The Mentaculus

Trade-Offs In Evolvability

2012-01-27T00:23:00.000-05:00

"[T]he main and broadly applicable effect of fluctuating selection on the evolution of gene regulatory networks that allow for a feedback loop is selection for specific system dynamics that confer an increased evolvability. Increased evolvability mainly results from evolution of system parameters controlling the feedback loop, into a nonlinear regime, where both phenotypic diversity and the amount of phenotypic shift caused by individual mutations are increased."

More here. To the extent that you expect your environment to change a lot (i.e., undergo "fluctuating selection"), you should prefer meta-level approaches which allow you to change your object-level strategy more quickly and less costly. To the extent that you expect your environment to remain constant, this ability and propensity to change will be a hindrance.

A Separation

2012-01-21T01:24:00.001-05:00

Finally it has come out in Bethesda! Spoiler alert, you can view it as a delectable set of plausible moral quandaries wrapped up in a family drama. You can also view it as a demonstration of how external stressors are what really kill relationships. My favorite line was, naturally, "what is wrong is wrong, no matter who said it or where it's written."

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Completely unrelated, this is the funniest thing I've read so far this calendar year. Anything for science.

Seven Ideas From 2011

2012-01-01T16:21:00.000-05:00

One Idea For Trepidation

1) U.S. Life Expectancies Stagnate: In more than 20% of counties, life expectancies for women declined between 1997 and 2007, driven largely by increased rates of smoking and high blood pressure. In some senses this is not unexpected, as the century-long gains in lifespan in developed nations have been more a story of asymptotically approaching the maximum human lifespan rather than pushing it back. And healthiness during one's lifespan is to some people the most important measure. Still, this is a major worry, and all of the other ideas on this list must be tainted by this one. (see here and here for more)

county-wide change in life expectancies over recent decades, left is males and right is females, green is positive and red is negative; doi:10.1371/journal.pmed.0050066

Four Ideas For Optimism

2) Chip-Based Neuronal Nets: Memristors are circuit elements that can "remember" their resistance state even in the absence of curent. They open up a wealth of potential applications, including directly mimicking synaptic learning rules. The first implementation of the memristor is now slated for commercial release in less than two years. (see here, here, and here for more)

certain memristor architectures can store the topology of a maze in the state of its switches and thus allow all of the memristors to participate in the path calculation at once; http://arxiv.org/pdf/1103.0021v2

3) Altering DNA More Precisely. Zinc finger nucleases are proteins that can be engineered to target and cut a particular DNA sequence, thus allowing for manipulation of (human) genomes. This year a set of breakthroughs were announced which allow for researchers to query the specificity of ZFN's across the genome. This is crucial, because you really want to minimize any chance for error when you might accidentally mutate a tumor suppressor gene. The only clinical trial I know of with these is for HIV, which seems to have had some promising albeit highly preliminary results. (see here, here, and here for more)

a model of a zinc finger nuclease; doi:10.1186/1471-2164-12-83

4) Downloadable Sneakers. What will be the "killer app" of 3D printing that makes everybody want one as badly as they first wanted a personal computer? It's unclear, but the initial spread of the tech is already upon us, and the events of this year have me more convinced that it will prove similarly disruptive. (see here and here for more)

photo by photon

5) The End Of Drunk Driving. What if your smartphone could double as your chauffeur? Amazingly, we already have the basic autonomous driving capabilities. The most important reasons to care about this are a) the number of lives it could save and b) the amount of time it could free up. Yes, there are plenty of downsides, but they must be weighed at every step against these upsides. (see here, here, and here for more)

photo by jurvetson

Two Ideas To Think About

6) The Dimensions Of The DSM-5. To what extent will the dimensional approach to mental disorders make it into the next draft of the bible of psychiatry? This is not purely academic. Rating patients by the significance of their disorder would help eliminate arbitrary thresholds between the healthy and pathological. But if the switch is made too soon, before the levels can be validated, then it could turn into a bonanza of overmedication. (see here and here for more)

photo by ecstaticist

7) The Apogee Of The Corporation. As self-employment rises and technology advances, a smaller and smaller chunk of economic activity is being dictated by firms. Our very notions of the corporation and the employee seem to be on their way out, and perhaps they will be replaced by something that makes more sense for the society of tomorrow. (see here and here for more)

a network representation of strongly connected transnational corporations; doi:10.1371/journal.pone.0025995; how long can or will they last?

"It Teaches You How To Think"

2011-12-28T15:24:00.000-05:00

Many pursuits apparently fall under this purview: programming, economics, history, philosophy, english, physics, math (often called "mental weightlifting"), sociology, classics, engineering, college (esp. the liberal arts), grad school, law school, medical school, business school, multi-level marketing, neuro-linguistic programming, and chess, to name a few.

I'm not at all opposed to this idea and I do favor "raising the sanity waterline." But I'd like to see the claims evaluated more systematically against 1) how beneficial the most common alternative activity that the median person who would otherwise invest in these pursuits would be and 2) how beneficial the most useful alternative activity that the median person who would otherwise invest in these subjects could be.

