Comment by gregory_lewis on Legal psychedelic retreats launching in Jamaica · 2019-04-19T01:42:09.615Z · score: 14 (8 votes) · EA · GW

My impression agrees with Issa's: in EA, psychedelic use seems to go along with a cluster of bad epistemic practice (e.g. pseudoscience, neurobabble, 'enlightenment', obscurantism).

This trend is a weak one, with many exceptions; I also don't know about direction of causation. Yet this is enough to make me recommend that taking psychedelics to 'make one a better EA' is very ill-advised.

Comment by gregory_lewis on Reducing EA job search waste · 2019-04-17T07:47:16.439Z · score: 23 (10 votes) · EA · GW

Although private industry and EA organisations may have different incentives, a lot of law for the former will apply to the latter. Per Khorton, demanding the right to publish successful applicants CVs would be probably illegal in many places, and some 'coordination' between EA orgs (e.g. a draft system) seems likely to run afoul of competition law.

Further:

  • The lowest hanging fruit here (which seems a like a good idea) is to give measures of applicant:place ratios for calibration purposes.
  • Independent of legal worries, one probably doesn't need to look at resumes to gauge applicant pool - most orgs have team pages, and so one can look at bios.
  • More extensive feedback to unsuccessful applicants is good, but it easier said than done, as explained by Kelsey Piper here.
  • I don't think EA employers are 'accountable to the community' for how onerous their hiring process is, provided they make reasonable efforts inform potential applicants before they apply. If they've done this, then I'd default to leaving it to market participants to make decisions in their best interest.
Comment by gregory_lewis on Is visiting North Korea effective? · 2019-04-05T09:45:37.283Z · score: 12 (4 votes) · EA · GW

'Getting experience in North Korea' is perhaps one of the worst things you can do if you want to work as a diplomat (or in government more broadly).

Taking US diplomats in particular (although this generalises well to other government roles, and to other countries) people in these roles - ditto ~half the federal government - require a security clearance. Going on your own initiative to a hostile foreign power (circumventing state department attempts to prevent US citizens going without their express dispensation due to safety concerns whilst you are at it) concisely demonstrates you are a giant security risk.

This impression gets little better (and plausibly even worse) if the explanation you offer for your visit is a (probably misguided) attempt to conduct tacit economic warfare against the NK government.

Comment by gregory_lewis on Apology · 2019-03-23T19:02:22.769Z · score: 37 (25 votes) · EA · GW

I don't see that as surprising/concerning. Suppose someone approaches you with (e.g.) "Several people have expressed concerns about your behaviour - they swore us to secrecy about the details, but they seemed serious and credible to us (so much so we intend to take these actions)."

It looks pretty reasonable, if you trust their judgement, to apologise for this even if you lack precise knowledge of what the events in question are.

(Aside: I think having a mechanism which can work in confidence between the relevant parties is valuable for these sorts of difficult situations, and this can get undermined if lots of people start probing for more information and offering commentary.

This doesn't mean this should never be discussed: these sorts of mechanisms can go wrong, and should be challenged if they do (I can think of an example where a serious failing would not have come to light if the initial 'behind closed doors' decision was respected). Yet this seems better done by people who are directly affected by and know the issue in question.)

Comment by gregory_lewis on EA jobs provide scarce non-monetary goods · 2019-03-21T06:46:34.242Z · score: 8 (4 votes) · EA · GW

Right, I (mis?)took the OP to be arguing "reducing salaries wouldn't have an effect on labour supply, because it is price inelastic", instead of "reducing salaries wouldn't have enough of an effect to qualitatively change oversupply.

Aside:

I'd expect a reduction but not a drastic one. Like I'd predict Open Phil's applicant pool to drop to 500-600 from 800 if they cut starting salary by $10k-$15k.

This roughly cashes out to an income elasticity of labour (/applicant) supply of 1-2 (i.e. you reduce applicant supply by ~20% by reducing income ~~10%). Although a crisp comparison is hard to find, in the labour market you see figures generally <1, so this expectation slightly goes against the OP, given it suggests EA applicants are more compensation sensitive than typical.

Comment by gregory_lewis on EA jobs provide scarce non-monetary goods · 2019-03-20T22:55:07.058Z · score: 22 (11 votes) · EA · GW

(Obvious CoI/own views, but in my defence I've been arguing along these lines long before I had - or expected to have - an EA job.)

I agree 'EA jobs' provide substantial non monetary goods, and that 'supply' of willing applicants will likely outstrip available positions in 'EA jobs'. Yet that doesn't mean 'supply' of potential EA employees is (mostly) inelastic to compensation.

In principle, money is handy to all manner of interests one may have, including altruistic ones. Insofar as folks are not purely motivated by altruistic ends (and in such a way they're indifferent to having more money to give away themselves) you'd expect them to be salary-sensitive. I aver basically everyone in EA is therefore (substantially) salary-sensitive.

In practice, I know of cases (including myself) where compensation played a role in deciding to change job, quit, not apply etc. I also recall on the forum remarks from people running orgs which cannot compensate as generously as others that this hurts recruitment.

So I'm pretty sure if you dropped salaries you would reduce the number of eager applicants (albeit perhaps with greater inelasticity than many other industries). As (I think) you imply, this would be a bad idea: from point of view of an org, controlling overall 'supply' of applicants shouldn't be their priority (rather they set salaries as necessary to attract the most cost effective employees). For the wider community point of view, you'd want to avoid 'EA underemployment' in other ways than pushing to distort the labour market.

Comment by gregory_lewis on EA Hotel with free accommodation and board for two years · 2019-03-20T02:23:17.829Z · score: 2 (1 votes) · EA · GW

The inconvenience I had in mind is not in your list, and comprises things in the area of, "Prefer to keep the diet I'm already accustomed to", "Prefer omnivorous diets on taste etc. grounds to vegan ones", and so on. I was thinking of an EA who is omnivorous and feels little/no compunction about eating meat (either because they aren't 'on board' with the moral motivation for animal causes in general, or doesn't find the arguments for veganism persuasive in particular). I think switching to a vegan diet isn't best described as a minor inconvenience for people like these.

But to be clear, this doesn't entail any moral obligation whatsoever on the hotel to serve meat - it's not like they are forcing omnivorous guests to be vegan, but just not cooking them free (non-vegan) food. If a vegan offers me to stay at their house a) for free, b) offers vegan food for free too, c) welcomes me to, if I'm not a fan of vegan food, get my own food to cook at their house whenever I like - which seems basically the counterfactual scenario if I wasn't staying with them in the first place, and d) explains all of this before I come, they've been supererogatory in accommodating me, and it would be absurd for me to say they've fallen short in not serving me free omnivorous food which they morally object to.

Yet insofar as 'free food' is a selling point of the hotel, 'free vegan food' may not be so enticing to omnivorous guests. Obviously the offer is still generous by itself, leave alone combined with free accommodation, but one could imagine it making a difference on the margin to omnivores (especially if they are cost-sensitive).

Thus there's a trade-off in between these people and vegans who would be put off if the hotel served meat itself (even if vegan options were also provided). It's plausible to me the best option to pick here (leave alone any other considerations) is the more 'vegan-friendly' policy. But this isn't because the trade-off is in fact illusory because the 'vegan-friendly' policy is has minimal/minor costs to omnivores after all.

[Empirically though, this doesn't seem to amount to all that much given (I understand) the hotel hasn't been struggling for guests.]

Comment by gregory_lewis on Sharing my experience on the EA forum · 2019-03-20T01:22:31.567Z · score: 7 (5 votes) · EA · GW

Beyond the 'silent downvote -> anon feedback' substitution (good, even if 'public comment' is even better) substitution, there could also be a 'public comment --> anon feedback' one (less good).

That said, I'm in favour of an anon feedback option: I see karma mostly serving as a barometer of community sentiment (so I'm chary of disincentivizing downvotes as this probably impairs resolution). It isn't a good way of providing feedback to the author (a vote is only a bit or two of information). Text is better - although for me, the main reasons I don't 'explain my downvotes' are mostly time, but occasionally social considerations. An anon option at least removes the latter disincentive.

Comment by gregory_lewis on The Importance of Truth-Oriented Discussions in EA · 2019-03-16T02:44:03.880Z · score: 17 (9 votes) · EA · GW

I think I get the idea:

Suppose (heaven forbid) a close relative has cancer, and there's a new therapy which fractionally improves survival. The NHS doesn't provide it on cost-effectiveness grounds. If you look around and see the NHS often provides treatment it previously ruled out if enough public sympathy can be aroused, you might be inclined try to do the same. If instead you see it is pretty steadfast ("We base our allocation on ethical principles, and only change this when we find we've made a mistake in applying them"), you might not be - or at least change your strategy to show the decision the NHS has made for your relative is unjust rather than unpopular.

None of this requires you to be acting in bad faith looking for ways of extorting the government - you're just trying to do everything you can for a loved one (the motivation for pharmaceutical companies that sponsor patient advocacy groups may be less unalloyed). Yet (ideally) the government wants to encourage protest that highlights a policy mistake, and discourage those for when it has done the right thing for its population, but is against the interests of a powerful/photogenic/popular constituency. 'Caving in' to the latter type pushes in the wrong direction.

(That said, back in EA-land, I think a lot things that are 'PR risks' for EA look bad because they are bad (e.g. in fact mistaken, morally abhorrent, etc.), and so although PR considerations aren't sufficient to want to discourage something, they can further augment concern.)

