rossry

Karma: 139

rossry 12 Jun 2019 8:05 UTC
3 points

on: Get Rich Real Slowly
What’s up with “FDIC insurance up to $1,000,000”? Wikipedia claims that FDIC insurance only covers $0.25mln/bank unless I have a joint account, retirement account, or some kind of legal entity which I’m not.

rossry 7 Jun 2019 12:46 UTC
4 points

in reply to: Gurkenglas's comment on: Fractional Reserve Charity
I don’t think that there is off-the-shelf insurance for “I lose my job (prospects) or otherwise choose to have lower lifetime earnings, in some way I did not foresee.”

It would be confusing to me if most EAs had equity investments they could not afford to bear a crash loss in, especially those involved in an emergency fund scheme. Why add market exposure to the portfolio of donations + scheme membership + liquid cash? (Especially, why as market exposure you expect other scheme participants to share?)

That said, it is possible to buy insurance against a market crash. Probably not as a centralized service.

rossry 26 May 2019 22:41 UTC
3 points

in reply to: Chris G's comment on: 0.999...=1: Another Rationality Litmus Test

So shouldn’t that inequality apply to 0.AAA… (base eleven) and 0.999… (base ten) as well? (A debatable point maybe).

Not debatable, just false. Formally, the fact that $x_{k} < y_{k}$ for all $k$ does not imply that ${lim}_{k \to \infty} x_{k} < {lim}_{k \to \infty} y_{k}$ .

If I were to poke a hole in the (proposed) argument that 0.[k 9s]{base 10} < 0.[k As]{base 11} (0.9<0.A; 0.99<0.AA;...), I’d point out that 0.[2*k 9s]{base 10} > 0.[k As]{base 11} (0.99>0.A; 0.9999>0.AA;...), and that this gives the opposite result when you take $k \to \infty$ (in the standard sense of those terms). I won’t demonstrate it rigorously here, but the faulty link here (under the standard meanings of real numbers and infinities) is that carrying the inequality through the limit just doesn’t create a necessarily-true statement.

0.111...{binary} is 1, basically for the Dedekind cut reason in the OP, which is not base-dependent (or representation-dependent at all) -- you can define and identify real numbers without using Arabic numerals or place value at all, and if you do that, then 0.999...=1 is as clear as not(not(true))=true.

rossry 22 May 2019 23:09 UTC
6 points

in reply to: Davidmanheim's comment on: No Really, Why Aren’t Rationalists Winning?
I think your comment is unnecessarily hedged—do you think that you’d find much disagreement among LWers who interact with FHI/GMU-Econ over whether people there sometimes (vs never) fail to do level-one things?

I think I understand the connotation of your statement, but it’d be easier to understand if you strengthened “sometimes” to a stronger statement about academia’s inadequacy. Certainly the rationality community also sometimes fails to do even the obvious, level-one intelligent character things to enable them to achieve their goals—what is the actual claim that distinguishes the communities?

rossry 22 May 2019 12:30 UTC
3 points

in reply to: TAG's comment on: No Really, Why Aren’t Rationalists Winning?
I’m confused; it seems like evidence against the claim that you can get arbitrary amounts of value out of learning generic rationality skills, but I don’t see it as “devastating” to the claim you can get significant value, unless you’re claiming that “spent years learning all that stuff, and now do it as a day job; some of them 16 hours a day” should imply only a less-than-significant improvement. Or am I missing something here?

rossry 29 Apr 2019 14:30 UTC
3 points

in reply to: Virgil Kurkjian's comment on: Counterspells
cf. my comment cousin to this one; I misunderstood what the term was pointing at at first, though I stand by my complaint that that’s a problem with the term.

rossry 28 Apr 2019 14:34 UTC
3 points

in reply to: Slider's comment on: Counterspells
Thanks; I legitimately misunderstood at first read whether “counterspell” was intended to apply to the invocations thrown out by bad arguers or the concise and specific distillations the OP is presenting for use. On re-read, I agree that it’s supposed to be a set of useful tools.