Surely there is not enough time, given our current healthspans, to invest ourselves in all or even most of these activities. So, for those of us who do value good "thinking" skills, how should we choose?

(The above link anecdotes do not prove much, as it is possible to make nearly any point with a little google-fu, but I have read and heard this sort of statement repeated over and over to the point that it seems to me to be nigh-gospel. If anyone knows of a systematic way to determine whether these are commonly held beliefs, I'm all ears.)

The Best Movies Of 2011

2011-12-26T18:00:00.000-05:00

In reverse order: 5) Hugo (not bad, but fragmented and too long, e.g. they could have cut out the station inspector storyline, which relied upon sadly hackneyed deterministic developmental psychology), 4) HP7P2 (technically stunning, but Radcliffe just doesn't do it for me), 3) Drive (I do sympathize with the "too violent" critiques, but I loved the pacing), 2) Warrior (I'm slacking), and 1) A Separation (still not out in my area).

All in all this has been a down year for offerings on the big screen. Currently there are only 5 movies in the top 250, and that number will surely drop as they come out on video and the attrition of time does its damage. I predict only 3 movies from this year will still remain on the list come this time next year. Compare that to 7 for 2009 and 8 for 2010. Hollywood needs to stop investing so heavily in sequels!

Six Thoughts On Rewatchability

2011-12-24T18:00:00.000-05:00

1) Let's consider movies that are driven at least in part by plot uncertainty. Watching such a movie a second time is by no means necessarily worse (e.g., many enjoy Inception even more the second time through), but it is different.

For example, watching a movie could really force you to question some of your beliefs and adjust your corresponding models of the world. This could be a very worthwhile experience, yet you could quite reasonably expect that watching the movie again would be unlikely to yield the same reward.

In such a case, it'd be fair to say that the experience you derived from that particular movie (i.e., watching it and thinking about it after) was better than the experience you derived from any other, yet you still might not especially want to watch it a second time.

2) Touching the Void is an example of such a movie, for me. Watching it meant a lot to me and I have thought about it often since doing so, but I wouldn't want to watch it again in the near future.

3) I'd agree that, all things equal, wanting to re-watch a movie is a proxy for how much you got out of it. But I don't think people should have to "prove" that they like a movie by watching it over and over.

4) And further, I don't think the metric is all that good of a proxy. I doubt that there'd be a very high correlation between the movies with the highest average subjective experience rating and the ones that people watch over and over.

This is because I expect people ultimately get the most out of movies that challenge them, and in the moment they are less likely to choose to re-watch such a movie, because of the insidious effects of delay discounting.

5) The counter is that people are too likely to be signaling when they merely say what their favorite movie is, which is why we need some measure of how people actually behave. I do sympathize with this argument.

For example, people tend to watch a lot of comedies, yet there are few comedies in the top 250 and actors in comedies hardly ever win awards. Yes, some of this is because humor does not cut across cultures well. But surely on some level comedies are underrated because liking them does not allow us to as effectively signal our sophistication.

6) The main upside to any behavioral metric is that it slices through the noisy opinion market. The downsides are that we might not be measuring what we think we are, and, to the extent that the metric is widely held, it can lead to costly gaming.

Full Disclosure: When a movie that I have seen more than once is brought up in conversation, I will almost always brag about how many times I have seen it, to collect some street cred.

Disease Olympics

2011-12-24T01:10:00.001-05:00

This is my favorite new phrase, which I first heard in this article by Carl Bialik about the ethics of using sometimes tenuous statistics to rouse advocacy for diseases. It is used to refer to situations in which different maladies "compete" against one another for funding, attention, empathy, and the like.

As Otis Brawley points out, in many avenues of biomedical research, disease olympics relies upon a false dichotomy. For example, the antimicrotubule agent estramustine was the first targeted therapy for breast cancer cells, for which it failed. Instead, it became the first (and until recently, only) chemotherapy agent for prostate cancer. Sites like prostatecancerpetition.org, although laudable in some respects, often neglect these crucial second-order effects.

I love this phrase because it articulates what was previously an unconscious anxiety of mine, its meaning is intuitively obvious (i.e., it doesn't propagate "insider baseball"), and it addresses an important issue. One thing I don't like about the phrase is that the word "olympics" is usually capitalized. I worry that this will hurt its memetic staying power, because capitalization often perturbs the flow of a sentence.

Yawn Contagion Increases With Social Bond

2011-12-11T11:23:00.001-05:00

The social bond categories are 0 = strangers, 1 = acquaintances, 2 = friends, and 3 = kin and life partners, more details here. Perhaps this would be a good litmus test for how close you are with someone?

Note that merely reading about yawning is often sufficient to elicit a yawn.