Risk Communication Strategies for the Very Worst of Cases

2019-03-09T06:56:12.480Z · score: 26 (7 votes)
Comment by gregory_lewis on What to do with people? · 2019-03-08T01:26:06.048Z · score: 8 (2 votes) · EA · GW

Related: David Manheim's writing on network theory and scaling organisations.

Comment by gregory_lewis on What skills would you like 1-5 EAs to develop? · 2019-03-07T20:53:31.808Z · score: 3 (2 votes) · EA · GW

A bit of both:

I'd like to see more forecasting skills/literacy 'in the water' of the EA community, in the same way statistical literacy is commonplace. A lot of EA is about making the world go better, and so a lot of (implicit) forecasting is done when deciding what to do. I'd generally recommend most people consider things like opening a Metaculus account, reading superforecasting, etc.

This doesn't mean everyone should be spending (e.g.) 3 hours a day on this, given the usual story about opportunity costs. But I think (per the question topic) there's also a benefit of a few people highly developing this skill (again, a bit like stats: it's generally harder to design and conduct statistical analysis than to critique one already done, but you'd want some folks in EA who can do the former).

Comment by gregory_lewis on What skills would you like 1-5 EAs to develop? · 2019-03-07T00:19:14.160Z · score: 9 (4 votes) · EA · GW

Forecasting

This is more a 'skill I'd like to see more of in the EA community', rather than a career track. It seems a generally valuable skill set for a lot of EA work, and having some people develop expertise/very high performance in it (e.g. becoming a superforecaster) looks beneficial to me.

Comment by gregory_lewis on What skills would you like 1-5 EAs to develop? · 2019-03-07T00:12:06.196Z · score: 12 (5 votes) · EA · GW

[Not one of the downvoters]

The leading rationale of "Learn a trade --> use it for EA projects that need it" looks weak to me:

  • There's not a large enough density of 'EA' work in any given place to take up more than a small fraction of a tradepersons activity. So this upside should be discounted by (substantial) time to learn the trade, and then most of one's 'full time job' as (say) an electrician will not be spent on EA work.
  • It looks pretty unlikely to have 'nomadic' tradespeople travelling between EA hubs, as the added cost of flights etc. suggest it might be more efficient just to try and secure good tradespeople by (e.g.) offering above market rates.

As you say, it could be a good option for some due to good earning power (especially for those with less academic backgrounds, cf. kbog's guide) but the leading rationale doesn't seem substantial reason to slant recommendations (e.g. if you could earn X as a plumber, but 1.1X in something else, the fact they could occasionally help out for EA projects shouldn't outweigh this.

Comment by gregory_lewis on Making discussions in EA groups inclusive · 2019-03-04T20:30:23.843Z · score: 13 (12 votes) · EA · GW

[I didn't downvote.] I fear the story is that this is something of a 'hot button' issue, and people in either 'camp' have sensitivities about publicly speaking out on one side or the other for fear of how others in the opposing 'camp' may react towards them. (The authors of this document are anonymous; previous conversations on this area in this forum have had detractors also use anon accounts or make remarks along the lines of, 'I strongly disagree with this, but I don't want to elaborate further'). Hence why people who might be opposed to this (for whatever reason) preferring anonymous (albeit less-informative) feedback via downvoting.

There are naturally less charitable explanations along the lines of tribalism, brigadeing, etc. etc.

Comment by gregory_lewis on EA Survey 2018 Series: How welcoming is EA? · 2019-03-03T11:29:02.823Z · score: 10 (4 votes) · EA · GW

Thanks for your reply, and the tweaks to the post. However:

[I] decided to keep the discussion short because the regression seemed to offer very limited practical significance (as you pointed out). Had I decided to give it more weight in my analysis then it certainly would be appropriate to offer a fuller explanation. Nonetheless, I should have been clearer about the limited usefulness of the regression, and noted it as the reason for the short discussion.

I think the regression having little practical significance makes it the most useful part of the analysis: it illustrates the variation in the dependent variable is poorly explained by all/any of the variables investigated, that many of the associations found by bivariate assessment vanish when controlling for others, and gives better estimates of the effect size (and thus relative importance) of those which still exert statistical effect. Noting, essentially, "But the regression analyses implies a lot of the associations we previously noted are either confounded or trivial, and even when we take all the variables together we can't predict welcomeness much better than taking the average" at the end buries the lede.

A worked example. The summary notes, "EAs in local groups, in particular, view the movement as more welcoming than those not in local groups" (my emphasis). If you look at the t-test between members and nonmembers there's a difference of ~ 0.25 'likert levels', which is one of the larger effect sizes reported.

Yet we presumably care about how much of this difference can be attributed to local groups. If the story is "EAs in local groups find EA more welcoming because they skew (say) male and young", it seems better to focus attention on these things instead. Regression isn't a magic wand to remove confounding (cf.), but it tends to be better than not doing it at all (which is essentially what is being done when you test association between a single variable and the outcome).

As I noted before, the 'effect size' of local group membership when controlling for other variables is still statistically significant, but utterly trivial. Again: it is ~ 1/1000th of a likert level; the upper bound of the 95% confidence interval would only be ~ 2/1000th of a likert level. By comparison, the effect of gender or year of involvement are two orders of magnitude greater. It seems better in the conclusion to highlight results like these, rather than results the analysis demonstrates have no meaningful effect when other variables are controlled for.

A few more minor things:

  • (Which I forgot earlier). If you are willing to use means, you probably can use standard errors/confidence intervals, which may help in the 'this group looks different, but small group size' points.
  • Bonferroni makes a rod for your back given it is conservative (cf.); an alternative approach is false discovery rate control instead of family wise error rate control. Although minor, if you are going to use this to get your adjusted significance threshold, this should be mentioned early, and the result which 'doesn't make the cut' should be simply be reported as non-significant.
  • It is generally a bad idea to lump categories together (e.g. countries, cause areas) for regression as this loses information (and so statistical power). One of the challenges of regression analysis is garden of forking path issues (even post-hoc - some coefficients 'pop into' and out of statistical significance depending on which model is used, and once I've seen one, I'm not sure how much to discount subsequent ones). It is here where an analysis plan which pre-specifies this is very valuable.
Comment by gregory_lewis on After one year of applying for EA jobs: It is really, really hard to get hired by an EA organisation · 2019-03-01T07:36:14.444Z · score: 9 (5 votes) · EA · GW

FWIW: I think I know of another example along these lines, although only second hand.

Comment by gregory_lewis on EA Survey 2018 Series: How welcoming is EA? · 2019-03-01T07:28:07.030Z · score: 50 (17 votes) · EA · GW

Thanks for this - the presentation of results is admirably clear. Yet I have two worries:

1) Statistics: I think the statistical methods are frequently missing the mark. Sometimes this is a minor quibble; other times more substantial:

a) The dependent variable (welcomeness - assessed by typical Likert scale) is ordinal data i.e. 'very welcoming' > welcoming > neither etc). The write-up often treats this statistically either as categorical data (e.g. chi2) or interval data (e.g. t-test, the use of 'mean welcomeness' throughout). Doing the latter is generally fine (the data looks pretty well-behaved, t-tests are pretty robust, and I recall controversy about when to use non-parametric tests). Doing the former isn't.

chi2 tests against the null of (in essence) the proportion in each 'row' of a table is the same between columns: it treats the ordered scale as a set of 5 categories (e.g. like countries, ethnicities, etc.). Statistical significance for this is not specific for 'more or less welcoming': two groups with identical 'mean welcomeness' yet with a different distribution across levels could 'pass statistical significance' by chi2. Tests for 'ranked dependent by categorical independent' data exist (e.g. Kruskall-Wallis) and should be used instead.

Further, chi2 assumes the independent variable is categorical too. Usually it is (e.g. where you heard about EA) but sometimes it isn't (e.g. age, year of joining, ?political views). For similar reasons to the above, a significant chi2 result doesn't demonstrate a (monotonic) relationship between welcomeness and time in EA. There are statistical tests for trend which can be used instead.

Still further, chi2 (ditto K-W) is an 'omnibus' test: it tells you your data is surprising given the null, but not what is driving the surprise. Thus statistical significance 'on the test' doesn't indicate whether particular differences (whether highlighted in the write-up or otherwise) are statistically significant.

b) The write-up also seems to be switching between the descriptive and the inferential in an unclear way. Some remarks on the data are accompanied with statistical tests (implying an inference from the sample to the population), whilst similar remarks are not: compare the section on 'time joining EA' (where there are a couple of tests to support a 'longer in EA - finding it more welcoming'), versus age (which notes a variety of differences between age groups, but no statistical tests).

My impression is the better course is the former, and so differences being highlighted to the readers interest should be accompanied by whether these differences are statistically significant. This uniform approach also avoids 'garden of forking path' worries (e.g. 'Did you not report p values for the age section because you didn't test, or because they weren't significant?')

c) The ordered regression is comfortably the 'highest yield' bit of statistics performed, as it is appropriate to the data, often more sensitive (e.g. lumping the data into two groups by time in EA and t-testing is inferior technique to regression), and helps answer questions of confounding sometimes alluded to in the text ("Welcoming seems to go up with X, but down with Y, which is weird because X and Y correlate"), but uniformly important ("People in local groups find EA more welcoming - but could that driven by other variables between those within and without local groups?")

It deserves a much fuller explanation (e.g. how did 'country' and 'top priority cause' become single variables with a single regression coefficient - is the 'lumping together' implied in the text post-hoc? How was variable selection/model choice decided? Model 1 lacks only 'top priority cause', so assumedly 'adding in political spectrum didn't improve explanatory power' is a typo?). When its results vary with the univarible analysis, I would prefer the former over the latter. That fb membership, career shifting (in model 2), career type, and politics aren't significant predictors means their relationship to welcomingness, if, even if statistically significant, probably confounding rather than true association.