I remain convinced of the specific claim that “counterspell” is bad jargon (though I don’t think it’s good practice to cite my own confusion too strongly; the incentives there aren’t great). I agree that MtG″s paradigm where more general counterspells are more expensive seems like a good fit for thinking about rhetorical (and perhaps epistemic) tactics, though I reiterate that that’s not how they work in many other settings, and that ambiguous baggage is worse than no baggage for this sort of thing. The question of whether identifying counterspells with magic is supposed to be a positive or negative association is additional gratuitous confusion—I think your claim that the magic metaphor implies they don’t work is wrong, but I’m not 85% sure.

rossry 28 Apr 2019 4:40 UTC
16 points

on: Counterspells
Strong approval of the overall goal of the post, but here’s a semantic criticism:
In accordance with the Rationalist tradition that requires everything to have a nerdy sci-fi or fantasy name
I parse this as an in-joke (and appreciate it as such), but I do think that regularly minting new jargon that’s likely to carry substantial, conflicting(!) contextual baggage (not all of it appropriate[1]) is...a bad norm for an epistemic community to have.
I also think that the deeper tradition of jargon-forging (as Eliezer practiced it) involved names that sounded nerdy, but _not_ sci-fi or fantasy -- _cf._ Knowing About Biases Can Hurt People, which uses “Fully General Counterargument” in much the same way(?) as you’re using “Counterspell”. “Fully General Counterargument” is slightly more unwieldy, but apart from that is a better piece of jargon—it’s less loaded and by leaning even harder into the implicit snark that winks at the fact that the purported counter- isn’t working at all, makes it even more clear that no, this is not a useful thing.
[1] To belabor this point, MtG counterspells are fully general (edit: okay, not **fully** general, and see Slider below), and a reasonable fit for the term as you’re using it, but D&D (3.5e, at least) counterspells are based on negating a spell by casting a copy of it, which is not what you mean at all. I don’t actually know what “counterspells” are in WoD/Mage, but the risk that they’re even further afield from your intention should be another strike against using the already-loaded handle.

rossry 28 Apr 2019 4:23 UTC
1 point

in reply to: avturchin's comment on: Open Thread April 2019
preference “my decisions should be mine”—and many people seems to have it
Fair. I’m not sure how to formalize this, though—to my intuition it seems confused in roughly the same way that the concept of free will is confused. Do you have a way to formalize what this means?
(In the absence of a compelling deconfusion of what this goal means, I’d be wary of hacking epistemics in defense of it.)
There are “friends” who claim to have the same goals as me, but later turns out that they have hidden motives.
Agreed and agreed that there’s a benefit to removing their affordance to exploit you. That said, why does this deserve more attention than the inverse case (there are parties you do not trust who later turn out to have benign motives)?

rossry 27 Apr 2019 2:57 UTC
3 points

in reply to: avturchin's comment on: Open Thread April 2019
“give the power over my final decisions to small random events around me” seems like a slightly confused concept if your preferences are truly indifferent. Can you say more about why you see that as a problem?

The potential adversary seems like a more straightforward problem, though one exciting possibility is that lightness of decisions lets a potential cooperator manipulate your decisions on favor of your common interests. And presumably you already have some system for filtering acquaintances into adversaries and cooperators. Is the concern that your filtering is faulty, or something else?

[Commitment] eventually often turn to be winning strategy, compared to the flexible strategy of constant updating expected utility.

Some real-world games are reducible to the game of Chicken. Commitment is often a winning strategy in them. Though I’m not certain that it’s a commitment to a particular set of beliefs about utility so much as a more-complex decision theory which sits between utility beliefs and actions.

