trentmkelly/LessWrong-43k huggingface dataset:
Circling
by Unreal — 2018-02-16T23:26:54.955Z

Circling is a practice, much like meditation is a practice.

There are many forms of it (again, like there are many forms of meditation). There are even life philosophies built around it. There are lots of intellectual, heady discussions of its theoretical underpinnings, often centered in Ken Wilber's Integral Theory. Subcultures have risen from it. It is mostly practiced in the US and Europe. It attracts lots of New Age-y, hippie, self-help-guru types. My guess is that the median age of practicers is in the 30's. I sometimes refer to practicers of Circling as relationalists (or just Circlers).

In recent years, Circling has caught the eye of rationalists, and that's why this post is showing up here, on LessWrong. I can hopefully direct people here who have the question, "I've heard of this thing called Circling, but... what exactly is it?" And further, people who ask, "Why is this thing so ****ing hard to explain? Just tell me!"

You are probably familiar with the term inferential distance.

Well, my friend Tiffany suggested a similar term to me, experiential distance—the gap in understanding caused by the distance between different sets of experiences. Let's just say that certain Circling experiences can create a big experiential distance, and this gap isn't easily closed using words. Much of the relevant "data" is in the nonverbal, subjective aspects of the experience, and even if I came up with a good metaphor or explanation, it would never close the gap. (This is annoyingly Postmodern, yes?)

[Ho ho~ how I do love poking fun at Postmodernism~]

But! There are still things to say, so I will say them. Just know that this post may not feel like eating a satisfying meal. I suspect it will feel more like licking a Pop-Tart, on the non-frosted side.

Some notes first.

Note #1: I'm not writing this to sell Circling or persuade you that it's good. I recommend using your own sense of curiosity, intuition, and intelligence to guide you. I don't want you to "put away" any of your thinking-feeling parts just to absorb what I'm saying. Rather, try remaining fully in contact with your awareness, your sensations, and your thoughts. (I hope this makes sense as a mental move.)

Note #2: The best introduction to Circling is to actually try it. It's like if I tried to explain watching Toy ...
Clarifying the Postmodernism Debate With Skeptical Modernism
by Chris_Leong — 2018-02-16T09:40:30.757Z

One of the greatest challenges with attempting to discuss post-modernism is figuring out exactly what claims are being made. For a start, many of the figures typically associated with post-modernism didn't label themselves as post-modernist, so it isn't as unified as it might have been if it had been an explicit movement, rather than just people who wrote about similar things. Secondly, the roots of post-modernism are in continental philosophy, which has much less of a focus on clearly defining terminology and logic flow than analytical philosophy and so is often harder on the reader. Thirdly, post-modernism tends to be popular among a certain crowd and many in that crowd tend to be less interested in rigour than I would like (think artists, literature majors, sociology students). Due to these factors, it is particularly important to clarify exactly what is being said when talking about post-modernism or otherwise reduce how often people end up talking past each other.

Post-Modernism is usually contrasted with modernism. Modernism isn’t any one thing, but a collection of related beliefs such as a progression of history, optimism about the power of science to answer our questions, a belief in an objective reality that we can know or at least progress towards knowing. It is also associated with certain movements in art, film or architecture, but these are outside the scope of this article. Post-Modernism is posited as a rejection of these assumptions. It may argue that grand narratives a merely a fallacy, that science isn’t truly objective, that our interpretations of the world are unavoidably a product of our culture and perhaps even that there is no objective truth or reality.

Scott Alexander wrote an article that attempted to put post-modernism in terms that rationalists could understand. He later retracted the article based on feedback from people who told him that it wasn’t a good explanation of Post-Modernism. I actually think that the content was good, but that he should have framed it differently. While he did a great job of defending a Modernist (or Rationalist) position that made significant concessions towards post-modernism, the beliefs conveyed in the article weren’t really post-modernism. Nonetheless, this is a useful perspective which deserves its own name, so I will henceforth refer to this as Skeptical Modernism.

More precisely, Skeptic...
Confidence Confusion
by alkjash — 2018-02-16T02:00:00.852Z

“Captain, if you steer the Enterprise directly into that black hole, our probability of surviving is only 2.234%” Yet nine times out of ten the Enterprise is not destroyed. What kind of tragic fool gives four significant digits for a figure that is off by two orders of magnitude?

