse gasses is then on the hook for
averting or capturing some equivalent amount. For example, if you
choose to fly round trip from Boston to LA, and this entails emitting
1.3T CO2e, then you should buy 1.3T CO2e of offsets. On the other
hand, if this is business travel for a company that already is
offsetting its employees' emissions, then you wouldn't need to buy
offsets.

It's a bit of a stretch to extend this to averting deaths: shouldn't
the people whose lives you save offset their own emissions? But if
you think they aren't going to, a reasonable assumption for the
extremely poor people that, ex, the AMF is helping, then perhaps you
still are responsible? [1]

This also runs into complicated questions around estimating the impact
of your decisions. If I buy a shirt at a thrift store, what is the
chance that this causes someone else to not find a shirt they like and
so buy a new one instead? If I buy leather, how much of an impact
does that have on how many cows are raised? If I rent in a place
where I can take the subway to work, but then the city refuses to
allow more construction and so someone else ends up living farther out
and driving more, how do I count this?

I think this way of thinking about emissions is coherent, but requires
people to put a lot of effort into estimating the emissions impact of
their decisions. Instead, I think carbon taxes are a much better
approach. If we tax emissions at their full social cost, then instead
of people tracking the counterfactual climate impact of their
decisions they just need to look at prices.

For example, the airlines would be taxed for emitting carbon from
flights, taking into account that high-altitude emissions are worse.
Someone buying a plane ticket will see this as a higher price, but
doesn't need to try to estimate the airline's load factor or the fuel
efficiency of its jets.

This does prompt the question, though, of what we shou...
Humans Are Embedded Agents Too
by johnswentworth — 2019-12-23T19:21:15.663Z

Most models of agency (in game theory, decision theory, etc) implicitly assume that the agent is separate from the environment - there is a “Cartesian boundary” between agent and environment. The embedded agency sequence goes through a long list of theoretical/conceptual problems which arise when an agent is instead embedded in its environment. Some examples:

No defined/input output channels over which to optimize
Agent might accidentally self-modify, e.g. drop a rock on its head
Agent might intentionally self-modify, e.g. change its own source code
Hard to define hypotheticals which don’t actually happen, e.g. “I will kill the hostages if you don’t pay the ransom”
Agent may contain subcomponents which optimize for different things
Agent is made of parts (e.g. atoms) whose behavior can be predicted without thinking of the agent as agenty - e.g. without thinking of the agent as making choices or having beliefs
Agent is not logically omniscient: it cannot know all the implications of its own beliefs

The embedded agency sequence mostly discusses how these issues create problems for designing reliable AI. Less discussed is how these same issues show up when modelling humans - and, in particular, when trying to define human values (i.e. “what humans want”). Many - arguably most - of the problems alignment researchers run into when trying to create robust pointers to human values are the same problems we encounter when talking about embedded agents in general.

I’ll run through a bunch of examples below, and tie each to a corresponding problem-class in embedded agency. While reading, bear in mind that directly answering the questions posed is not the point. The point is that each of these problems is a symptom of the underlying issue: humans are embedded agents. Patching over each problem one-by-one will produce a spaghetti tower; ideally we’d tackle the problem closer to the root.

The Keyboard is Not The Human

Let’s imagine that we have an AI which communicates with its human operator via screen and keyboard. It tries to figure out what the human wants based on what’s typed at the keyboard.

A few possible failure modes in this setup:

The AI wireheads by seizing control of the keyboard (either intentionally or accidentally)
A cat walks across the keyboard every now and then, and the AI doesn

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Autoexperiments
by Ideopunk — 2019-12-23T16:53:03.287Z

Over the next year I want to try some low-intensity daily experiments to see if they have noticeable and positive effects: Things like cold showers, a gratitude journal, cutting sugar, etc. My working plan is to do one per month for a two-week stretch, to use the other two weeks of the month as the closest I can get to a control, and to track my mood and any other relevant metrics each day. Obviously it's hard to get reliable data from these, but are there ways I could increase the likelihood of extracting good information from the noise?
Yet another Simpson's Paradox Post
by  — 2019-12-23T14:20:09.309Z
Link: https://an1lam.github.io/post/2019-12-13-alternative-explanation-of-simpsons-paradox/

Intro

Simpson's paradox is a phenomenon in statistics where a choice or treatment performs better in all sub-populations but worse in the overall population. Since first learning of Simpson's Paradox, I've struggled to develop a gut-level understanding that lets me easily detect cases of it and clearly explain its cause. This is even after reading Michael Nielsen's wonderful post that provides a number of different ways of thinking about it and Judea Pearl's fascinating analysis of it from a causality perspective. In this post, I describe an example and intuitions that finally led to me (seemingly) grokking Simpson's paradox.

