trentmkelly/LessWrong-43k huggingface dataset:
The First Person And The Physical Person
by dadadarren — 2022-01-10T19:47:51.325Z

This is another attempt to promote my approach to anthropic paradoxes. I framed the argument differently hopefully making it more clear. Please refer to my website for more.

What "I" Means

In the strict indexical sense, "I" just means the first person. However we also often interpret it as the physical person uttering the word and usually equate the two meanings, "I am this physical person" after all. But there is a caveat. The equivalency is bound by the perspective.

The first person meaning of "I" is restricted to its own viewpoint, from other perspectives only the physical meaning can be used. If I hear you say "I'm hungry", to me the only correct way of interpreting it would be the physical person "[insert reader name] is hungry", not that "I am hungry" (as in "dadadarren is hungry"). We do this sort of transcoding naturally all the time.

What's more subtle is this should also apply to "god's eye view" (or "view from nowhere" if you prefer). If we try to be objective and reason from a god's eye view, then we shouldn't be using the first-person "I" at all. For it would only refer to the imaginary impartial observer, not any particular person.

But we keep using the two meanings interchangeably in anthropic problems. Effectively jumping back and forth between our natural viewpoints and the god's eye view. This is the cause of paradoxes and why different camps have trouble communicating.

Is "I exist" Meaningful Evidence?

One major contention in anthropics is whether or not "I exist" can be used as evidence to support certain theories. (Which exact theory, such as more observers, big universe, or "fine-tuning" is a separate matter. ) One camp suggests it does not support any theory because "I would always find myself exist". The other camp disagrees arguing that is claiming "My existence is guaranteed to happen". Which is obviously untrue. So "I exist" is valid evidence. Both camps are unconvinced by the opponent's argument.

The key difference between the two camps is they are using different meanings of "I". When the former argues "I would always find myself exist", they are using the strictly indexical, first-person meaning of "I". i.e. No matter whose perspective we choose to take, we will always conclude the first person exists. It does not have any specific physical person in mind.

On the contrary, when the opponents say 'I exi...
Forecasting Newsletter: December 2021
by NunoSempere — 2022-01-10T19:35:40.815Z

Highlights

Polymarket’s future is uncertain after it settled with the CFTC for $1.4M
Astral Codex Ten gives out $40k to forecasting projects
Many people, including Mathew Yglesias, write predictions for 2022.
Eli Lifland writes the reference piece on bottlenecks to impactful forecasting
Google reveals the existence of a gigantic new internal prediction market
A new forecasting platform appears, Manifold Markets

Index

Prediction Markets & Forecasting Platforms
Long Content
Blog Posts
In The News

You can sign up for this newsletter on substack, or browse past newsletters here. If you have a content suggestion or want to reach out, you can leave a comment or find me on Twitter. A big hat tip goes to Nathan Young and Clay Graubard for comments and suggestions on this edition.

Prediction Markets & Forecasting Platforms

Polymarket

The US Commodity Futures Trading Commission (CFTC) has fined Polymarket $1.4M (a). For reference, Polymarket's seed funding amounted to $4M (a) and were in talks for another round at a nearly $1B valuation (a) prior to the investigation.

The order requires that Polymarket pay a $1.4 million civil monetary penalty, facilitate the resolution (i.e. wind down) of all markets displayed on Polymarket.com that do not comply with the Commodity Exchange Act (CEA) and applicable CFTC regulations, and cease and desist from violating the CEA and CFTC regulations, as charged.

With this, Polymarket's future seems now very uncertain. The Polymarket team has been mostly silent, though it recently released an update (a) as a Google doc, which promised that they were just "getting started".

To quantify this uncertainty, I asked a more experienced prediction market trader—who wishes to remain anonymous—for his probability estimate that Polymarket would be "pretty much dead". This was operationalized as there being no new markets with more than $100k in volume by November 2022. His guess ranged from 30% to 50% that it'd in fact be dead.