~Why truth? And…

This post poses a basic question about probabilities that I’m confused about. Insight would be appreciated.

It’s inspired by a quick skim I gave to Proofiness, which argues that precise numbers are a powerful persuasion technique.

The Dinosaur Market

One of the CFAR prediction markets was: A randomly selected participant will correctly name seven real species of dinosaurs.

I made a series of suspect Fermi estimate as follows:

Extrapolating from the current bids, half the participants will not bid in this market. If selected, they will just try to name as many dinosaurs as they can. 20% of participants will be able to.

Half the participants do bid in this market. Among those that bid high on the market, 70% will take the time to study dinosaurs and memorize seven. The other half who bid low will intentionally or unintentionally fail if they’re paying attention. I give them a 10% chance of success.

That comes out to a total of 30%.

There’s a 5% chance of anomalous situations such as one person caring enough to teach people or publicly post dinosaur names. In this case much higher chances of market evaluating to True, say 60%.

I arrived at a probability estimate of .95 * .3 + .05 * .6 = .315.

At this point, I felt obligated to round 31.5% to 30%, and so I bid 30 on the market instead of 31 or 32. Is there a valid reason to do so?

Precision is Confidence

I’ve been focusing on my aversion to report high-precision numbers, even if I believe them to be closer to the truth. When I report 31.5%, I feel more confident than I am.

Teasing out what it means for 31.5% to be more confident 30% the issue is that any number comes with an implicit confidence interval based on the number of significant figures. 30 really means , whereas 31.5 really means .

In the absence of explicitly reporting confidence intervals around every probability estimate, 30 thus feels like a more honest report of my actual beliefs. Despite the simultaneous fact that I would buy at any price less than 31 and sell at any price over 32.

While explicitly reporting confidence intervals solves the issue – I’d rather say inst...
Toward a New Technical Explanation of Technical Explanation
by abramdemski — 2018-02-16T00:44:29.274Z

A New Framework

(Thanks to Valentine for a discussion leading to this post, and thanks to CFAR for running the CFAR-MIRI cross-fertilization workshop. Val provided feedback on a version of this post. Warning: fairly long.)

Eliezer's A Technical Explanation of Technical Explanation, and moreover the sequences as a whole, used the best technical understanding of practical epistemology available at the time* -- the Bayesian account -- to address the question of how humans can try to arrive at better beliefs in practice. The sequences also pointed out several holes in this understanding, mainly having to do with logical uncertainty and reflective consistency.

MIRI's research program has since then made major progress on logical uncertainty. The new understanding of epistemology -- the theory of logical induction -- generalizes the Bayesian account by eliminating the assumption of logical omniscience. Bayesian belief updates are recovered as a special case, but the dynamics of belief change are non-Bayesian in general. While it might not turn out to be the last word on the problem of logical uncertainty, it has a large number of desirable properties, and solves many problems in a unified and relatively clean framework.

It seems worth asking what consequences this theory has for practical rationality. Can we say new things about what good reasoning looks like in humans, and how to avoid pitfalls of reasoning?

First, I'll give a shallow overview of logical induction and possible implications for practical epistemic rationality. Then, I'll focus on the particular question of A Technical Explanation of Technical Explanation (which I'll abbreviate TEOTE from now on). Put in CFAR terminology, I'm seeking a gears-level understanding of gears-level understanding. I focus on the intuitions, with only a minimal account of how logical induction helps make that picture work.

Logical Induction

There are a number of difficulties in applying Bayesian uncertainty to logic. No computable probability distribution can give non-zero measure to the logical tautologies, since you can't bound the amount of time you need to think to check whether something is a tautology, so updating on provable sentences always means updating on a set of measure zero. This leads to convergence problems, although there's been recent progress on that front.

Put another way...
Two Types of Updatelessness
by abramdemski — 2018-02-15T20:19:54.575Z

Cross-posted.

Just a small note which I’m not sure has been mentioned anywhere else:

It seems like there are two different classes of “updateless reasoning”.

In problems like Agent Simulates Predictor, switching to updateless reasoning is better for you in the very situation you find yourself in. The gains accrue to you. You objectively achieve higher expected value, at the point of decision, by making the decision from the perspective of yourself long ago rather than doing what seems higher EV from the current perspective.

In problems like counterfactual mugging, the gains do not accrue to the agent at the point of making the decision. The increase in expected value goes to other possible selves, which the decision-point self does not even believe in any more. The claim of higher EV is quite subjective; it depends entirely on one’s prior.