In summary, if the acquaintances whose info you update on are sufficiently unaligned with you and your decision theory always selects the addition that your posterior assigns the highest utility, then your actions will be “over-updating on the evidence” if your beliefs are properly Bayesian. But I don’t think the best response is to bias yourself towards under-updating.

rossry 23 Apr 2019 23:22 UTC
3 points

in reply to: clone of saturn's comment on: Moral Weight Doesn’t Accrue Linearly
Do you bite the bullet that this means the set of things you morally value changes discontinuously and predictably as things move out of your light cone? (Or is there some way you value things less as they are less “in” your light cone, in some nonbinary way?)

rossry 23 Apr 2019 23:15 UTC
4 points

on: On the Nature of Programming Languages
I think it’s from SICP that programs are meant to be read by humans and only incidentally for computers to execute; I’ve been trying for more than a year now to write a blog post about the fundamental premise that, effort-weighted, we almost never write new programs from scratch, and mostly are engaged in transmuting one working program into another working program. Programs are not only meant to be read by humans, but edited by humans.

I think if you start from the question of how much effort it is to write a new program on a blank page, most languages will come out looking the same, and the differences will look like psychological constructs. If you ask, however, how much effort it is to change an existing piece of a code base to a specific something else, you start to see differences in epistemic structure, where it matters how many of the possible mutations that a human algorithm might try will non-obviously make the resulting program do something unexpected. And that, as you point out, opens the door to at least some notion of universality.

rossry 23 Apr 2019 22:55 UTC
3 points

in reply to: ryan_b's comment on: On the Nature of Programming Languages

C, the most widespread general-purpose programming language, does things that are extremely difficult or impossible in highly abstract languages like Haskell or LISP

Can you give an example? I’m surprised by this claim, but I only have deep familiarity with C of these three. (My primary functional language includes mutable constructs; I don’t know how purely functional languages fare without them.)

rossry 9 Apr 2019 23:40 UTC
1 point

in reply to: cousin_it's comment on: Open Thread April 2019
I was trying to construct a proof along similar lines, so thank you for beating me to it!

Note that 2 is actually a case of 1, since you can think of the “walls” of the simplex as being bets that the universe offers you (at zero odds).

rossry 9 Apr 2019 11:34 UTC
1 point

in reply to: Oscar_Cunningham's comment on: Open Thread April 2019
(This comment isn’t an answer to your question.)

If I’m understanding properly, you’re trying to use the set of bets offered as evidence to infer the common beliefs of the market that’s offering them. Yet from a Bayesian perspective, it seems like you’re assigning P( X offers bet B | bet B has positive expectation ) = 0. While that’s literally the statement of the Efficient Markets Hypothesis, presumably you—as a Bayesian—don’t actually believe the probability to be literally 0.

Getting this right and generalizing a bit (presumably, you think that P( X offers B | B has expectation +epsilon ) < P( X offers B | B has expectation +BIG_E )), should make the market evidence more informative (and cases of arbitrage less divide-by-zero, break-your-math confusing).

rossry 9 Apr 2019 9:46 UTC
1 point

in reply to: Gurkenglas's comment on: Open Thread April 2019
I’m confused what the word “fairly” means in this sentence.

Do you mean that they make a zero-expected-value bet, e.g., 1:1 odds for a fair coin? (Then “fairly” is too strong; non-degenerate odds (i.e., not zero on either side) is the actual required condition.)

Do you mean that they bet without fraud, such that one will get a positive payout in one outcome and the other will in the other? (Then I think “fairly” is redundant, because I would say they haven’t actually bet on the outcome of the coin if the payouts don’t correspond to coin outcomes.)

rossry 17 Mar 2019 1:53 UTC
1 point

in reply to: rossry's comment on: How can we respond to info-cascades? [Info-cascade series]
A related idea in non-punishment of “wrong” reports that have insufficient support (again in the common-prior/private-info setting) comes from this paper [pdf] (presented at the same conference), which suggests collecting reports from all agents and assigning rewards/punishments by assuming that agents’ reports represent their private signal, computing their posterior, and scoring this assumed posterior. Under the model assumptions, this makes it an optimal strategy for agents to truly reveal their private signal to the mechanism, while allowing the mechanism to collect non-cascaded base data to make a decision.
In general, I feel like the academic literature on market design / mechanism design has a lot to say about questions of this flavor.