This is terrible news. Polymarket has recently been one of the very few real-money markets where one could find highly liquid markets on things of actual importance, like the covid pandemic. I don't tire of mentioning this ¡2008! piece (a) by several Nobel prize winners and other notable figures urging the CFTC to essentially allow these markets to exist.

[As an aside, I'll elaborate a bit on the method of elicitation, because I thought...
Activated Charcoal for Hangover Prevention: Way more than you wanted to know
by Maxwell Peterson — 2022-01-10T19:26:54.907Z

Activated charcoal is charcoal that has been heated up a whole lot and then washed really hard, by water or acid. This process is what "activates" it, and activating it increases the surface area by a lot. I think it prevents hangovers.

I won't spend too much time in this post arguing that activated charcoal works. Instead, I'll mostly take for granted that it does, then take a tour of the various things that might cause hangovers, stopping at each to look at why activated charcoal might or might not be likely to reduce them. So even if you're sure activated charcoal is just a hokey health craze thing I've tricked myself into believing, this post still has lots of interesting hangover science you might not have heard about.

A quick warning
Some sellers of activated charcoal say to take it every day. I don't think there's any reason to do this, and some people say it's bad to. This is because it's a great absorber - that's why it helps with hangovers! - but it's possible it absorbs things you want to keep, like nutrients from food, so there's a theory that daily use could result in nutrient deficiency. This post advises taking activated charcoal only on nights of heavy drinking.

Also, if you take medications, activated charcoal could make them less effective, by absorbing the active ingredient; this could be pretty bad, depending on how important the medications are to your health.
Don't take activated charcoal every day. If you take important medicines, do solid research or ask a professional before taking any charcoal.

I used to suffer vicious hangovers pretty often - usually a headache and sometimes nausea - after nights of drinking with friends. This past spring, I started taking two 520mg capsules of activated charcoal before going to bed on these nights. Since then, I've had maybe 26 nights out with the level of drinking I'd expect to result in hangover, and had a headache twice and nausea just once. (Tiredness is still common). Based on past experience, without activated charcoal I would have had headaches 12-18 of these times and nausea 4-10 times.

I recently convinced a friend to try a capsule before going to bed after a late night, after she'd insisted for months that there was no way this would work. The next morning she sent me a rave review, saying she'd expected to feel terrible after the number of drinks she'd had, but just felt a li...
Tips for productively using short (<30min) blocks of time
by just_browsing — 2022-01-10T18:05:16.008Z

Here's a common situation I find myself in: it's 1:30pm and I have a commitment at 2pm. I'd like to spend the next 30 minutes working, but all of the tasks I need to complete will take much more than 30 minutes to complete. I think to myself: "By the time I get set up to do this task (context switching etc), it will be basically time for my 2pm meeting, so I'll have mostly wasted the last 30 minutes."

My primary fix for this is reserving contiguous blocks in my schedule for deep work. However, I do not always have control over my schedule.

What are tips for effectively using short (<30min) blocks of time?

(Feel free to redefine "short" if you perceive "short" in a different way.)
Critiquing Scasper's Definition of Subjunctive Dependence
by Heighn — 2022-01-10T16:22:56.355Z

Before we get to the main part, a note: this post discusses subjunctive dependence, and assumes the reader has a background in Functional Decision Theory (FDT). For readers who don't, I recommend this paper by Eliezer Yudkowsky and Nate Soares. I will leave their definition of subjunctive dependence here, because it is so central to this post:

When two physical systems are computing the same function, we will say that their behaviors “subjunctively depend” upon that function.