Reference

Norscia I, Palagi E (2011) Yawn Contagion and Empathy in Homo sapiens. PLoS ONE 6(12): e28472. doi:10.1371/journal.pone.0028472

Time Estimation Correlates With Math Smarts

2011-12-08T23:30:00.001-05:00

Details here. For the five tone durations, the mean correlation coefficient was 0.59, and was still significant when the authors adjusted for a measure of general intelligence.

Suddenly "what time is it?" isn't such an innocuous question.

Reference

Kramer P, Bressan P, Grassi M (2011) Time Estimation Predicts Mathematical Intelligence. PLoS ONE 6(12): e28621. doi:10.1371/journal.pone.0028621

Reviewing Newt's Reviews

2011-12-07T22:25:00.001-05:00

That is a histogram of his Amazon book ratings, and here is the source (HT TC). He is quite the pushover, and the above is a classic example of why a good rating system must rate the raters or suffer from bias. What about the content? Two trends stick out:

1) He is highly positive. Among his most common adjectives are "masterful," "remarkable," and "brilliant." Even when he gives a book four stars, he rarely says anything negative, and in fact it's usually not clear why books didn't get the top score of five.

2) He is highly technical. By this I mean that the majority of his sentences are devoted to strict summary rather than analysis. This makes sense, as it is probably smarter for a politician to say something obviously factual (and thus unassailable) than to take a risk.

(A Big) Part Of Science Is Publicizing Your Results

2011-11-29T19:55:00.001-05:00

I’ve actually seen this sort of thing—claiming a result while backing off from claiming it, circulating a writeup to a few people but not really circulating it, burying an observation where no one will find it—happen over and over again in science, and its invariable effect is to leave fields in a state of utter confusion. There’s an excellent reason why, 350 years ago, science moved from the “announce-by-cryptogram” model to the model of rapid, widespread dissemination of research. And I’m not willing to forsake the attendant gains in human progress, just because some commenters here seem to enjoy the romantic image of someone stuffing the proof of a theorem into a bottle, throwing the bottle into the ocean, then going back to collecting seashells (or whatever), secure in the knowledge that the history of mathematics will need to be rewritten once the bottle washes up on some distant beach a thousand years later. Sorry, not how it works in this civilization.

That is yet more interestingness by Scott Aaronson in the comments of his blog. There is a thin line here, no doubt, as too much marketing and not enough meat is anathema to progress. But yes, in order for our results to be useful, we must attempt to ensure that they are heard by people who can use them. One way to do this is to split disparate ideas into separate, shorter papers, even though that practice is sometimes disparaged.

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Of the well-subscribed to bloggers I read, Aaronson is one of the few who consistently responds to commenters. He also seems to have grown quite tired of his commenters, as he has threatened to shut down his blog more than once. Perhaps long-lasting success in the blogosphere selects for people who do not respond to comments.

What Does "Statistical" Mean To You?

2011-11-19T20:08:00.001-05:00

What exactly do [the authors] mean by a quantum state being “statistically interpretable”?... Basically, [the authors] call something “statistical” if two people, who live in the same universe but have different information, could rationally disagree about it.... As for what “rational” means, all we’ll need to know is that a rational person can never assign a probability of 0 to something that will actually happen.

To illustrate, suppose a coin is flipped, and you (but not I) get a tip from a reliable source that the coin probably landed heads. Then you and I will describe the coin using different probability distributions, but neither of us will be “wrong” or “irrational”, given the information we have.

That's Scott Aaronson discussing a paper about the nature of quantum states. Googling "define statistical," I see, unsurprisingly, "of or relating to the use of statistics," and then googling "define statistics," I see "the practice or science of collecting and analyzing numerical data in large quantities."

To me, the large quantities bit emphasizes that the role of statistics is to parse signal from noise, which is only possible with more than two data points (or, to be fair, some assumptions). So, I'd consider the authors' use of the word statistical to be sort of non-standard, because it seems to be able to be used for interpreting just one quantum state.

Quite possibly this is actually standard use of the word statistical among certain physicists, which would make this yet another example of why you shouldn't assume that terminology is at all consistent across disciplines.

The Self-Reinforcing Effects Of Ignorance

2011-11-13T21:04:00.001-05:00

Outside of baseball there had been, for decades, an intellectual revolt, led by a free thinker named Bill James, devoted to creating new baseball knowledge. The movement generated information of value in the market for baseball players, but the information went ignored by baseball insiders. The market’s willful ignorance had a self-reinforcing quality: the longer the information was ignored, the less credible it became. After all, if this stuff had any value, why didn’t baseball insiders pay it any attention? To see the value in what Bill James and his crowd were up to you had first to believe that a market as open and transparent as the market for baseball players could ignore valuable information—that is, that it could be irrational.

That's Michael Lewis, more here. In particular, to find value in old, unorthodox stances, you have to believe in the possibility of status quo bias.

A New Solution To A Grid Coloring Challenge

2011-11-06T18:14:00.000-05:00

It is here, as explained by Alexandre Thiery. The challenge is to find a four color schema such that a 17 x 17 grid has no rectangle with the same four colors at each corner. The best known solution, shown below, has three rectangles. They are denoted by the black lines.