The Parable of Murderball and Tea Party

Imagine we learn of a hypothetical world in which there are two countries named Gentlantis and Rageopolis. Both countries have populations of 1,000,000 people. Further, in both countries, every single individual plays one of two sports (exclusively): Murderball or Tea party. Rageopolis's residents love Murderball so 99.99% ($ 999,900 / 1,000,000 $) prefer it to Tea Party. On the other hand, the Genglantians love Tea Party and don't care for Murderball's complex rule system and drawn out games, so 99% (990,000/1,000,000) play Tea Party.

From the name, you might guess that Murderball has a much higher injury rate than Tea Party - every year, 99% of people who play Murderball get injured, compared to only 2% of annual Tea Party players. As a result, we can summarize the sports injury numbers and rates in the respective countries as follows.

Country
Murderball Players / Injuries
Tea Party Players / Injuries
Overall Injuries and Rate

Rageopolis
999,900 / 989,901
100 / 2
989,902 / 99%

Gentlantis
10000 / 9900
990,000 / 19,800
19,800 / 3%

As you can see, Rageopolis has a sports injury epidemic. Around 999,000 Rageopolans get hurt every year playing sports. This makes Rageopolis's politicians look bad when the UN compares their injury rate to Gentlantis's approximately 3%.

Technically, this is not yet an instance of Simpson's paradox since the two games have the same injury rate in both countries. But now, say Rageopolis's government decides they're tired of looking bad compared to Gentlantis and enacts a strict law that required anyone playing either sport to wear a helmet. Lo and behold, the law succeeds beyond anyone's wildest expectation, the Murderball and Tea Party injury rates halve in R

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Conversation about whether LW Moderators should express individual opinions about mod policy - 2019/12/22
by Ruby — 2019-12-23T03:46:31.060Z

Copying over some comments from a different thread so as to continue the conversation here where it's not off-topic.

[Some relevant context: Speaking for myself (re: how the LW2.0 team communicates)]

Bucky wrote on one of my posts:

My other worry about including this in the 2018 review is a claim of what the default should be. If the post claims that nurture culture should be the default, does that then seem like this is how LW should be? This counts even more as the post is by a member of the LW team.

Included in my (Ruby's) reply:

My own thinking on the topic has been enriched by my much greater participation in LW discussion, including discussion around communication styles. I'd begun typing a paragraph here of some of my current thoughts, but probably it's best to hold off till I've thought more at length and am speaking alongside the rest of team. (An update in recent discussions of moderation and conversation norms is that the team should be careful to not confuse people by saying different things individually.)

To which Ben Pace responded:

>but probably it's best to hold off till I've thought more at length and am >speaking alongside the rest of team.

I was gonna leave a comment reminding you that you should always feel free to speak for yourself, and then I hit

>(An update in recent discussions of moderation and conversation norms is >that the team should be careful to not confuse people by saying different >things individually.)

If I read you right, this hasn't been my own update, so I guess I'll tell you to be careful what you say on behalf of the team without checking for consensus ;-) I agree some users have been confused, but the result mustn't be to retreat to only saying consensus things. I might be open to adding more disclaimers or something, but overall I really care that I don't give up the ability to just think for myself out loud on LW on basically all topics relating to LW.

I agree writing about moderation in particular is an unusually careful topic where I want to take extra care to signal what is consensus/actionable and what is me just thinking aloud. But I still stand by that you should share your own thoughts, saying "I" everywhere (I just edited this very comment to own all of my thoughts more), is still pretty great and it'd be bad if you felt the general need to get team consensus.
Freezer Contents
by jefftk — 2019-12-23T02:40:02.002Z

This afternoon I defrosted our chest freezer, which I probably should
have done about two years ago. Aside from having spent a long time
dealing with frost buildup, another downside of waiting so long turned
out to be that by the time I learned that the drain didn't work
it was already out of warranty.

We mostly use the chest freezer for three things:

Buying things when they happen to be on sale.