So, I just finished reading Dissolving Confusion around Functional Decision Theory by Stephen Casper (scasper). In it, Casper explains FDT quite well, and makes some good points, such as FDT not assuming causation can happen backwards in time. However, Casper makes a claim about subjunctive dependence that's not only wrong, but might add to confusion around FDT:

Suppose that you design some agent who enters an environment with whatever source code you gave it. Then if the agent’s source code is fixed, a predictor could exploit certain statistical correlations without knowing the source code. For example, suppose the predictor used observations of the agent to make probabilistic inferences about its source code. These could even be observations about how the agent acts in other Newcombian situations. Then the predictor could, without knowing what function the agent computes, make better-than-random guesses about its behavior. This falls outside of Yudkowsky and Soares’ definition of subjunctive dependence, but it has the same effect.

To see where Casper goes wrong, let's look at a clear example. The classic Newcomb's problem will do, but now, Omega isn't running a model of your decision procedure, but has observed your one-box/two-box choices on 100 earlier instances of the game - and uses the percentage of times you one-boxed for her prediction. That is, Omega predicts you one-box iff that percentage is greater than 50. Now, in the version where Omega is running a model of your decision procedure, you and Omega's model are subjunctively dependent on the same function. In our current version, this isn't the case, as Omega isn't running such a model; however, Omega's prediction is based on observations that are causally influenced by your historic choices, made by historic versions of you. Crucially, "current you" and every "historic you" therefore subjunctively depend on your decision proced...
The IHME Report
by Zvi — 2022-01-10T15:50:01.338Z

An IHME report came out over the weekend. I was pleasantly surprised by it contents. Its conclusions and projections broadly match what I said in the last Omicron post, with only relatively minor obvious nonsense, and seemed worth their own post to break down.

Headline Takeaways

Our models for the United States suggest that infections may be currently peaking at 6 million a day, with varied peaks by state. We expect more than 50% of the US population will be infected with Omicron in the next 6 weeks. The infection-detection rate (IDR) is declining, although shortages of testing may lead to more rapid decreases in the IDR than we currently model. Nevertheless, we expect reported cases to exceed 1 million a day, peak by the third week of January, and then decline sharply.

I too expect reported cases to peak during the third week of January (to be clear, when I say we will peak on 19 January, I mean cases detected on 19 January, not infections that happen on 19 January. If counting from initial infections, I’d have said 16 January, but it’s hard to ever know what the actual lag was there.)

Once the peak arrives, a sharp decline is to be expected shortly thereafter, although I still expect cases to remain elevated (above pre-Omicron levels) for several months.

Note that ‘more than 50%’ sounds like the kind of thing one says when one does not want to make a precise prediction, but there are graphs later on.

Hospitalizations will increase to a peak that may be twice as high as last winter. These figures, however, include incidental admissions. Because the prevalence of Omicron infection is so high, many individuals hospitalized for other conditions will have asymptomatic infections. Incidental admissions may exceed 50% of total COVID-19 admissions in some states. Daily deaths will increase but remain below 2,000 a day, peaking by the end of the month. This means the peak of deaths will remain below the summer Delta surge and well below the peak last winter.

That sounds like a best case scenario. If hospital admissions peak at twice last winter, but half of them are incidental, then things won’t be substantially worse than last winter. We survived last winter. Deaths peaking below 2,000 per day means they won’t even double once, and the peak will come within a few weeks. Expecting them to peak by month’s end seems wrong given the historical lag times, ...
Uncontroversially good legislation
by braces — 2022-01-10T02:26:04.743Z

Say you’re fortuitously seated next to a senator, state assembly member, or city supervisor at a wedding. You’ve got to talk about something, so you figure it wouldn’t be rude to mention some legislative issue you’re passionate about.

What would the legislation be?

I’m curious about almost definitely good laws that Republicans, Democrats, and Independents could all get behind. This could be at the local, state, or federal level although it seems as though there might be more obvious reforms in smaller governments. (I searched around for this here and on EA forums and didn’t find any, but would love to know about any similar lists.)

Here’s a few I could think of. These are debatable and surely reflect my own biases and limited knowledge.