It is unfortunate some of these are highlighted in the summary and conclusion, even more so when a crucial negative result from the regression is relatively unsung. The ~3% R^2 and very small coefficients (with the arguable exception of sex) implies very limited practical significance: almost all the variation in whether an EA finds EA welcoming or not is not predicted by the factors investigated; although EAs in local groups find EA more welcoming, this effect - albeit statistically significant - is (if I interpret the regression right) around 0.1% of a single likert level.

2) Selection bias: A perennial challenge to the survey is issues of selection bias. Although happily noted frequently in discussion, I still feel it is underweighed: I think it is huge enough to make the results all but uninterpretable.

Facially, one would expect those who find EA less welcoming are less likely to join. We probably wouldn't think that how welcoming people already in EA think it is would be informative to how good it is at welcoming people into EA (caricatured example: I wouldn't be that surprised if members of something like the KKK found it generally welcoming). As mentioned in the 'politics' section, the relative population size seems a far better metric (although the baseline hard to establish) to which welcomingness adds very little.

Crucially, selection bias imposes some nigh-inscrutable but potentially sign-inverting considerations to any policy 'upshot'. A less welcoming subgroup could be cause for concern, but alternatively cause for celebration: perhaps this subgroup offers other 'pull factors' that mean people who find EA is less welcoming nonetheless join and stick around within it (and vice versa: maybe subgroups whose members find EA very welcoming do so because they indirectly filter out everyone who doesn't). Akin to Wald and the bombers in WW2, it is crucial to work out which. But I don't think we can here.

Comment by gregory_lewis on After one year of applying for EA jobs: It is really, really hard to get hired by an EA organisation · 2019-02-27T00:45:08.529Z · score: 38 (17 votes) · EA · GW

I think the reason the OP had a high fraction of 'long' processes had more to do with him being a strong applicant who would get through a lot of the early filters. I don't think a typical 'EA org' hiring round passes ~50% of its applicants to a work test.

This doesn't detract from your other points re. the length in absolute terms. (The descriptions from OP and others read uncomfortably reminiscent of more senior academic hiring, with lots of people getting burned competing for really attractive jobs). There may be some fundamental trade-offs (the standard argument about '*really* important to get the right person, so we want to spent a lot of time assessing plausible candidates to pick the right one, false negatives at intermediate stages cost more than false positives, etc. etc.'), but an easy improvement (mentioned elsewhere) is to communicate as best as one can the likelihood of success (perhaps broken down by stage) so applicants can make a better-informed decision.

Comment by gregory_lewis on Has your "EA worldview" changed over time? How and why? · 2019-02-26T00:22:08.344Z · score: 20 (9 votes) · EA · GW
If you're Open Phil, you can hedge yourself against the risk that your worldview might be wrong by diversifying. But the rest of us are just going to have to figure out which worldview is actually right.

Minor/Meta aside: I don't think 'hedging' or diversification is the best way to look at this, whether one is an individual or a mega-funder.

On standard consequentialist doctrine, one wants to weigh things up 'from the point of view of the universe', and be indifferent as to 'who is doing the work'. Given this, it looks better to act in the way which best rebalances the humanity-wide portfolio of moral effort, rather than a more narrow optimisation of 'the EA community', 'OPs grants', or ones own effort.

This rephrases the 'neglectedness' consideration. Yet I think people don't often think enough about conditioning on the current humanity-wide portfolio, or see their effort as being a part of this wider whole, and this can mislead into moral paralysis (and, perhaps, insufficient extremising). If I have to 'decide what worldview is actually right', I'm screwed: many of my uncertainties I'd expect to be resilient to a lifetime of careful study. Yet I have better prospects of reasonably believing that "This issue is credibly important enough that (all things considered, pace all relevant uncertainties) in an ideal world humankind would address X people to work on this - given in fact there are Y, Y << X, perhaps I should be amongst them."

This is a better sketch for why I work on longtermism, rather than overall confidence in my 'longtermist worldview'. This doesn't make worldview questions irrelevant (there are lot of issues where the sketch above applies, and relative importance will be one of the ingredients that goes in the mix of divining which one to take), but it means I'm fairly sanguine about perennial uncertainty. My work is minuscule part of the already-highly-diversified corporate effort of humankind, and the tacit coordination strategy of people like me acting on our best guess of the optimal portfolio looks robustly good (a community like EA may allow better ones), even if (as I hope and somewhat expect) my own efforts transpire to have little value.

The reason I shouldn't 'hedge' but Open Phil should is not so much because they can afford to (given they play with much larger stakes, better resolution on 'worldview questions' has much higher value to them than to I), but because the returns to specialisation are plausibly sigmoid over the 'me to OP' range. For individuals, there's increasing marginal returns to specialisation: in the same way we lean against 'donation splitting' with money, so too with time (it seems misguided for me to spend - say - 30% on bio, 10% on AI, 20% on global health, etc.) A large funder (even though it still represents a minuscule fraction of the humanity-wide portfolio) may have overlapping marginal return curves between its top picks of (all things considered) most promising things to work on, and it is better placed to realise other 'portfolio benefits'.

Comment by gregory_lewis on Evidence on good forecasting practices from the Good Judgment Project: an accompanying blog post · 2019-02-16T18:44:01.262Z · score: 6 (5 votes) · EA · GW

Excellent. This series of interviews with superforecasters is also interesting. [H/T Ozzie]

Comment by gregory_lewis on EA Survey 2018 Series: Donation Data · 2018-12-10T23:45:59.445Z · score: 5 (3 votes) · EA · GW

Thanks. I should say that I didn't mean to endorse stepwise when I mentioned it (for reasons Gelman and commenters note here), but that I thought it might be something one might have tried given it is the variable selection technique available 'out of the box' in programs like STATA or SPSS (it is something I used to use when I started doing work like this, for example).

Although not important here (but maybe helpful for next time), I'd caution against using goodness of fit estimators (e.g. AIC going down, R2 going up) too heavily in assessing the model as one tends to end up with over-fitting. I think the standard recommendations are something like:

  • Specify a model before looking at the data, and caveat any further explanations as post-hoc. (which sounds like essentially what you did).
  • Split your data into an exploration and confirmation set, where you play with whatever you like on the former, then use the model you think is best on the latter and report these findings (better, although slightly trickier, are things like k-fold cross validation rather than a single holdout).
  • LASSO, Ridge regression (or related regularisation methods) if you are going to select predictors 'hypothesis free' on your whole data.

(Further aside: Multiple imputation methods for missing data might also be worth contemplating in the future, although it is a tricky judgement call).

Comment by gregory_lewis on Giving more won't make you happier · 2018-12-10T23:13:58.822Z · score: 27 (13 votes) · EA · GW

Neither of your examples backs up your point.

The 80000 hours article you cite notes in its summary only that:

Giving some money to charity is unlikely to make you less happy, and may well make you happier. (My emphasis)

The GWWC piece reads thus:

Giving 10% of your income to effective charities can make an incredible difference to some of the most deprived people in the world. But what effect will giving have on you? You may be concerned that it will damage your quality of life and make you less happy. This is a perfectly reasonable concern, and there is no shame in wanting to live a full and happy life.

The good news is that giving can often make you happier.... (My emphasis)

As I noted in prior discussion, not only do these sources not claim 'giving effectively will increase your happiness', I'm not aware of this being claimed by any major EA source. Thus the objection "This line of argument confuses the effect of donating at all with the effect of donating effectively" targets a straw man.

Comment by gregory_lewis on Open Thread #43 · 2018-12-09T19:17:24.830Z · score: 12 (5 votes) · EA · GW

My impression FWIW is that the 'giving makes you happier' point wasn't/isn't advanced to claim that the optimal portfolio for one's personal happiness would include (e.g.) 10% of charitable donations (to effective causes), but that doing so isn't such a 'hit' to one's personal fulfilment as it appears at first glance. This is usually advanced in conjunction with the evidence on diminishing returns to money (i.e. even if you just lost - say - 10% of your income, if you're a middle class person in a rich country, this isn't a huge loss to your welfare - and given this evidence on the wellbeing benefits to giving, the impact is likely to be reduced further).

E.g. (and with apologies to the reader for inflicting my juvenilia upon them):

[Still being in the a high global wealth percentile post-giving] partly explains why I don’t feel poorly off or destitute. There are other parts. One is that giving generally makes you happier, and often more happier than buying things for yourself. Another is that I am fortunate in non-monetary respects: my biggest medical problem is dandruff, I have a loving family, a wide and interesting circle of friends, a fulfilling job, an e-reader which I can use to store (and occasionally read) the finest works of western literature, an internet connection I should use for better things than loitering on social media, and so on, and so on, and so on. I am blessed beyond all measure of desert.
So I don’t think that my giving has made me ‘worse off’. If you put a gun to my head and said, “Here’s the money you gave away back. You must spend it solely to further your own happiness”, I probably wouldn’t give it away: I guess a mix of holidays, savings, books, music and trips to the theatre might make me even happier (but who knows? people are bad at affective forecasting). But I’m pretty confident giving has made me happier compared to the case where I never had the money in the first place. So the downside looks like, “By giving, I have made myself even happier from an already very happy baseline, but foregone opportunities to give myself a larger happiness increment still”. This seems a trivial downside at worst, and not worth mentioning across the scales from the upside, which might be several lives saved, or a larger number of lives improved and horrible diseases prevented.
Comment by gregory_lewis on EA Survey 2018 Series: Donation Data · 2018-12-09T13:16:07.099Z · score: 3 (2 votes) · EA · GW

Thanks for these interesting results. I have a minor technical question (which I don't think was covered in the methodology post, nor in the Github repository from a quick review):

How did you select the variables (and interaction term) for the regression model? A priori? Stepwise? Something else?