Having enough space that we can make large ~quarterly shops when
we have access to a car.

Storing leftovers and other cooked-ahead food.

The main tricky part is not losing track of things in it, since the
closer it gets to full the harder it is to find anything.

While I was reorganizing and refilling it I took inventory. This is
what was in it:

Dairy (60lb):

3.4gal ice cream

19lb butter

6lb cheddar

2.5lb shredded mozzarella

8oz cream cheese

Raw meat (48lb):

15lb stew beef

11lb ground beef

8lb bacon

7lb sweet italian sausage

5.7lb chicken thighs

1pt chicken for soup

Ready to defrost and eat (26lb):

7lb hot dogs

6lb ravioli

5lb chicken nuggets

2.8lb fish sticks

1.8lb frozen pizza

1lb cooked mussels

1lb shredded ham

9oz par-baked bread

9oz hotdog buns

2 salmon patties

Vegan stuff (19lb):

5.3lb tofu

3.5lb vegan cheddar shreds

3pt vegan ice cream

2.6lb vegan sausage

2lb earth balance sticks

18oz vegan ice cream sandwiches

1lb tempe

9oz vegan breakfast sausage

Fruit and veg (16lb):

8lb chopped onions

3lb mango

2.5lb raspberries

2lb peas

12oz spinach

Frozen leftovers (13lb):

2pt vegan pasta sauce

2pt beef stew

2pt vegan beans

2lb beef and onions

2lb BBQ pork

1pt vegan peanut ginger soup

1lb vegan cardamon saffron sauce

1pt unlabeled sauce

Other (12lb):

5.4lb puff pastry

1qt bacon grease

2lb shortening

one pie crust

1pt red cooking wine

8oz almonds

1C stew mushrooms

4oz dried basil

This is for a house with six adults (three omnivores, two vegans, one
vegetarian), and two kids (one of which is kind of vegetarian).

Comment via: facebook
Can fear of the dark bias us more generally?
by TurnTrout — 2019-12-22T22:09:42.239Z

There was a long-lasting man-made sound outside my home last night. I couldn't come up with a good explanation for what the sound was or why it was outside my house. My brain naturally promoted the hypothesis that a psychopathic murderer was outside my house making the strange noises. I noticed this was absurd, and predicted that, in the morning, I would find this explanation much less concerning. Sure enough, when I woke up, I thought the whole thing was rather goofy.

Now, supposing there had been a psychopathic murderer outside my house, it wasn't like I was at much more risk at night, since I was planning on staying indoors. This seems like a pretty clear manifestation of nychtophobia: fear of the dark magnifying our fears of being attacked or victimized.

My question is: does this apply more generally? Might we be more risk-averse at night, or otherwise biased?[1] Suppose I plan to soon leave work and walk home along a dimly lit path. Then suppose I make an unrelated decision - am I more likely to be conservative or fearful in weighing that decision, above and beyond the normal effects of having recently considered something slightly distressing?

One study indicated that night owls are actually risk-takers, but there's a lot of confounders there with respect to nychtophobia-related explanations. ↩︎
Decission Theory and Quantum Self-Measurement
by Alan Givré — 2019-12-22T19:16:56.547Z

Most Quantum Mechanics are formulated from a point of view of Causal Decission Theory, as can be seen from the Noncontextuality/counterfactual indefiniteness of Kochen-Specker Theorem.

Now, this creates a chatastrophe when the Observator needs to be analized through a physical lense. That is, Self-Measurement is terribly paradoxical.

Things go so badly that one needs to conclude that the following axiom is incompatible with the Law of Noncontradiction and Quantum Mechanics. According to Frauchiger and Renner:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6143649/

Suppose that agent A has established that

Statement A(i): “I am certain that agent A′, upon reasoning within the same theory as the one I am using, is certain that x = ξ at time t.”

Then agent A can conclude that

Statement A(ii): “I am certain that x = ξ at time t.”

How can we create a Quantum Theory of Self-Measurement that is compatible with Updateless or Functional Decission Theory (I don't know the difference between the two), which I deem more realistic for physical reasons.

I ask you this because I consider you the experts on Decission Theory. The answer to this question may have consecquences on my personal research in biophysical processing of information.

If you need clarification on Quantum Theory and its No-Go theorems to answer this question tell me.

Thank you on advance!!!!