Price transparency: Airlines are required by the

Full Fare Advertising rule

to show the all-in cost whenever they advertise prices. Why not the same for hotels and food delivery, where the price jumps at the last page from taxes and fees? This would better allow businesses to compete on price rather than deception.
Let us buy glasses: We can’t buy glasses or contact lenses if our eye prescription is over 1-2 years old. This means that every 1-2 years, glasses-wearers need to pay $200 to optometrists for the slip of paper (and stinging eyeballs). Seems like it’s probably a racket and the benefit from detecting the odd eye cancer is outweighed by the costs, although see the debate

here

. (Edit: it's actually not that hard to get around this, at least for glasses. Thanks Dustin.)
Tax filing in the US should be more automated: This one is well-known (see

Planet Money episode

) and seems like another case of common sense vs. lobbyists. (Speaking of Planet Money, another candidate is repealing the

Jones Act

.)

What are some others?
Omicron - How does it change Covid risk and what should we do about it?
by jackc — 2022-01-09T23:13:06.084Z

[Crossposted from https://firstsigma.substack.com/p/omicron with a few small updates to the estimates from the last couple days]

My thoughts on how Omicron affects Covid risk and what we should do about it. In particular, I wanted to address some common questions I've seen along the lines of "since it's less severe shouldn't I worry less?" and "is it so transmissible that everyone's going to get it, and if so is there any point in trying to avoid it?"

Summary

tl;dr: it's worse than Delta and not as bad as during the 2020 surges (since that was before vaccines). Your risk of getting infected and hospitalized has likely gone up by over 5x since before the surge (that’s accounting for Omicron being less severe). I think we should take stronger protection measures during January in particular when the risk is highest and treatment most strained.

How much does Omicron increase the risk to me?

Your Covid infection risk for the same activity has already gone up by over 10x in most regions (mostly because Covid prevalence has gone up by that much, and also because of increased transmissibility) and your risk of severe illness has gone up by over 5x (see next bullet point). And the risk will continue to increase until the surge peaks.

How severe is Omicron?

It's estimated to be less severe than Delta (~50% less), but similar or more severe than Alpha (Delta was about 2x more severe than Alpha). Note that a lot of the apparent reduction in severity is because more of Omicron's cases are breakthrough infections, which are less severe.
And the overall chance of getting hospitalized with Omicron is still much higher because of the much higher rate of infections: if we estimate an Omicron infection as 50% less likely to cause a hospitalization, and Covid prevalence is 10x higher, then your hospitalization risk is 10x * 50% = 5x higher than before.

Will Omicron burn through the US and then be over quickly?

I think this is roughly 50% likely, I definitely wouldn't count on it. I think the main other possibility is a shape similar to Delta in the US - a quick peak, then a slow decline into an elevated plateau. I think we'll reach the peak quickly, the more important question is what the shape of the pandemic looks like after the peak.

Will Omicron infect most of the population? If yes, is it even worth it to try to avoid it?

I think it's worth taking low and moderate cost efforts to avo

...
Use Normal Predictions
by Jan Christian Refsgaard — 2022-01-09T15:01:44.934Z

Making predictions is a good practice, writing them down is even better.

However, we often make binary predictions when it is not necessary, such as

Biden win popular vote: 91%

Danish COVID deaths above 10.000 by January 1. 2022: 84%

Alternatively, we could make predictions from a normal distribution, such as ('~' means ‘comes from’):

Biden’s popular vote ~ N(0.54, 0.03)

Danish COVID deaths by January 1. 2022 ~ N(15,000, 5,000)

While making "Normal" predictions seems complicated, this post should be enough to get you started, and more importantly to get you a method for tracking your calibration, which is much harder with dichotomous predictions.

The key points are these:

Predicting from a normal is surprisingly easy.

Getting an actionable number for how over/under confident you are requires only simple math!

The normal distribution carries more information than the Bernoulli (binary outcome such as coins) and will therefore give you more information to act on!

Things this post will answer:

How do I make a normal prediction?