Comment by gregory_lewis on EA Survey 2018 Series: Community Demographics & Characteristics · 2018-11-27T19:44:30.141Z · score: 2 (1 votes) · EA · GW

Minor: I'd say the travel times in 'Loxbridge' are somewhat longer than an hour.

Time from (e.g.) Oxford train station to London train station is an hour, but adding on the travel time from 'somewhere in Oxford/London to the train station' would push this up to ~2 hours. Oxford to Cambridge takes 3-4 hours by public transport.

The general topic looks tricky. I'd guess if you did a kernel density map over the bay, you'd get a (reasonably) even gradient over the 3k square miles. If you did the same over 'Loxbridge' you'd get very strong foci over the areas that correspond to London/Oxford/Cambridge. I'd also guess you'd get reasonable traffic between subareas in the bay area, but in Loxbridge you'd have some Oxford/London and Cambridge/London (a lot of professionals make this sort of commute daily) but very little Oxford/Cambridge traffic.

What criteria one uses to chunk large connurbations into natural language looks necessarily imprecise. I'd guess if you had the ground truth and ran typical clustering algos on it, you'd probably get a 'bay area' cluster though. What might be more satisfying is establishing whether the bay acts like a single community: if instead there is a distinguishable (e.g.) East Bay and South Bay community, where people in one or the other group tend to go to (e.g.) events in one or the other and visit the other occasionally (akin to how an Oxford-EA like me may mostly attend Oxford events but occasionally visit London ones), this would justify splitting it up.

Comment by gregory_lewis on Cross-post: Think twice before talking about ‘talent gaps’ – clarifying nine misconceptions, by 80,000 Hours. · 2018-11-20T08:29:15.217Z · score: 6 (3 votes) · EA · GW

Although orgs tacitly colluding with one another to pay their staff less than they otherwise would may also have an adverse effect on recruitment and retention...

Comment by gregory_lewis on William MacAskill misrepresents much of the evidence underlying his key arguments in "Doing Good Better" · 2018-11-17T20:55:52.930Z · score: 27 (13 votes) · EA · GW

Sure.

I don't take, "[DGB] misrepresents sources structurally, and this is a convincing sign it is written in bad faith." to be either:

  • True. The OP strikes me as tendentiously uncharitable and 'out for blood' (given the earlier versions was calling for Will to be disavowed by EA per Gleb Tsipursky, trust in Will down to 0, etc.), and the very worst that should be inferred, even if we grant all the matters under dispute in its favour - which we shouldn't - would be something like "sloppy, and perhaps with a subconscious finger on the scale tilting the errors to be favourable to the thesis of the book" rather than deceit, malice, or other 'bad faith'.
  • Helpful. False accusations of bad faith are obviously toxic. But even true ones should be made with care. I was one of the co-authors on the Intentional Insights document, and in that case (with much stronger evidence suggestive of 'structural misrepresentation' or 'writing things in bad faith') we refrained as far as practicable from making these adverse inferences. We were criticised for this at the time (perhaps rightly), but I think this is the better direction to err in.
  • Kind. Self explanatory.

I'm sure Siebe makes their comment in good faith, and I agree some parts of the comment are worthwhile (e.g. I agree it is important that folks in EA can be criticised). But not overall.

Comment by gregory_lewis on Crohn's disease · 2018-11-16T14:15:46.358Z · score: 9 (2 votes) · EA · GW

In hope but little expectation:

You could cast about for various relevant base-rates ("What is the chance of any given proposed conjecture in medical science being true?" "What is the chance of a given medical trial giving a positive result?"). Crisp data on these questions are hard to find, but the proportion for either is comfortably less than even. (Maybe ~5% for the first, ~20% for the second).

From something like this one can make further adjustments based on the particular circumstances, which are generally in the adverse direction:

  • Typical trials have more than n=6 non-consecutive case series behind them, and so this should be less likely to replicate than the typical member of this class.
  • (Particularly, heterodox theories of pathogenesis tend to do worse, and on cursory search I can find a alternative theories of Crohn's which seem about as facially plausible as this).
  • The wild theory also imposes a penalty: even if the minimal prediction doesn't demand the wider 'malasezzia causes it etc.', that the hypothesis is generated through these means is a further cost.
  • There's also information I have from medical training which speaks against this (i.e. if antifungals had such dramatic effects as proposed, it probably would have risen to attention somewhat sooner).
  • All the second order things I noted in my first comment.

As Ryan has explained, standard significance testing puts a floor of 2.5% of a (false) positive result in any trial even if the true effect is zero. There is some chance the ground truth really is that itraconazole cures Crohn's (given some evidence of TNFa downstream effects, background knowledge of fungal microbiota disregulation, and the very slender case series), which gives it a small boost above this, although this in itself is somewhat discounted by the limited power of the proposed study (i.e. even if Itraconazole works, the study might miss it).

Comment by gregory_lewis on Crohn's disease · 2018-11-15T22:54:38.027Z · score: 10 (3 votes) · EA · GW

~3% (Standard significance testing means there's a 2.5% chance of a false positive result favouring the treatment group under the null).

Comment by gregory_lewis on Crohn's disease · 2018-11-15T19:59:49.140Z · score: 9 (2 votes) · EA · GW

The idea of doing an intermediate piece of work is so one can abandon the project if it is negative whilst having spent less than 500k. Even independent of the adverse indicators I note above, the prior on case series finding replicating out in RCT is very low.

Another cheap option would be talking to the original investigators. They may have reasons why they haven't followed this finding up themselves.

Comment by gregory_lewis on Crohn's disease · 2018-11-15T15:45:05.007Z · score: 7 (4 votes) · EA · GW

A cheaper alternative (also by about an order of magnitude) is to do a hospital record study where you look at subsequent Crohn's admissions or similar proxies of disease activity in those recently prescribed antifungals versus those who aren't.

I also imagine it would get better data than a poorly powered RCT.

Comment by gregory_lewis on Crohn's disease · 2018-11-14T08:27:43.642Z · score: 29 (11 votes) · EA · GW

I strong-downvoted this post. I had hoped the reasons why would be obvious. Alas not.

Scientific (in)credibility

The comments so far have mainly focused on the cost-effectiveness calculation. Yet it is the science itself that is replete with red flags: from grandiose free-wheeling, to misreporting cited results, to gross medical and scientific misunderstanding. [As background: I am a doctor who has published on the genetics of inflammatory bowel disease]

Several examples before I succumbed:

  • Samuel et al. 2010 is a retrospective database review of 6 patients treated with itraconazole for histoplasmosis in Crohn's Disease (CD) (N.B. Observational, not controlled, and as a letter, editor- rather than peer-reviewed). It did not "report it cured patients with CD by clearing fungus from the gut": the authors' own (appropriately tentative - unlike the OP) conjecture was any therapeutic effect was mediated by immunomodulatory effects of azole drugs downstream of TNF-a. It emphatically didn't "suggest oral itraconazole may be effective against Malassezia in the gut" (as claimed in the linked website's FAQ) as the presence or subsequent elimination of Malassezia was never assessed - nor was Malassezia mentioned.
  • Crohn's disease is not a spondyloarthritis! (and neither is psoriasis, ulcerative colitis, or acute anterior uveitis). As the name suggests, spondyloarthritides are arthritides (i.e. diseases principally of joints - the 'spondylo' prefix points to joints between vertebrae); Crohn's a disease of the GI tract. Crohn's can be associated with a spondyloarthritis (enteropathic spondyloarthritis). As the word 'associated' suggests, these are not one and the same: only a minority of those with Crohn's develop joint sequelae. (cf. Standard lists of spondyloarthrides - note Crohn's simpliciter isn't on them).
  • Chronic inflammation isn't a symptom ('spondoyloarthritide' or otherwise), and symptoms (rather than diseases) are only cured in the colloquial use of the term.
  • However one parses "[P]roving beyond all doubt that Crohn's disease is caused by this fungus will very likely lead to a cure for all spondyloarthritide symptoms using antifungal drugs." ('Merely' relieving all back pain from spondyloarthritides? Relieving all symptoms that arise from the set of (correctly defined) spondyloarthritides? Curing all spondyloarthritides? Curing (and/or relieving all symptoms) from the author's grab bag of symptoms/diseases which include CD, Ulcerative Collitis, Ankylosing spondylitis, Psoriasis and chronic back pain?) The antecedent (one n=40 therapeutic study won't prove Malassezia causes Crohn's, especially with a competing immunomodulatory mechanism already proposed); the consequent (anti-fungal drugs as some autoimmune disease panacea of uncertain scope); and the implication (even if Malasezzia is proven to cause Crohn's, the likelihood of this result (and therapy) generalising is basically nil) are all absurd.
  • The 'I love details!' page notes at then end "These findings satisfy Koch’s postulates for disease causation, albeit scattered across several related diseases." Which demonstrate the author doesn't understand Koch's postulates: you can't 'mix and match' across diseases, and the postulates need to be satisfied in sequence (i.e. you find the microorganism only present in cases of the disease (1), culture it (2), induce the disease in a healthy individual with such a culture (3), and extract the organism again from such individuals (4)).
  • The work reported in that page, here, and elsewhere also directly contradict Koch's first postulate. Malasezzia is not found in abundance in cases of disease (pick any of them) and not in healthy individuals (postulate 1): the author himself states Malasezzia is ubiquitous across individuals, diseased or not (and this ubiquity is cited as why this genus is being proposed in the first place).