Who can find a schema with no such rectangles? Does one exist?

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The fact that I enjoy this so much indicates some sort of bias towards colorful things. Or maybe just pretty things, more generally.

Casnocha On Felten On Loyalty vs Universality

2011-10-05T23:59:00.001-05:00

[L]oyalty is essential in human affairs. Without loyalty, trust disappears and relationships crumble. The problem is, loyalties conflict. For example, when friends commit immoral acts, should you stand by them (loyal to friend) or uphold moral principles (loyal to principle)?...

What's the difference between a little and a lot of wickedness? That's up to you. Figuring it out is an example of a tough decision Felten says we need to make, case by case.

More here. Loyalty vs universality is great example of a trade-off that comes up often and leads to tough decisions. Every time you spend luxury money on yourself or friends that could have gone to an effective charity or basic research, you're implicitly choosing loyalty. Two thoughts:

1) Contra Felten, I'm reluctant to say that decisions for any trade-off must be made on a case by case basis, because there are huge gains to be reaped in cognitive efficiency by creating rules and following them.

2) The trade-off can interact with some now vs more later. That is, being loyal to your associates and thus building connections in the short run can help you achieve your goals in the long run. These long run goals, in turn, may be designed to make a larger set of people (or even "everyone") better off, thus justifying a universally beneficial motive.

Yet, how many historical atrocities were once rationalized with this logic? If you really favor the welfare of everyone equally, it's probably safer to act that way while on the way to your goals, instead of planning to do so in some future world.

The Value Of Thinking About Rating Systems

2011-09-26T16:54:00.002-05:00

A new project I have just started is going to generate personalized movie ratings for users. The way it works is as follows. You rate the movies you have seen. Then the system finds other users with similar tastes to extrapolate how much the you will like some other movies. It is currently written entirely in Python.

That's from Sergey Brin's 1996 resume. Prior, of course, to co-founding Google.

Correlation, causation, or aberration? You tell me.

Can You Keep Your Job While Innovating?

2011-09-13T21:39:00.000-05:00

Justin Lall says, at least in the context of competitive bridge, basically no. This is similar to NFL coaches not going for it on fourth down as often as they should, but a little bit more nuanced.

The situation in bridge is less dire, as percentage plays are respected, and the math is often easily demonstrable. However, a large part of becoming a great bridge player, good enough to be hired to play on professional teams, is having excellent judgement about when situations to go against conventional wisdom or A priori odds....

The biggest problem is that you are not just thinking about a bridge problem anymore, that’s the easy part, you’re deciding if making this play is worth possibly getting fired, get a bad reputation, maybe never get hired again and be forced to get a 9-5 job that pays much less.

You can generalize his argument to the claim that some now vs more later trade-offs are a superset of exploration vs exploitation trade-offs.

I agree. In the short run people who follow the status quo have an edge, especially in the absence of good long run indicators.

One prediction of this is that if 1) the football season were longer, or 2) instantaneous ratings for the probability that a team would win became standard (like "pawn units" in chess), more coaches would go for it on fourth down.

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If you think this post was just an elaborate excuse to use the word "superset," you know too much.

Is One Willpower Trade-Off Fundamental?

2011-09-05T21:56:00.000-05:00

[T]he authors offer no systematic account of the trade-offs the brain must make among goals that differ in their likelihood of success, their time horizons and their evolutionary impact. The old joke about the man in front of a firing squad who refuses the customary last cigarette because he’s trying to quit reminds us that deferring a reward does not always make sense....

That's from Steven Pinker's otherwise mostly positive review of Baumeister and Tierney's Willpower. The relevant trade-offs in my current schema are some now vs more later (delay discounting) and sure bet vs shot in the dark (probability discounting).

Mentioning both in the same sentence reminds me of an old question of whether these trade-offs are actually equivalent on some fundamental level. Green and Myerson's highly cited '04 review addresses this.

From one perspective, you can think of a lower probability for success on a task as indicating that it will need to be repeated more times, and thus take longer. On the flip side, you can think of a longer delay as indicating a lower chance that the expected reward will actually be received.

One problem with both of these theories is that for humans, the discounting rate differs between delay and probability with respect to amount. That is, smaller rewards lose value more quickly as delay increases, but larger rewards lose value more quickly as the odds against increases. Check out this figure for some data.

This amount finding remains contentious, because it has not replicated in studies of non-human animals. And in those studies, it looks like delay discounting could be the more fundamental force of the two.

Still, some intuition remains on the side of considering them as distinct trade-offs. I don't think you'd want to tell an out-of-luck gambler in Vegas that if they just play longer, they'll eventually win.

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After reading one of Baumeister's original papers, Tierney's exposition, Pinker's review, and Robert Kurzban's three published critiques, I am now in the curious situation of having devoured a fair number of words about a book without any inclination or intention to read the text itself.

Do I feel bad about this? Not really. I still think that the hegemony of the book is a bit anachronistic, and prefer the back-and-forth commentary that blog posts and edited articles provide.