For lack of better terms, I’ll call the first type all-upside updatelessness; the second type is mixed-upside.

It is quite possible to construct decision theories which get all-upside updateless reasoning without getting mixed-upside. Asymptotic decision theory was one.

On the other hand, it seems unlikely that any natural proposal would get mixed-upside without getting the all-upside cases.

Policy selection

, for example, automatically gets both types (to the limited extent that it enables updatelessness reasoning).

Nonetheless, I find it plausible that one wants two different mechanisms to get the two different kinds. It seems to me that one can handle all-upside cases in a more objective way, getting good overall guarantees. Mixed-upside cases, on the other hand, require more messiness and compromise, as in the policy selection proposal. So, it could be beneficial to combine a mechanism which does perfectly for all-upside cases with a mechanism that provides some weaker guarantee for mixed-upside.
Subduing Moloch
by Teja Prabhu — 2018-02-14T23:34:20.601Z

If rationality is systemized winning, then the diaspora of rationalists should be the most powerful group in the world. One way to increase individual and group power is to increase cooperation among rational agents.

As a starting point, the obvious way to increase cooperation is to increase the frequency of high bandwidth communication among the agents. Imagine the existence of an app that each week would randomly pair you with another rationalist. You would converse with the person for an hour everyday (for example, you could spend 30 mins each discussing your respective days and how to optimize it). Then if you repeat the process for a year, then you would get to know 52 people. In 10 years, you would know 520 people. If you connect particularly well with someone, you can continue talking with them elsewhere after the week is over.

The purpose of this is to develop a real community of people with the shared mission of optimizing the world. This is admittedly a pretty weird idea, but once there is a sufficiently high density of edges, then the group as a whole can act as an "super-agent" when the need arises.

While the benefits of forming such a community will initially be restricted to mundane things like job references and entertainment, it can eventually be used to resolve multi-player prisoner's dilemmas of the kind described by SlateStarCodex:

Bostrom makes an offhanded reference of the possibility of a dictatorless dystopia, one that every single citizen including the leadership hates but which nevertheless endures unconquered. It’s easy enough to imagine such a state. Imagine a country with two rules: first, every person must spend eight hours a day giving themselves strong electric shocks. Second, if anyone fails to follow a rule (including this one), or speaks out against it, or fails to enforce it, all citizens must unite to kill that person. Suppose these rules were well-enough established by tradition that everyone expected them to be enforced.

So you shock yourself for eight hours a day, because you know if you don’t everyone else will kill you, because if they don’t, everyone else will kill them, and so on. Every single citizen hates the system, but for lack of a good coordination mechanism it endures. From a god’s-eye-view, we can optimize the system to “everyone agrees to stop doing this at once”, but no one within the system is

...
Active vs Passive Distraction
by squidious — 2018-02-14T22:14:02.064Z

When life gets difficult, it can often become tempting to distract yourself from your own thoughts and feelings. Loved ones may scold us for this, telling us that we should confront our feelings, because distracting ourselves doesn't accomplish anything. However, distraction is an important part of distress tolerance. Imagine Jill, a young woman who, in typical romantic comedy fashion, gets fired and dumped on the same day. Sure, distracting herself isn't going to help her find a new job, but binge-watching her favorite TV series would give Jill time to let her emotions around the problem cool down before she decides to start working on it.

Of course, different kinds of people may require different kinds of distraction. For Jill, a more passive distraction like watching TV is perfect; she may not have the energy to do much else. However, her now-ex Bob is worried about how awkward their break-up is going to make things with their mutual friend group. If he sat down to watch TV, he would still be worrying about it. Bob needs a distraction that he can throw himself into, something that takes so much effort and focus that he can't spend any time worrying. So instead, he decides to pick up his guitar and practice a new song he's been trying to learn. Bob opts for a more active distraction.

The examples above not only show the difference between passive and active distraction, but also how to match what kind of distraction you need to your mood. For a lot of people, depression makes it hard to do things, so a more passive distraction may be preferred. Jill would not have had the energy to practice an instrument while depressed. On the other side, anxiety often manifests as a sort of nervous energy, which can easily be redirected. Of course, this isn't the case for everyone. Some people find anxiety paralyzing, so they may prefer a passive distraction despite being anxious. The important thing here is that the activeness and passivity of your distraction match your energy level.