Intermezzo

I'd also rather not know how much has been spent on this so far. Whatever it is, investing another half a million dollars is profoundly ill-advised (putting the money in a pile and burning it is mildly preferable, even when one factors in climate change impacts). At least an order of magnitude cheaper is buying the time of someone who works in Crohn's to offer their assessment. I doubt it would be less scathing than mine.

Meta moaning

Most EAs had the good judgement to avoid the terrible mistake of a medical degree. One of the few downsides of so doing is (usually) not possessing the background knowledge to appraise something like this. As a community, we might worry about our collective understanding being led astray without the happy accident of someone with specialised knowledge (yet atrocious time-management and prioritisation skills among manifold other relevant personal failings) happening onto the right threads.

Have no fear: I have some handy advice/despairing pleas:

  • Medical science isn't completely civilizationally inadequate, and thus projects that resort to being pitched directly to inexpert funders have a pretty poor base rate (cf. DRACO)
  • Although these are imperfect, if the person behind the project doesn't have credentials in a relevant field (bioinformatics rather than gastroenterology, say), and/or a fairly slender relevant publication record, and scant/no interest from recognised experts, these are also adverse indicators. (Remember the nobel-prize winner endorsed Vit C megadosing?)
  • It can be hard to set the right incredulity prior: we all want take advantage of our risk neutrality to chase hits, but not all upsides that vindicate a low likelihood are credible. A rule-of-thumb I commend is 10^-(3+n(miracles)). So when someone suggests they have discovered the key mechanism of action (and consequent fix) for Crohn's disease, and ulcerative colitis, and ankylosing spondylitis, and reactive arthritis, and psoriasis, and psoriatic arthritis, and acute anterior uveitis, and oligoarthritis, and multiple sclerosis, and rheumatoid arthritis, and systemic lupus erythematosus, and prostate cancer, and benign prostatic hyperplasia, and chronic back pain (n~14), there may be some cause for concern.
  • Spot-checking bits of the write-up can be a great 'sniff test', especially in key areas where one isn't sure of one's ground ("Well, the fermi seems reasonable, but I wonder what this extra-sensory perception thing is all about").
  • Post value tends to be multiplicative (e.g. the antecedent of "If we have a cure for Crohn's, how good would it be?" may be the crucial consideration), and so its key to have an to develop an understanding across the key topics. Otherwise one risks conversational bikeshedding. Worse, there could be Sokal-hoax-esque effects where nonsense can end up well-received (say, moderately upvoted) provided it sends the right signals on non-substantive metrics like style, approach, sentiment, etc.

I see these aspects of epistemic culture as an important team sport, with 'amateur' participation encouraged (for my part, implored). I had hoped when I clicked the 'downvote' arrow for a few seconds I could leave this to fade in obscurity thereafter. When instead I find it being both upvoted and discussed like it has been, I become worried that it might actually attract resources from other EAs who might mistakenly take conversation thus-far to represent the balance of reason, and detract from EA's reputation with those who recognise it does not (cf. "The scientific revolution for altruism" aspiration). So I feel I have to am to write something more comprehensive. This took a lot longer than a few seconds, although fortunately my time is essentially worthless. Next time we may not be so lucky.

Comment by gregory_lewis on Even non-theists should act as if theism is true · 2018-11-09T22:07:37.681Z · score: 5 (3 votes) · EA · GW

The meat of this post seems to be a version of Plantinga's EAAN.

Comment by gregory_lewis on Mind Ease: a promising new mental health intervention · 2018-10-23T22:17:21.312Z · score: 19 (16 votes) · EA · GW

[based on an internally run study of 250 uses] Mind Ease reduces anxiety by 51% on average, and helps people feel better 80% of the time.

Extraordinary claims like this (and it's not the only one - e.g. "very likely" to help myself or people who I know who suffer from anxiety elsewhere in the post, "And for anxiety [discovering which interventions work best] is what we've done, '45% reduction in negative feelings' in the app itself) demands much fuller and more rigorous description and justification. e.g. (and cf. PICO):

  • (Population): How are you recruiting the users? Mturk? Positly? Convenience sample from sharing the link? Are they paid for participation? Are they 'people validated (somehow) as having an anxiety disorder' or (as I guess) 'people interested in reducing their anxiety/having something to help when they are particularly anxious?'
  • (Population): Are the "250 uses" 250 individuals each using Mindease once? If not, what's the distribution of duplicates?
  • (Intervention): Does "250 uses" include everyone who fired up the app, or only those who 'finished' the exercise (and presumably filled out the post-exposure assessment)?
  • (Comparator): Is this a pre-post result? Or is this vs. the sham control mentioned later? (If so, what is the effect size on the sham control?)
  • (Outcome): If pre-post, is the postexp assessment immediately subsequent to the intervention?
  • (Outcome): "reduces anxiety by 51%" on what metric? (Playing with the app suggests 5-level Likert scales?)
  • (Outcome): Ditto 'feels better' (measured how?)
  • (Outcome): Effect size (51% from what to what?) Inferential stats on the same (SE/CI, etc.)

There are also natural external validity worries. If (as I think it is) the objective is 'immediate symptomatic relief', results are inevitably confounded by anxiety a symptom that is often transient (or at least fluctuating in intensity), and one with high rates of placebo response. An app which does literally nothing but waits a couple of days before assessing (symptomatic) anxiety again will probably show great reductions in self-reported anxiety on pre-post, as people will be preferentially selected to use the app when feeling particularly anxious, and severity will tend to regress. This effect could apply to much shorter intervals (e.g. those required to perform a recommended exercise).

(Aside: An interesting validity test would be using GAD-7 for pre-post assessment. As all the items on GAD-7 are 'how often do you get X over the last 2 weeks', significant reduction in this metric immediately after the intervention should raise alarm).

In candour (and with regret) this write-up raises a lot of red flags to me. There is a large relevant literature which this post does not demonstrate command of. For example, there's a small hill of descriptive epidemiology papers on prevalence of anxiety as a symptom or anxiety disorders - including large population samples for GAD-7, which would look better routes to prevalence estimates than conducting a 300-person survey (and if you do run this survey, finding a prevalence in your sample of 73% >5 GAD given the population studies (e.g.) give means and medians ~2-3 and proportions >5 ~ 25% prompt obvious questions).

Likewise there are well-understood pitfalls in conducting research (some them particularly acute for intervention studies, and even moreso in intervention studies on mental health), which the 'marketing copy' style presentation (heavy on exuberant confidence, light on how this is substantiated) gives little reassurance they were in fact avoided. I appreciate "writing for an interested lay audience" (i.e. this one) demands a different style than writing to cater to academic scepticism. Yet the latter should be satisfied (either here or in a linked write-up), especially when attempting pioneering work in this area and claiming "extraordinarily good" results. We'd be cautious in accepting this from outside sources - we should mete out similar measure to projects developed 'in house'.

I hope subsequent work proves my worries unfounded.

Comment by gregory_lewis on Many EA orgs say they place a lot of financial value on their previous hire. What does that mean, if anything? And why aren't they hiring faster? · 2018-10-14T08:47:21.969Z · score: 29 (27 votes) · EA · GW

My hunch is (as implied elsewhere) 'talent-constraint' with 'talent' not further specified is apt to mislead. My impression for longtermist orgs (I understand from Peter and others this may apply less to orgs without this as the predominant focus) is there are two broad classes, which imperfectly line up with 'senior' versus 'junior'.

The 'senior' class probably does fit (commensensically understood) 'talent-constraint', in that orgs or the wider ecosystem want to take everyone who clears a given bar. Yet these bars are high even when conditioned on the already able cohort of (longtermist/)EAs. It might be things like 'ready to run a research group', 'can manage operations for an org' (cf. Tara's and Tanya's podcasts), 'subject matter expertise/ability/track record'.

One common feature is that these people add little further load on current (limited) management capacity, either because they are managing others or are already 'up to speed' to contribute themselves without extensive training or supervision. (Aside: I suspect this is a under-emphasised bonus of 'value-aligned operations staff' - their tacit knowledge of the community/mission/wider ecosystem may permit looser management than bringing on able professionals 'from outside'.) From the perspective of the archetypal 'pluripotent EA' a few years out from undergrad, these are skills which are hard to develop and harder to demonstrate.

More 'junior' roles are those where the criteria are broader (at least in terms of legible ones: 'what it takes' to be a good generalist researcher may be similarly rare to 'what it takes' to be a good technical AI safety researcher, but more can easily 'rule themselves out' of the latter than the former), where 'upskilling' is a major objective, or where there's expectation of extensive 'hands-on' management.

There might be similarly convex returns to getting a slightly better top candidate (e.g. 'excellent versus very good' might be 3x rather than 1.3x). Regardless, there will not be enough positions for all the talented candidates available: even if someone at an org decided to spend their time only managing and training junior staff (and haste considerations might lead them to spending more of their time doing work themselves than investing in the 'next generation'), they can't manage dozens at a time.

I think confusing these two broad classes is an easy way of burning a lot of good people (cf. Denise's remarks). If Alice the 23-year-old management consultant might reason on current messaging, "EA jobs are much better for the world than management consultancy, and they're after good people - I seem to fit the bill, so I should switch career into this". She might then forsake her promising early career for an unedifying and unsuccessful period as 'EA perennial applicant', ending up worse than she was at the start. EA has a vocational quality to it - key it does not become a siren song.