But perhaps this is just a rationalization of my lack of willpower to actually close my computer screen and pick up a book.

Power To The Wiki People

2011-08-31T20:45:00.000-05:00

While reading Robert Kurzban's (mostly good) book Why Everyone (Else) Is a Hypocrite, I came across a fragment of a sentence which annoyed me.

Kurzban is in the midst of explaining a computer science topic when he writes, "according to Wikipedia, which I am usually hesitant to use, but will for this purpose," and then block quotes, starting with "creating a domain-specific language...".

As it turns out, Wikipedia is written by people. Rp, a Dutch software developer, added this sentence on April 24, 2008. The only difference between Rp's change and the current version is a superfluous "of course" which was removed on May 12, 2008. This is not hard to decipher based on a gander at the page's revision history. It took me about four minutes.

Listen, I recognize that Wikipedia is low status, which is why Kurzban had to express his hesitation to use it. But we all know how Wikipedia works now. People edit it. You aren't constrained to merely cite "Wikipedia", you can look back and see exactly which user wrote that passage first, and cite that user.

Some of my clever readers are probably already mentally defending the status quo by saying that some sentences or portions of articles have been edited so many times that it would be difficult to say who wrote them.

Yes, in very rare cases like The Iraq War this is the case, but it happens much less often than you'd expect. The vast majority of articles are edited in chunks of sentences, paragraphs, or sections, and these chunks are eminently traceable.

Perhaps the best thing about such a shift in citation norms is that it would help incentivize people to edit Wikipedia. If you think this is not an issue, you are sorely mistaken.

Consider the page on epigenetics. Inspired in part by Razib's manifesto about the growing importance of this topic, I have subscribed via RSS to the changes made to the page since January. What I expected were the vitriolic edit wars deserving of such an unfolding, important topic.

But I've seen nothing of the sort. In fact the page hasn't changed significantly since Team Cytokine Storm made some edits last November. In the meantime, how many words have been typed about epigenetics for publication elsewhere?

For example, in the past two months, there have been at least four academic reviews on topics in epigenetics (see here, here, here, and here). See for yourself--here is a pubmed search for "epigenetics review."

How many people will read these reviews? Do you think that more will read those reviews than will read the Wikipedia page? Is this a healthy division of labor?

nobody does homework on saturdays

Bottom Line: When quoting or referencing an article hosted on Wikipedia, cite the major user(s) that contributed, instead of just "Wikipedia."

Punishing Praise

2011-08-27T16:34:00.000-05:00

[B]ecause we tend to reward others when they do well and punish them when they do badly, and because there is regression to the mean, it is part of the human condition that we are statistically punished for rewarding others and rewarded for punishing them.

That's Daniel Kahneman, more here. Regression to the mean will occur in situations that involve at least some luck, which is to say, almost everywhere.

Luck seems especially inevitable once we consider that spontaneous fluctuations in your brain's dynamic states (as seen in fMRI BOLD responses) can help account for trial-to-trial variability in behavior.

One study found that the amount of pain that people feel following laser stimulation (equivalent to a pinprick) can be predicted (beyond 5% chance) based on baseline, spontaneous activity in certain brain regions three seconds before the stimulation. (pubmed, PNAS)

Another study found that 74% of the within-participant variability in a button press force task could be attributed to ongoing ﬂuctuations in neural activity. (pubmed)

In light of the fact that seemingly uncontrollable neural fluctuations play such an important role in behavior on any given attempt, punishing people for poor performance on small sample sizes seems particularly pernicious.

But then again, most punishment is probably not really intended to improve future performance, but rather to improve the mood and status of the punisher.

Are We More Like Chimps Or Bonobos?

2011-08-25T21:03:00.001-05:00

In Sex at Dawn, Ryan and Jethá argue that humans are more like bonobos. This is, in part, because we both 1) employ diverse sex positions, 2) have sex for non-reproductive ends, and 3) gaze into each other's eyes during sex (when this jives with #1).

In his review (pdf, OA), Ryan Ellsworth disputes their thesis and makes the case for the chimp model. He emphasizes that humans and chimps (but not bonobos) share "sex-based hierarchies, sex-biased cooperation and coalitions, and intergroup hostility."

I've only skimmed Sex at Dawn, but I find Ellsworth's review much more persuasive. I'm happy being chimp-like.

(photo credit to patries71)

Seven Thoughts On Rules And Willpower

2011-08-21T13:55:00.000-05:00

1) John Tierney discusses ego depletion, the idea that willpower is an (unconsciously) expendable resource. He relates it to trade-offs:

Once you’re mentally depleted, you become reluctant to make trade-offs, which involve a particularly advanced and taxing form of decision making.... To compromise is a complex human ability and therefore one of the first to decline when willpower is depleted. You become what researchers call a cognitive miser, hoarding your energy. If you’re shopping, you’re liable to look at only one dimension, like price: just give me the cheapest.