What some people find to work as a distraction, others might find works better as emotional regulation. Maybe the real reason Jill didn't want to play music is that it wouldn't distract her at all, and would instead remind her of Bob even more! A few days after the break-up, Jill may still be feeling sad and missing him, so she sits down at her piano and pl...
More precise regret bound for DRL
by Vanessa Kosoy — 2018-02-14T11:58:31.000Z

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We derive a regret bound for DRL reflecting dependence on:

Number of hypotheses

Mixing time of MDP hypotheses

The probability with which the advisor takes optimal actions

That is, the regret bound we get is fully explicit up to a multiplicative constant (which can also be made explicit). Currently we focus on plain (as opposed to catastrophe) and uniform (finite number of hypotheses, uniform prior) DRL, although this result can and should be extended to the catastrophe and/or non-uniform settings.

Appendix A contains the proofs, Appendix B recalls a few lemmas we need from previous essays.

##Results

First, we briefly recall some properties of Markov chains.

#Definition 1

Consider S a finite set and T:Sk→S. We say that k∈N+ is a period of T when there is s∈S an essential state of T (that is, T∞(s∣s)>0) s.t. k is its period, i.e. k=gcd{n∈N+∣Tn(s∣s)>0}. We denote PT the set of periods of T.

The following is a corollary of the Perron-Frobenius theorem which we give without proof. [I believe this is completely standard and would be grateful to get a source for this which treats the reducible case; of course I can produce the proof but it seems redundant.]

#Proposition 1

Consider S a finite set and T:Sk→S. Then, there are F∈(0,∞), λ∈(0,1), ζ:Sk→PT and ξ:S×PTk→S s.t. for any s∈S

∀k∈PT:Tkξ(s,k)=ξ(s,k)

∀n∈N:dtv(Tn(s),Ek∼ζ(s)[Tnξ(s,k)])≤Fλn

For the purpose of this essay, we will use a definition of local sanity slightly stronger than what previously appeared as "Definition 4." We think this strengthening is not substantial, but also the current analysis can be generalized to the weaker case by adding a term proportional to the 2nd derivative of V (or the 2nd moment of the mixing time). We leave out the details for the time being.

We will use the notation AωM(s):=⋂k∈NAkM(s).

#Definition 2

Let υ=(μ,r) be a universe and ϵ∈(0,1). A policy σ is said to be locally ϵ-sane for υ when there are M, S and UM⊆SM (the set of uncorrupt states) s.t. υ is an O-realization of M with state function S, S(λ)∈UM and for any h∈hdomμ, if S(h)∈UM then

i. ∀a∈suppσ(h):TM(UM∣S(h),a)=1

ii. suppσ(h)⊆A0M(S(h))

iii. ∃a∈AωM(S(h)):σ(a∣h)>

...
Catastrophe Mitigation Using DRL (Appendices)
by Vanessa Kosoy — 2018-02-14T11:57:47.000Z

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These are Appendices B and C for the essay Catastrophe Mitigation Using DRL. They appear in a separate post because of a length limit in the website.

##Appendix B

Given p=(a,o)∈A×O, we denote pA:=a, pO:=o.

#Proposition B.1

Consider a universe υ=(μ,r) which an O-realization of an MDP M with state function S, a stationary policy π∗:SMk→A, an arbitrary I-policy π0 and some γ∈(0,1). Then,

EUπ∗Sυ(γ)−EUπ0υ(γ)=∞∑n=0γnEx∼μ⋈π0[VMπ∗(S(x:n),γ)−QMπ∗(S(x:n),xAn,γ)]

#Proof of Proposition B.1

For the sake of encumbering the notation less, we will omit the parameter γ in functions that depend on it. We will use S implicitly, i.e. given F a function on SM and h∈hdomμ, F(h):=F(S(h)). Finally, we will omit Mπ∗, using the shorthand notations V:=VMπ∗, Q:=QMπ∗.