There seem a few ways to do this better, as alluded to in prior discussions here and elsewhere:

0) If I'm right, it'd be worth communicating the 'person spec' for cases where (common-sense) talent constraint applies, and where we really would absorb basically as many as we could get (e.g. "We want philosophers to contribute to GPR, and we're after people who either already have a publication record in this area, or have signals of 'superstar' ability even conditioned on philosophy academia. If this is you, please get in touch.").

1) Concurrently, it'd be worth publicising typical applicants:place or similar measures of competition for hiring rounds in more junior roles to allow applicants to be better calibrated/emphasise the importance of plan B. (e.g. "We have early-career roles for people thinking of working as GPR researchers, which serves the purpose of talent identification and development. We generally look for XYZ. Applications for this are extremely competitive (~12:1). Other good first steps for people who want to work in this field are these"). {MIRI's research fellows page does a lot of this well}.

2) It would be good for there to be further work addressed to avoiding 'EA underemployment', as I would guess growth in strong candidates for EA roles will outstrip intra-EA opportunities. Some possibilities:

2.1) There are some areas I'd want to add to the longtermist portfolio which might be broadened into useful niches for people with comparative advantage in them (macrohistory, productivity coaching and nearby versions, EA-relevant bits of psychology, etc.) I don't think these are 'easier' than the existing 'hot' areas, but they are hard in different ways, and so broaden opportunities.

2.2) Another option would be 'pre-caching human capital' into areas which are plausible candidates for becoming important as time goes on. I imagine something like international relations turning out to be crucial (or, contrariwise, relatively unimportant), but it seems better rather than waiting for this to be figured out for instead people to coordinate and invest themselves across the portfolio of plausible candidates. (Easier said than done from the first person perspective, as such a strategy potentially involves making an uncertain bet with many years of one's career, and if it turns out to be a bust ex post the good ex ante EV may not be complete consolation).

2.3) There seem a lot of stakeholders where it would be good for EAs to enter due to the second-order benefits even if their direct work is of limited direct relevance (e.g. having more EAs in tech companies looks promising to me, even if they aren't doing AI safety). (Again, not easy from the first person-perspective).

2.4) A lot of skills for more 'senior' roles can and have been attained outside of the EA community. Grad school is often a good idea for researchers, and professional/management aptitude is often a transferable skill. So some of the options above can be seen as a holding-pattern/bet hedging approach: they hopefully make one a stronger applicant for such roles, but in the meanwhile one is doing useful things (and also potentially earning to give, although I think this should be a minor consideration for longtermist EAs given the field is increasingly flush with cash).

If the framing is changed to something like, "These positions are very valuable, but very competitive - it is definitely worth you applying (as you in expectation increase the quality of the appointed candidate, and the returns of a slightly better candidate are very high), don't bet the farm (or quit the day job) on your application - and if you don't get in, here's things you could do to slant your career to have a bigger impact", I'd hope the burn risk falls dramatically: in many fields there are lots of competitive oversubscribed positions which don't impose huge costs to unsuccessful applicants.

Comment by gregory_lewis on 2018 list of half-baked volunteer research ideas · 2018-09-20T08:55:13.801Z · score: 4 (3 votes) · EA · GW

Something similar perhaps worth exploring is putting up awards/bounties for doing particular research projects. A central clearing-house of this could be interesting (I know myself and a couple of others have done this on an ad-hoc basis - that said, efforts to produce central repositories for self-contained projects etc. in EA have not been wildly successful).

A couple of related questions/topics I'd be excited for someone to have a look at:

1. Is rationality a skill, or a trait? Stanovich's RQ correlates with IQ fairly strongly, but I imagine going through the literature could uncover how much of a positive manifold there is between 'features' of rationality which is orthogonal to intelligence, and then investigation of how/whether this can be trained (with sub-questions around transfer, what seems particularly promising, etc.

2. I think a lot of people have looked into the superforecasting literature for themselves, but a general write-up for public consumption (e.g. How 'traity' is superforecasting? What exactly does GJP do to get a reported 10% boost from pre-selected superforecasters? Are there useful heuristics people can borrow to improve their own performance beyond practice/logging predictions? (And what is the returns curve to practice, anyway?)) could spare lots of private duplication.

3. More generally, I imagine lots of relevant books (e.g. Deep Work, superforecasting, better angels) could be concisely summarised. That said, I think there are already services that do this, so less clear if this already exists whether it is worth EA time to repeat 'in house'.

Comment by gregory_lewis on Current Estimates for Likelihood of X-Risk? · 2018-08-06T20:46:04.825Z · score: 6 (10 votes) · EA · GW

Thanks for posting this.

I don't think there are any other sources you're missing - at least, if you're missing them, I'm missing them too (and I work at FHI). I guess my overall feeling is these estimates are hard to make and necessarily imprecise: long-run large scale estimates (e.g. what was the likelihood of a nuclear exchange between the US and Russia between 1960 and 1970?) are still very hard to make ex post, leave alone ex ante.

One question might be how important further VoI is for particular questions. I guess the overall 'x risk chance' may have surprisingly small action relevance. The considerations about the relative importance of x-risk reduction seem to be fairly insensitive to 10^-1 or 10^-5 (at more extreme values, you might start having pascalian worries), and instead the discussion hinges on issues like tractability, pop ethics, etc.

Risk share seems more important (e.g. how much more worrying is AI than nuclear war?), yet these comparative judgements can be generally made in relative terms, without having to cash out the absolute values.

Comment by gregory_lewis on Leverage Research: reviewing the basic facts · 2018-08-05T17:47:05.220Z · score: 30 (27 votes) · EA · GW

[My views only]

Although few materials remain from the early days of Leverage (I am confident they acted to remove themselves from wayback, as other sites link to wayback versions of their old documents which now 404), there are some interesting remnants:

  • A (non-wayback) website snapshot from 2013
  • A version of Leverage's plan
  • An early Connection Theory paper

I think this material (and the surprising absence of material since) speaks for itself - although I might write more later anyway.

Per other comments, I'm also excited by the plan of greater transparency from Leverage. I'm particularly eager to find out whether they still work on Connection Theory (and what the current theory is), whether they addressed any of the criticism (e.g. 1, 2) levelled at CT years ago, whether the further evidence and argument mentioned as forthcoming in early documents and comment threads will materialise, and generally what research (on CT or anything else) have they done in the last several years, and when this will be made public.

Comment by gregory_lewis on EA Forum 2.0 Initial Announcement · 2018-07-23T15:45:00.525Z · score: 3 (3 votes) · EA · GW

Relatedly, some comments could be marked as "only readable by the author", because it's a remark about sensitive information. For example, feedback on someone's writing style or a warning about information hazards when the warning itself is also an information hazard. A risk of this feature is that it will be overused, which reduces how much information is spread to all the readers.

Forgive me if I'm being slow, but wouldn't private messages (already in the LW2 codebase) accomplish this?

Comment by gregory_lewis on EA Forum 2.0 Initial Announcement · 2018-07-21T11:52:31.509Z · score: 6 (6 votes) · EA · GW

One solution would be to demand that every down-vote comes with a reason, to which the original poster can reply.

This has been proposed a couple of times before (/removing downvotes entirely), and I get the sentiment than writing something and having someone 'drive-by-downvote' is disheartening/frustrating (it doesn't keep me up at night, but a lot of my posts and comments have 1-2 downvotes on them even if they end up net-positive, but I don't really have a steer as to what problem the downvoters wanted to highlight).

That said, I think this is a better cost to bear than erecting a large barrier for expressions of 'less of this'. I might be inclined to downvote some extremely long and tendentious line-by-line 'fisking' criticism, without having to become the target of a similar reply myself by explaining why I downvoted it. I also expect a norm of 'explaining your reasoning' will lead to lots of unedifying 'rowing with the ref' meta-discussions ("I downvoted your post because of X"/ "How dare you, that's completely unreasonable! So I have in turn downvoted your reply!")

Comment by gregory_lewis on Impact Investing - A Viable Option for EAs? · 2018-07-12T01:09:06.133Z · score: 3 (3 votes) · EA · GW

I'd also guess the social impact estimate would regress quite a long way to the mean if it was investigated to a similar level of depth as something like Cool Earth.

Comment by gregory_lewis on Ideas for Improving Funding for Individual EAs, EA Projects, and New EA Organizations · 2018-07-11T15:05:26.289Z · score: 5 (5 votes) · EA · GW

One key challenge I see is something like 'grant-making talent constraint'. The skills needed to make good grants (e.g. good judgement, domain knowledge, maybe tacit knowledge, maybe relevant network, possibly commissioning/governance/operations skill) are not commonplace, and hard to explicitly 'train' outside i) having a lot of money of your own to practise with, or ii) working in a relevant field (so people might approach you for advice). (Open Philanthropy's recent hiring round might provide another route, but places were limited and extraordinarily competitive).

Yet the talents needed to end up at (i) or (ii) are somewhat different, as are the skills to acquire: neither (e.g.) having a lot of money and being interested in AI safety, nor being an AI safety researcher oneself, guarantee making good AI safety grants; time one spends doing either of these things is time one cannot dedicate to gaining grant-making experience.

Dividing this labour (as the suggestions in the OP point towards) seem the way to go. Yet this can only get you so far if 'grantmaking talent' is not only limited among people with the opportunity to make grants, but limited across the EA population in general. Further, good grant-makers will gravitate to the largest pools of funding (reasonably enough, as this is where their contribution has the greatest leverage). This predictably leads to gaps in the funding ecosystem where 'good projects from the point of view of the universe' and 'good projects from the point of view of the big funders' subtly differ: I'm not sure I agree with the suggestions in the OP (i.e. upskilling people, new orgs), but I find Carl Shulman's remarks here persuasive.