This is why I think learning about trade-offs can be so useful. The less novel a decision is, the less resources it should use up. The more general your schemas are, the more easily you'll adapt.

2) How do people typically deal with ego depletion? Apparently,

[E]ventually [you] look for shortcuts, usually in either of two very different ways. One shortcut is to become reckless: to act impulsively instead of expending the energy to first think through the consequences.... The other shortcut is the ultimate energy saver: do nothing. Instead of agonizing over decisions, avoid any choice. Ducking a decision often creates bigger problems in the long run, but for the moment, it eases the mental strain.

I think Tierney is a bit off here, as he neglects a crucial strategy: devising rules. "No coffee after two, no liquor before five." "Always take the middle option." Even, much more perniciously, statistical discrimination. For better or worse, we advance cognitively by thinking less.

3) Marketers know that we use rules, and they (wisely) use our rules against us. This makes rarer rules more valuable (holding effectiveness equal), as they will be less exploitable.

4) Before you go off devising your own un-gameable rule system, recognize that there are trade-offs to thinking about topics like this. It might be a better use of your time to just go along with most of the status quo rules and accept that you'll sacrifice some small amount of money to savvy marketers. As Ice T says, it's not about being mad at everything, it's about being really mad at the right things.

5) If willpower is a muscle, can you train it? Yes, self-control training can improve one's willpower to complete unrelated tasks. For example, in one study, maintaining better posture for two weeks (and keeping a diary about it) significantly improved hand-grip persistance (link, pdf). More examples here.

6) As Tierney's article discusses, decision fatigue often helps trap people in poverty. But since willpower is apparently like a muscle, shouldn't exercising decision circuits improve willpower enough over time to escape the trap?

7) I expect that the confound with the above is an interaction with stress. Making self-control decisions when you feel comfortable and empowered increases your set "willpower" level. But the emotionally stable undergraduates studied are not very representative of the population at large. When people must make decisions under psychological duress, it might instead condition a sort of "decision avoidance." Kind of like how overtraining your muscles can actually decrease strength.

Addendum 8/25: See Robert Kurzban's astute criticisms of this model (HT Brian Potter).

The Motion Mystery

2011-08-20T12:54:00.000-05:00

Even to eminent thinkers, an explanation for motion was seemingly unknowable near the turn of the 20th century.

For example, in the late 19th century Thomas Huxley said that "existence, motion, and law-abiding operation in nature are more stupendous miracles than any recounted by the mythologies...".

Santiago Ramón y Cajal went further in the early 20th century, writing, "there is no doubt that the human mind is fundamentally incapable of solving these formidable problems (the origin of life, nature of matter, origin of movement, and appearance of consciousness)."

It turns out that in the early 21st century we now have a pretty good answer to this mystery. That answer comes in the form of molecular machines.

As Steven Pinker explains, "the stuff of life turned out to be not a quivering, glowing, wondrous gel but a contraption of tiny jigs, springs, hinges, rods, sheets, magnets, zippers, and trapdoors...".

One example of such a machine is ATP synthase, which literally works like a rotor:

Now, molecular machines don't explain why atoms themselves move (you'd need to go deeper for that), but their existence certainly does explain why you can move in the absence of an outside force and a rock cannot.

If we don't kill ourselves (from, e.g., an environmental disaster or nuclear war) first, we will to continue to solve puzzles that some of us currently consider intractable mysteries.

And in the meantime, we should cultivate some doubt in our doubt of the potential of science.

Searching For The Imdb Of Books, Part II

2011-08-13T18:55:00.002-05:00

As watching imdb's top 250 most highly rated movies has proven to be such a smashing success, I have long yearned to find (and fleetingly, to develop) a similarly authoritative list for fiction books. The keys for a good list are: 1) a large sample size, 2) shrinkage estimation of ratings to the average, 3) a continuous scale (the more levels, the better, but yes we'll often have to settle for five stars), 4) defenses against gaming, and 5) a wide index of titles. To the best of my knowledge no site fulfills all of these requirements. These are the current contenders:

Amazon Reviews: Upside: They have a huge incentive to index all available books and are proficient at combining ratings across different editions of the same text. They also have a useful "was this review helpful to you?" tool which could eventually be employed to rate the raters and thus weight the overall ratings. Downsides: Their insistence on showing the average rating in half-star increments (typically 5, 4.5, 4, or 3.5) means that it involves manual calculation to distinguish between the two radically different scores of 4.24 and 3.76. I also often don't trust the resistance of their ratings to gaming. But most damningly, there is simply no attempt to create a good list of the most highly rated fiction books. Filtering by "highest average rating" in "literature and fiction", their #7 best fiction book of all time is currently Jim Gorant's The Lost Dogs: Michael Vick's Dogs and Their Tale of Rescue and Redemption, which is probably a fine book, but I think the author would be insulted to hear that it was considered fiction, and I think more than three-quarters of the english profs across the country would be insulted to hear it called literature.