For any x∈hdomωμ, it is easy to see that

EUπ∗Sυ=V(λ)=∞∑n=0γn(V(x:n)−γV(x:n+1))

Ur(x)=(1−γ)∞∑n=0γnr(x:n)

EUπ∗Sυ−Ur(x)=∞∑n=0γn(V(x:n)−(1−γ)r(x:n)−γV(x:n+1))

EUπ∗Sυ−Ur(x)=∞∑n=0γn(V(x:n)−Q(x:n,xAn)+Q(x:n,xAn)−(1−γ)r(x:n)−γV(x:n+1))

Taking expected value over x, we get

EUπ∗Sυ−EUπ0υ=∞∑n=0γn(Eμ⋈π0[V(x:n)−Q(x:n,xAn)]+Eμ⋈π0[Q(x:n,xAn)−(1−γ)r(x:n)−γV(x:n+1)])

It is easy to see that the second term vanishes, yielding the desired result.

#Proposition B.2

Consider some τ∈(0,∞), T∈N+, a universe υ=(μ,r) that is an O-realization of M with state function S, a stationary policy π∗:SMk→A and an arbitrary I-policy π0:(A×O)∗k→A. For any n∈N, let π∗n be an I-policy s.t. for any h∈hdomμ

π∗n(h):={π0(h) if |h|<nTπ∗(S(h)) otherwise

Assume that

i. For any h∈hdomμ suppπ0(h)⊆A0Mπ∗(S(h))

ii. For any s∈SM and γ∈(0,1) ∣∣∣dVMπ∗(s,γ)dγ∣∣∣≤τ

Then, for any γ∈(0,1),

EUπ∗Sυ(γ)−EUπ0υ(γ)≤(1−γ)∞∑n=0T−1∑m=0γnT+m(Ex∼μ⋈π∗n[r(x:nT+m)]−Ex∼μ⋈π0[r(x:nT+m)])+2τγT(1−γ)1−γT

#Proof of Proposition B.2

For the sake of encumbering the notation less, we will use S implicitly, i.e. given F a function on SM and h∈hdomμ, F(h):=F(S(h)). Also, we will omit Mπ∗, using the shorthand notations V:=VMπ∗, Q:=QMπ∗.

By Proposition B.1, for any l∈N

EUπ∗υ(γ)−EUπ∗lυ(γ)=∞∑n=0γnEx∼μ⋈π∗l[V(x:n,γ)−Q(x:n,xAn,γ)]

π∗l coincides with π∗ after lT, therefore the corresponding expected values vanish.

EUπ∗υ(γ)−EUπ∗lυ(γ)=lT−1∑n=0γnEx∼μ⋈π0[V(x:n,γ)−Q(x:n,xAn,γ)]

Subtracting the

...
The Principled Intelligence Hypothesis
by KatjaGrace — 2018-02-14T01:00:00.939Z

I have been reading the thought provoking Elephant in the Brain, and will probably have more to say on it later. But if I understand correctly, a dominant theory of how humans came to be so smart is that they have been in an endless cat and mouse game with themselves, making norms and punishing violations on the one hand, and cleverly cheating their own norms and excusing themselves on the other (the ‘Social Brain Hypothesis’ or ‘Machiavellian Intelligence Hypothesis’). Intelligence purportedly evolved to get ourselves off the hook, and our ability to construct rocket ships and proofs about large prime numbers are just a lucky side product.

As a person who is both unusually smart, and who spent the last half hour wishing the seatbelt sign would go off so they could permissibly use the restroom, I feel like there is some tension between this theory and reality. I’m not the only unusually smart person who hates breaking rules, who wishes there were more rules telling them what to do, who incessantly makes up rules for themselves, who intentionally steers clear of borderline cases because it would be so annoying to think about, and who wishes the nominal rules were policed predictably and actually reflected expected behavior. This is a whole stereotype of person.

But if intelligence evolved for the prime purpose of evading rules, shouldn’t the smartest people be best at navigating rule evasion? Or at least reliably non-terrible at it? Shouldn’t they be the most delighted to find themselves in situations where the rules were ambiguous and the real situation didn’t match the claimed rules? Shouldn’t the people who are best at making rocket ships and proofs also be the best at making excuses and calculatedly risky norm-violations? Why is there this stereotype that the more you can make rocket ships, the more likely you are to break down crying if the social rules about when and how you are allowed to make rocket ships are ambiguous?

It could be that these nerds are rare, yet salient for some reason. Maybe such people are funny, not representative. Maybe the smartest people are actually savvy. I’m told that there is at least a positive correlation between social skills and other intellectual skills.

I offer a different theory. If the human brain grew out of an endless cat and mouse game, what if the thing we traditionally think of as ‘intelligence’ grew out of being th...