Comment by gregory_lewis on The Values-to-Actions Decision Chain: a lens for improving coordination · 2018-07-11T06:14:39.291Z · score: 2 (2 votes) · EA · GW

I agree history generally augurs poorly for those who claim to know (and shape) the future. Although there are contrasting positive examples one can give (e.g. the moral judgements of the early Utilitarians were often ahead of their time re. the moral status of women, sexual minorities, and animals), I'm not aware of a good macrohistorical dataset that could answer this question - reality in any case may prove underpowered.

Yet whether or not in fact things would change with more democratised decision-making/intelligence gathering/ etc., it remains an open question whether this would be a better approach. Intellectual progress in many areas is no longer an amateur sport (see academia, cf. ongoing professionalisation of many 'bits' of EA, see generally that many important intellectual breakthroughs have historically been made by lone figures or small groups versus more swarm-intelligence-esque methods), and there's a 'clownside' risk of lot of enthusiastic, well-meaning, but inexperienced people making attempts that add epistemic heat rather than light (inter alia). The bar to appreciate 'X is an important issue' may be much lower than 'can contribute usefully to X'.

A lot seems to turn on whether the relevant problems are more high serial depth (favouring intensive effort) high threshold (favouring potentially-rare ability) or broader and relatively shallower, favouring parallelization. I'd guess relevant 'EA open problems' are a mix, but this makes me hesitant for there to be a general shove in this direction.

I have mixed impressions about the items you give below (which I appreciate was meant more as quick illustration than some 'research agenda for the most important open problems in EA'). Some I hold resilient confidence the underlying claim is false, for more I am uncertain yet I suspect progress on answering these questions (/feel we could punt on these for our descendants to figure out in the long reflection). In essence, my forecast is that this work would expectedly tilt the portfolios, but not so much to be (what I would call) a 'cause X' (e.g. I can imagine getting evidence which suggests we should push more of a global health portfolio to mental health - or non-communicable disease - but not something as decisive where we think we should sink the entire portfolio there and withdraw from AMF/SCI/etc.)

Comment by gregory_lewis on The Values-to-Actions Decision Chain: a lens for improving coordination · 2018-07-04T10:14:18.300Z · score: 1 (1 votes) · EA · GW

Sorry for being unclear. I've changed the sentence to (hopefully) make it clearer. The idea was there could be other explanations for why people tend to gravitate to future stuff (group think, information cascades, selection effects) besides the balance of reason weighs on its side.

I do mean considerations like population ethics etc. for the second thing. :)

Comment by gregory_lewis on The Values-to-Actions Decision Chain: a lens for improving coordination · 2018-07-03T23:38:20.350Z · score: 3 (5 votes) · EA · GW

Excellent work. I hope you'll forgive me taking issue with a smaller point:

Given the uncertainty they are facing, most of OpenPhil's charity recommendations and CEA's community-building policies should be overturned or radically altered in the next few decades. That is, if they actually discover their mistakes. This means it's crucial for them to encourage more people to do local, contained experiments and then integrate their results into more accurate models. (my emphasis)

I'm not so sure that this is true, although it depends on how big an area you imagine will / should be 'overturned'. This also somewhat ties into the discussion about how likely we should expect to be missing a 'cause X'.

If cause X is another entire cause area, I'd be pretty surprised to see a new one in (say) 10 years which is similar to animals or global health, and even more surprised to see one that supplants long term future. My rationale for this is I see broad funnel where EAs tend to move into the long term future/x-risk/AI, and once there they tend not to leave (I can think of a fair number of people who made the move from (e.g.) global health --> far future, but I'm not aware of anyone who moved from far future --> anything else). There are also people who have been toiling in the long term future vinyard for a long time (e.g. MIRI), and the fact we do not see many people moving elsewhere suggests this is pretty stable attractor.

There are other reasons for a cause area being a stable attractor besides all reasonable roads lead to it. That said, I'd suggest one can point to general principles which would somewhat favour this (e.g. the scope of the long term future, that the light cone commons, stewarded well, permits mature moral action in the universe to whatever in fact has most value, etc.) I'd say similar points to a lesser degree to apply to the broad landscape of 'on reflection moral commitments', and so the existing cause areas mostly exhaust this moral landscape.

Naturally, I wouldn't want to bet the farm on what might prove overconfidence, but insofar as it goes it supplies less impetus for lots of exploratory work of this type. At a finer level of granulariy (and so a bit further down your diagram), I see less resilience (e.g. maybe we should tilt the existing global poverty portfolio more one way or the other depending how the cash transfer literature turns out, maybe we should add more 'avoid great power conflict' to the long term future cause area, etc.) Yet I still struggle to see this adding up to radical alteration.

Comment by gregory_lewis on Informational hazards and the cost-effectiveness of open discussion of catastrophic risks · 2018-07-03T22:47:53.130Z · score: 4 (4 votes) · EA · GW

0: We agree potentially hazardous information should only be disclosed (or potentially discovered) when the benefits of disclosure (or discovery) outweigh the downsides. Heuristics can make principles concrete, and a rule of thumb I try to follow is to have a clear objective in mind for gathering or disclosing such information (and being wary of vague justifications like ‘improving background knowledge’ or ‘better epistemic commons’) and incur the least possible information hazard in achieving this.

A further heuristic which seems right to me is one should disclose information in the way that maximally disadvantages bad actors versus good ones. There are a wide spectrum of approaches that could be taken that lie between ‘try to forget about it’, and ‘broadcast publicly’, and I think one of the intermediate options is often best.

1: I disagree with many of the considerations which push towards more open disclosure and discussion.

1.1: I don’t think we should be confident there is little downside in disclosing dangers a sophisticated bad actor would likely rediscover themselves. Not all plausible bad actors are sophisticated: a typical criminal or terrorist is no mastermind, and so may not make (to us) relatively straightforward insights, but could still ‘pick them up’ from elsewhere.

1.2: Although a big fan of epistemic modesty (and generally a detractor of ‘EA exceptionalism’), EAs do have an impressive track record in coming up with novel and important ideas. So there is some chance of coming up with something novel and dangerous even without exceptional effort.

1.3: I emphatically disagree we are at ‘infohazard saturation’ where the situation re. Infohazards ‘can’t get any worse’. I also find it unfathomable ever being confident enough in this claim to base strategy upon its assumption (cf. eukaryote’s comment).

1.4: There are some benefits to getting out ‘in front’ of more reckless disclosure by someone else. Yet in cases where one wouldn’t want to disclose it oneself, delaying the downsides of wide disclosure as long as possible seems usually more important, and so rules against bringing this to an end by disclosing yourself save in (rare) cases one knows disclosure is imminent rather than merely possible.

2: I don’t think there’s a neat distinction between ‘technical dangerous information’ and ‘broader ideas about possible risks’, with the latter being generally safe to publicise and discuss.

2.1: It seems easy to imagine cases where the general idea comprises most of the danger. The conceptual step to a ‘key insight’ of how something could be dangerously misused ‘in principle’ might be much harder to make than subsequent steps from this insight to realising this danger ‘in practice’. In such cases the insight is the key bottleneck for bad actors traversing the risk pipeline, and so comprises a major information hazard.

2.2: For similar reasons, highlighting a neglected-by-public-discussion part of the risk landscape where one suspects information hazards lie has a considerable downside, as increased attention could prompt investigation which brings these currently dormant hazards to light.

3: Even if I take the downside risks as weightier than you, one still needs to weigh these against the benefits. I take the benefit of ‘general (or public) disclosure’ to have little marginal benefit above more limited disclosure targeted to key stakeholders. As the latter approach greatly reduces the downside risks, this is usually the better strategy by the lights of cost/benefit. At least trying targeted disclosure first seems a robustly better strategy than skipping straight to public discussion (cf.).

3.1: In bio (and I think elsewhere) the set of people who are relevant setting strategy and otherwise contributing to reducing a given risk is usually small and known (e.g. particular academics, parts of the government, civil society, and so on). A particular scientist unwittingly performing research with misuse potential might need to know the risks of their work (likewise some relevant policy and security stakeholders), but the added upside to illustrating these risks in the scientific literature is limited (and the added downsides much greater). The upside of discussing them in the popular/generalist literature (including EA literature not narrowly targeted at those working on biorisk) is limited still further.

3.2: Information also informs decisions around how to weigh causes relative to one another. Yet less-hazardous information (e.g. the basic motivation given here or here, and you could throw in social epistemic steers from the prevailing views of EA ‘cognoscenti’) is sufficient for most decisions and decision-makers. The cases where this nonetheless might be ‘worth it’ (e.g. you are a decision maker allocating a large pool of human or monetary capital between cause areas) are few and so targeted disclosure (similar to 3.1 above) looks better.

3.3: Beyond the direct cost of potentially giving bad actors good ideas, the benefits of more public discussion may not be very high. There are many ways public discussion could be counter-productive (e.g. alarmism, ill-advised remarks poisoning our relationship with scientific groups, etc.). I’d suggest the examples of cryonics, AI safety, GMOs and other lowlights of public communication of policy and science are relevant cautionary examples.

4: I also want to supply other more general considerations which point towards a very high degree caution:

4.1: In addition to the considerations around the unilateralist’s curse offered by Brian Wang (I have written a bit about this in the context of biotechnology here) there is also an asymmetry in the sense that it is much easier to disclose previously-secret information than make previously-disclosed information secret. The irreversibility of disclosure warrants further caution in cases of uncertainty like this.