One-Time Votes: By this I refer to ad-hock competitions of various websites which ask users to vote on their favorite books. There are many of these strewn across the web, for example, check out NPR's top 100 science fiction and fantasy books, or Modern Library's top 100 novels. Upside: These tend to get large sample sizes (NPR had >60,000 votes), which makes them more accurate and harder to game. Downside: The process is not iterative and requires manual input to update, so they won't last or scale. More troublingly, many (such as NPR's) only allow the option to select one's favorite books, without voting others down, which unfairly favors books with high variance as opposed to just high average quality.

Google Books: The site aggregates ratings from elsewhere on the web, including major vendors and online "bookshelves." Upside: Transparent code, takes ratings from diverse sources, and has a clean layout. Downside: Like Amazon, also displays ratings in half-star increments (et tu, google?). But their biggest problem is that different editions of books are stored in different locations and the ratings are not aggregated across editions. See, for instance, the first four results of a search for "pride and prejudice" (here, here, here, and here). Now, even if they did manage to output one total score per novel, it still doesn't seem very google-like to actually curate such a list themselves. But in that case, it wouldn't be hard for someone else to scrape the ratings and convert them into a ranked list.

Library Thing: Upside: They have scale, with over 10 million ratings, and they already have some pretty cool statistics (check out the most "connected" people--Napolean is #1). They also do have a top 25 books by rating. Downside: They need to split the rankings for non-fiction and fiction. At this point I've given up on searching for a canonical non-fiction ranked list, as those ratings are so context-dependent and world-view driven. And they need to do a better job of categorizing in general. For example, the movie for LoTR:Two Towers, while an awesome movie and in imdb's top 250, should not be among the highest rated 25 books. More importantly, the editors of the site have not implemented a rating system that punishes books with fewer ratings. Instead, books simply need a minimum total of 20 ratings to make the list. This is bothersome, but easily improved, as the editors could simply study and implement the imdb method.

Good Reads: Upside: As far as I can tell, this is the largest "bookshelf" site with the most user ratings. Huge potential. Downside: They've made no attempt to publish a list of the highest rated books across the site! All I can ask is, what is holding you back, GoodReads editors? Qualms about alienating authors whose works won't make the list? Fears of being labelled imperialistic? These are both hogwash. Our time is scarce and in order to be informed consumers we need to know what the best books are. If you are worried about the arbitrariness of the minimum votes cut-off, then publish multiple lists with different scaling parameters. You will thank me later when the list gets out-of-control traffic. Indeed, a group of passionate GoodReads users recently called for such a list. To this valiant effort I can only say, Viva la Résistance!

Some Now Or More Later In Moth Reproduction

2011-07-17T18:38:00.000-05:00

The abstract from a (gated) paper by Nokelainen et al:

[Wood tiger moth males] have two distinct colour morphs: white and yellow. The efficacy of the warning signal of these morphs was tested by offering them to blue tits in the laboratory. Birds hesitated significantly longer to attack yellow than white males. In a field experiment, the survival of the yellow males was also higher than white males. However, mating experiments in the laboratory revealed that yellow males had lower mating success than white males. Our results offer an explanation for the maintenance of polymorphism via trade-off between survival selection and mating success.

Yellow moths are less likely to be attacked because their conspicuous color acts to fend off predators. On the other hand, the authors cannot suggest a clear reason for why white male moths have greater mating success. Whatever the mechanism is, this is a clear example of some now vs more later in evolution.

Bill Simmons' Rating Nihilism

2011-07-16T20:35:00.000-05:00

Earlier he claimed, on scarce evidence, that "Rotten Tomatoes scares me as a metric," because "people are idiots," and that "their 'top critics' rating is much more useful."[1]

Now he explains that:

I believe Michael Jordan is the greatest basketball player ever, and I can prove it. I believe The Breaks of the Game is the greatest sports book ever, but I can't prove it. Books can't be measured that way — they hit everyone differently, so when we're evaluating them, we can only say, "You can't mention the greatest books (or albums, paintings, TV shows, movies or whatever) without mentioning that one." That's as far as you can go.

I don't get it. He thinks you can sort of rate movies (if you trust only the experts), but you can never rate books except for saying which ones are "among the best"? This is inconsistent.

He's right that there is a key difference between sports and film/writing, although it is not, as he claims, that the latter "hit[s] everyone differently." The difference is that in sports there is a known goal--for the team to win. That means that, at least theoretically, it is possible to tease out which player stats tend to correlate with winning, and then use those stats to evaluate players.

But notice the causality here. We can't evaluate individual players well until we know which stats are generally good indicators that a player will help eir team win. Intuition does not necessarily serve well here, an insight upon which books have been written and careers have been made.

In film/writing there is no such clear objective, and thus the ratings by individuals who have seen/read them must be subjective. So instead of evaluating statistics based on how they correlate with the objective of winning, we must instead evaluate rating systems based on inter-rater reliability. The goal is that if you added more independent ratings by unbiased raters, there should be as small of a deviation as possible between the new and old ratings.