Why do I want to do this?

How do I track my calibration?

Quick recap about the normal distribution

The normal distribution is usually written as N(μ,σ) has 2 parameters:

a location parameter μ (pronounced mu) which is both the most likely and the average value

a scale parameter σ (pronounced sigma) which captures uncertainty, high σ implying high uncertainty

the 68-95-99.7 rule states that:

68% of your predictions should fall in μ±1σ

95% of your predictions should fall in μ±2σ

99.7% of your predictions should fall in μ±3σ

50% of the predictions should fall within 0.674≈23σ, which can be used as a quick spot check.

The last piece of Normal trivia we need to know is this: the variance of the Normal is simply σ2:

Var(N(μ,σ))=σ2

How to make predictions

To make a prediction, there are two steps. Step 1 is predicting μ. Step 2 is using the 68-95-99.7 rule to capture your uncertainty in μ.

I tried to predict Biden’s national vote share in the 2020 election. From the polls, I got 54% as a point estimate, so that seemed like a good guess for μ. For σ I used the 68-95-99.7 rule and tried to see what that would imply for different values of σ. Here is a table for 2-5%

Intervals
68%
95%
99.7%

σ=2
52-56%
50-58%
48-60%

σ=3
51-57%
48-60%
45-63%

σ=4
50-58%
46-62%
42-66%

σ=5
49-59%
44-64%
39-69%

σ=2 implies a 97.5% (95% int...
A counterargument that isn't
by dominicq — 2022-01-09T09:50:52.269Z

(cross-posted from my blog)

Let's say that you're in a discussion, and it goes something like this:

We should do institute regulatory measures, like taxes, to inhibit the growth of the economy so that we can slow down or stop climate change.

That makes sense if you think that climate change is the bigger of the possible threats, but it probably isn't. Growing our economy is the fastest way to get us over a certain technological capability threshold, which means that we're that much more equipped to work on even more pressing issues than climate change (like aging, or S-risks).

That makes sense if you think that economic growth is what's necessary, but just because there's a strong historical correlation, that doesn't guarantee that more economic growth will lead to more revolutionary discoveries. You could very well imagine a world where you have diminishing incremental improvements on the new iPhone, or some such. All the while, you're ignoring possible other avenues of governance that would get us over that same technological threshold (e.g. certain forms of technocracy).

That makes sense if you think that there's any way that something that is not modern-day capitalism can produce the same level of output as modern-day capitalism. And even ignoring the practicalities of such an endeavor (you'd essentially have to make the entire world switch over to a new paradigm, which is in practical terms extremely difficult), a) the game theory doesn't seem to be there, and b) the tail risks seem to be there. Meaning, it's uncertain that there actually is some arrangement in which parties, as they exist today, would transact among each other and raise the overall net value/profit/whatever for society in general - and that such an arrangement isn't regulated market capitalism that we're running on today. Moreover, if you do in fact find some game-theoretical arrangement that would work better than what we have today, there's still the question of unknown unknowns, of tail risks. This is the problem of things sounding good "on paper", but then you miss something important and/or tacit, something that you didn't think about, and that fundamentally changes everything. Returning to the original claim, if we try to inhibit the economy, sure we might improve our environment in the short term, but look at what you're doing in the long term: you're preventing the unlocking of

...
Total compute available to evolution
by redbird — 2022-01-09T03:25:54.149Z

I’m looking for estimates of the total compute available to evolution:

Total number of cell divisions

Total number of times a DNA nucleotide was transcribed to RNA

Total number of times an RNA codon was translated to an amino acid

Total number of base pairs in all genomes

Total entropy of the set of all genomes

I’d like to identify other significant sources of compute available to evolution (epigenome? lateral gene transfer? interspecies communication?) and how to quantify them.

I’m looking for estimates of total compute over all 4 billion years of Earth life, and also how compute varied with time.

Grateful for any leads!