4.2: I take the examples of analogous fields to also support great caution. As you note, there is a norm in computer security of ‘don’t publicise a vulnerability until there’s a fix in place’, and initially informing a responsible party to give them the opportunity to to do this pre-publication. Applied to bio, this suggests targeted disclosure to those best placed to mitigate the information hazard, rather than public discussion in the hopes of prompting a fix to be produced. (Not to mention a ‘fix’ in this area might prove much more challenging than pushing a software update.)

4.3: More distantly, adversarial work (e.g. red-teaming exercises) is usually done by professionals, with a concrete decision-relevant objective in mind, with exceptional care paid to operational security, and their results are seldom made publicly available. This is for exercises which generate information hazards for a particular group or organisation - similar or greater caution should apply to exercises that one anticipates could generate information hazardous for everyone.

4.4: Even more distantly, norms of intellectual openness are used more in some areas, and much less in others (compare the research performed in academia to security services). In areas like bio, the fact that a significant proportion of the risk arises from deliberate misuse by malicious actors means security services seem to provide the closer analogy, and ‘public/open discussion’ is seldom found desirable in these contexts.

5: In my work, I try to approach potentially hazardous areas as obliquely as possible, more along the lines of general considerations of the risk landscape or from the perspective of safety-enhancing technologies and countermeasures. I do basically no ‘red-teamy’ types of research (e.g. brainstorm the nastiest things I can think of, figure out the ‘best’ ways of defeating existing protections, etc.)

(Concretely, this would comprise asking questions like, “How are disease surveillance systems forecast to improve over the medium term, and are there any robustly beneficial characteristics for preventing high-consequence events that can be pushed for?” or “Are there relevant limits which give insight to whether surveillance will be a key plank of the ‘next-gen biosecurity’ portfolio?”, and not things like, “What are the most effective approaches to make pathogen X maximally damaging yet minimally detectable?”)

I expect a non-professional doing more red-teamy work would generate less upside (e.g. less well networked to people who may be in a position to mitigate vulnerabilities they discover, less likely to unwittingly duplicate work) and more downside (e.g. less experience with trying to manage info-hazards well) than I. Given I think this work is usually a bad idea for me to do, I think it’s definitely a bad idea for non-professionals to try.

I therefore hope people working independently on this topic approach ‘object level’ work here with similar aversion to more ‘red-teamy’ stuff, or instead focus on improving their capital by gaining credentials/experience/etc. (this has other benefits: a lot of the best levers in biorisk are working with/alongside existing stakeholders rather than striking out on one’s own, and it’s hard to get a role without (e.g.) graduate training in a relevant field). I hope to produce a list of self-contained projects to help direct laudable ‘EA energy’ to the best ends.

Comment by gregory_lewis on Informational hazards and the cost-effectiveness of open discussion of catastrophic risks · 2018-07-03T22:45:21.218Z · score: 13 (8 votes) · EA · GW

Thanks for writing this. How best to manage hazardous information is fraught, and although I have some work in draft and under review, much remains unclear - as you say, almost anything could have some some downside risk, and never discussing anything seems a poor approach.

Yet I strongly disagree with the conclusion that the default should be to discuss potentially hazardous (but non-technical) information publicly, and I think your proposals of how to manage these dangers (e.g. talk to one scientist first) generally err too lax. I provide the substance of this disagreement in a child comment.

I’d strongly endorse a heuristic along the lines of, “Try to avoid coming up with (and don’t publish) things which are novel and potentially dangerous”, with the standard of novelty being a relatively uninformed bad actor rather than an expert (e.g. highlighting/elaborating something dangerous which can be found buried in the scientific literature should be avoided).

This expressly includes more general information as well as particular technical points (e.g. “No one seems to be talking about technology X, but here’s why it has really dangerous misuse potential” would ‘count’, even if a particular ‘worked example’ wasn’t included).

I agree it would be good to have direct channels of communication for people considering things like this to get advice on whether projects they have in mind are wise to pursue, and to communicate concerns they have without feeling they need to resort to internet broadcast (cf. Jan Kulveit’s remark).

To these ends, people with concerns/questions of this nature are warmly welcomed and encouraged to contact me to arrange further discussion.

Comment by gregory_lewis on EA Hotel with free accommodation and board for two years · 2018-06-21T08:59:28.368Z · score: 10 (13 votes) · EA · GW

I'm getting tired of the 'veganism is only a minor inconvenience' point being made:

  • V*ganism shows very high 'recidivism' rates in the general population. Most people who try to stop eating meat/animal products usually end up returning to eat these things before long.
  • The general public health literature on behaviour/lifestyle change seldom says these things are easy/straightforward to effect.
  • When this point is made by EAAs, there is almost always lots of EAs who they say, 'No, actually, I found going v*gan really hard', or, 'I tried it but I struggled so much I felt I had to switch back'.
  • (The selection effect that could explain why 'ongoing v*gans' found the change only a minor convenience is left as an exercise to the reader).

I don't know many times we need to rehearse this such that people stop saying 'V*ganism is a minor inconvenience'. But I do know it has happened enough times that other people in previous discussions have also wondered how many times this needs to be rehearsed such that people stop saying this.

Of course, even if it is a major inconvenience (FWIW, I'm a vegetarian, and I'd find the relatively small 'step further' to be exclusively vegan a major inconvenience), this could still be outweighed by other factors across the scales (there's discussion to be had 'relative aversion', some second-order stuff about appropriate cooperative norms, etc. etc.). Yet discussions of the cost-benefit proceed better if the costs are not wrongly dismissed.

Comment by gregory_lewis on EA Hotel with free accommodation and board for two years · 2018-06-05T22:42:02.990Z · score: 11 (13 votes) · EA · GW

Bravo!

I'm not so sure whether this is targetting the narrowest constraint for developing human capital in EA, but I'm glad this is being thrashed out in reality rather than by the medium of internet commentary.

A more proximal worry is this. The project seems to rely on finding a good hotel manager. On the face of it, this looks like a pretty unattractive role for an EA to take on: it seems the sort of thing that demands quite a lot of operations skill, altready in short supply - further, 20k is just over half the pay of similar roles in the private sector (and below many unis typical grad starting salary), I imagine trying to run a hotel (even an atypical one) is hard and uninspiring work with less of the upsides the guests will enjoy, and you're in a depressed seaside town.

Obviously, if there's already good applicants, good for them (and us!), and best of luck going forward.

Comment by gregory_lewis on Why Groups Should Consider Direct Work · 2018-05-28T19:41:42.549Z · score: 7 (11 votes) · EA · GW

I'd be hesitant to recommend direct efforts for the purpose of membership retention, and I don't think considerations on these lines should play a role in whether a group should 'do' direct work projects. My understanding is many charities use unskilled volunteering opportunities principally as a means to secure subsequent donations, rather than the object level value of the work being done. If so, this strikes me as unpleasantly disingenuous.

I think similar sentiments would apply if groups offered 'direct work opportunities' to their membership in the knowledge they are ineffective but for their impact on recruitment and retention (or at least, if they are going to do so, they should be transparent about the motivation). If (say) it just is the case the prototypical EA undergraduate is better served reallocating their time from (e.g.) birthday fundraisers to 'inward looking' efforts to improve their human capital, we should be candid about this. I don't think we should regret cases where able and morally laudable people are 'put off' EA because they resiliently disagree with things we think are actually true - if anything, this seems better for both parties.

Whether the 'standard view' expressed in the introduction is true (i.e. "undergrads generally are cash- and expertise- poor compared to professionals, and so their main focus should be on self-development rather than direct work") is open to question. There are definitely exceptions for individuals: I can think of a few undergraduates in my 'field' who are making extremely helpful contributions.

Yet this depends on a particular background or skill set which would not be in common among a local group. Perhaps the forthcoming post will persuade me otherwise, but it seems to me that the 'bar' for making useful direct contributions is almost always higher than the 'bar' for joining an EA student group, and thus opportunities for corporate direct work which are better than standard view 'indirect' (e.g. recruitment) and 'bide your time' (e.g. train up in particular skills important to your comparative advantage) will be necessarily rare.

Directly: if a group like EA Oxford could fund-raise together to produce $100 000 for effective charities (double the donations reported across all groups in the LEAN survey), or they could work independently on their own development such that one of their members becomes a research analyst at a place at Open Phil in the future, I'd emphatically prefer they take the latter approach.

The person-affecting value of existential risk reduction

2018-04-13T01:44:54.244Z · score: 36 (29 votes)

How fragile was history?

2018-02-02T06:23:54.282Z · score: 11 (13 votes)

In defence of epistemic modesty

2017-10-29T19:15:10.455Z · score: 48 (44 votes)

Beware surprising and suspicious convergence

2016-01-24T19:11:12.437Z · score: 34 (40 votes)

At what cost, carnivory?

2015-10-29T23:37:13.619Z · score: 5 (5 votes)

Don't sweat diet?

2015-10-22T20:15:20.773Z · score: 11 (13 votes)

Log-normal lamentations

2015-05-19T21:07:28.986Z · score: 11 (13 votes)

How best to aggregate judgements about donations?

2015-04-12T04:19:33.582Z · score: 4 (4 votes)

Saving the World, and Healing the Sick

2015-02-12T19:03:05.269Z · score: 12 (12 votes)

Expected value estimates you can take (somewhat) literally

2014-11-24T15:55:29.144Z · score: 4 (4 votes)