rossry 17 Mar 2019 1:34 UTC
4 points

on: How can we respond to info-cascades? [Info-cascade series]
Abstract: Considering information cascades (both upwards and downwards) as a problem of incentives, better incentive design holds some promise. This academic paper suggests a model in which making truth-finding rewards contingent on reaching a certain number of votes prevents down-cascades, and where an informed (self-interested) choice of payout odds and threshold can also prevent up-cascades in the limit of a large population of predictors.
1) cf. avturchin from the question about distribution across fields, pointing out that up-cascades and down-cascades are both relevant concerns, in many contexts.
2) Consider information cascades as related to a problem of incentives—in the comments of the Johnichols post referenced in the formalization question, multiple commentators point out that the model fails if agents seek to express their marginal opinion, rather than their true (posterior) belief. But incentives to be right do need to be built into a system that you’re trying to pump energy into, so the question remains of whether a different incentive structure could do better, while still encouraging truth-finding.
3) Up-Cascaded Wisdom of the Crowd (Cong and Xiao, working paper) considers the information-aggregation problem in terms of incentives, and consider the incentives at play in an all-or-nothing crowdfunding model, like venture capital or Kickstarter (assuming that a ‘no’ vote is irrevocable like a ‘yes’ vote is) -- ‘yes’ voters win if there is a critical mass of other ‘yes’ voters and the proposition resolves to ‘yes’; they lose if there is a critical mass and the proposition resolves to ‘no’; they have 0 loss/gain if ‘yes’ doesn’t reach a critical mass; ‘no’ voters are merely abstaining from voting ‘yes’.
Their main result is that if the payment of incentives is conditioned on the proposition gaining a fixed number of ‘yes’ votes, a population of symmetric, common-prior/private-info agents will avoid down-cascades, as a single ‘yes’ vote that breaks a down-cascade will not be penalized for being wrong unless some later agent intentionally votes ‘yes’ to put the vote over the ‘yes’ threshold. (An agent i with negative private info still should vote no, because if a later agent i’ puts the vote over the ‘yes’ threshold based in part on i’s false vote, then i expects to lose on the truth-evaluation, since they’ve backed ‘yes’ but believe ‘no’.)
A further result from the same paper is that if the actor posing the proposition can set the payout odds and the threshold in response to the common prior and known info-distribution, then a proposition-poser attempting to minimize down-cascades (perhaps because they will cast the first ‘yes’ vote, and so can only hope to win if the vote resolves to ‘yes’) will be incentivized to set odds and a threshold that coincidentally minimize the chance of up-cascades. In the large-population limit, the number of cascades under such an incentive design goes to 0.
4) I suspect (but will not here prove) that augmenting Cong and Xiao’s all-or-nothing “crowdfunding for ‘yes’” design with a parallel “crowdfunding for ‘no’” design—i.e., ‘no’ voters win (resp. lose) iff there is a critical mass of ‘no’ voters and the proposition resolves ‘no’ (resp. ‘yes’) -- can further strengthen the defenses against up-cascades (by making it possible to cast a more informed ‘no’ vote conditioned on a later, more-informed agent deciding to put ‘no’ over the threshold).

rossry 17 Mar 2019 1:30 UTC
0 points

on: How can we respond to info-cascades? [Info-cascade series]
[this answer was duplicated when I mistakenly copied my comment into an answer and then moved the comment to an answer.]

rossry 17 Mar 2019 0:14 UTC
1 point

in reply to: avturchin's comment on: Distribution of info-cascades across fields? [Info-cascade series]
Why stop at 2? Belief-space is large, and many issues admit more than one (+/-) bit of information to cascade.