The obvious suggestion is that, if we want better opinions, we need more of them to average out more of our random biases, like how hungry we were when we first saw the movie.

Again, the input must be subjective. But once we've decided upon the best rating system, its output is objectively our best estimate of that film/book's quality. Just as in sports, personal intuition is not the best estimate of quality, and to believe otherwise is simply hubris.

Perhaps it should not surprise us that a key opinion maker is arguing that we should only trust key opinion makers, instead of wide-scale opinion aggregators. But the rest of us don't have to buy it.

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[1]: Rotten Tomatoes ratings have many problems, like the fact that they threshold scores into "good" and "bad" and count the percentage of each instead of employing a continuous scale. But that is a straw man for the claim that open, aggregated movie ratings are bad.

Venkatesh Rao On Protection vs Freedom

2011-07-03T21:32:00.000-05:00

Rao explores an application of this trade-off,

[The] industrial age of mass-scale production required paycheck workers. People who had to be trained in industrial-style schooling.... [The] unpublicized purpose was to create a class of people that was far more disciplined and risk-averse than natural for the human species. In other words, a domesticated, comfort-loving species. This was achieved through, quite literally, conditioning. Bells rang for waking up and meal-times. Food appeared magically. Retirement was taken care of. Everything happened like clockwork.

The first few generations resisted being drafted into the industrial workforce mightily. Not despite their intimate familiarity with risks ranging from bad harvests to disease, hunger and death through poverty, but because of it. Because they understood that with those risks came freedom. After that, the next generations were born and raised in captivity and never had a chance to sample the environments that might have made their wilder risk-taking instincts come out.

I get anxious when I read the word "generation", since it's so hard to define the gradients of separation. But thinking back on the older films I've watched, some of them (e.g. Modern Times) do explore this anxiety of becoming trapped by industry.

If Rao is right, does this indicate that part of the "wiseness" of earlier generations can be encapsulated as a more thorough understanding of trade-offs?

Why Trade-Offs Matter

2011-06-23T19:14:00.008-05:00

A respected friend recently gave me some push-back on this, asking: at the meta-level, what exactly is the value in reading a list of trade-offs? I offer three main reasons, in order of descending plausibility:

1) Interestingness: There are many systems used for classifying stories (e.g., here, here, and here). Now, the classical "decision" is not necessarily more "important" than the story. (And they are often intertwined, as we use our decisions to construct and shift the trajectory of our personal narratives). But still, we might consider a similar sort of interestingness as is found in classifying stories to be a lower bound on the value of a good trade-off classification system.

2) Awareness: Daniel Gilbert writes that "because resources are finite, every sensible thing we do is another sensible thing we don't. Alas, research shows that when human beings make decisions, they tend to focus on what they are getting and forget about what we are forgoing." And apparently teaching people about cost-benefit reasoning really can improve their ability and propensity to use it (see here).

3) Tactics: Reading one of the trade-offs might allow someone to recognize a systematic bias towards one side of that trade-off. In the future, when that person identifies a situation which can be classified into that trade-off, they could try to adjust for their tendency towards bias. This ability to treat individual situations as merely examples of broader trends is crucial for aligning short-term decisions with long-term preferences.

Seeing Status-Seeking Statements Everywhere

2011-06-21T21:09:00.000-05:00

I follow humblebrag on twitter, and have often chuckled when the feed re-tweets people boasting about their achievements under the guise of humility. But for some reason (curator) Harris Wittels' article summarizing the most flagrant humblebraggers gives me some anxiety about supporting the feed and evangelizing for it.

Perhaps this is just the paradox of funny things losing their appeal once they are explained, kind of like growing to loathe a song once you come to realize what the lyrics actually mean.

But I think my anxiety runs a bit deeper than that. Consider Wittels' sarcastic take-down of "a very specific type of humblebrag, which is the 'some person did something great and I am very good friends with them' Humblebrag."

There's no doubt that mentioning your association with high-status people and institutions is a great way to seem high-status. But we also have to respect these would-be humblebraggers' plausible deniability, which is that they might really just be happy for their friends.

To me, it is this plausible deniability that distinguishes between having a conversation and bragging. It is typically socially acceptable to mention an accomplishment of yours if it comes up naturally in a thread that you did not initiate.

The logical conclusion of humblebrag and like-minded feeds continuing to rise in popularity is that people will become especially conscious of not bragging. Rather than making people more earnest, I think this will likely make them more mysterious. Since I'd prefer more earnestness, I say to err on the side of bragging, as long as it is real.

Full disclosure: I once sent in a tweet to humblebrag@gmail.com that I thought was a particularly good instance of humblebragging and got no response, so I might just be bitter.

The Cost-Benefit Of Considering The Costs And Benefits

2011-06-14T20:13:00.000-05:00

Pierre-Simon Laplace, in my opinion the greatest statistician of all time, wrote eloquently about the cost-benefit principle in his magnus opus:

Consequently we ought always in the conduct of life to make the product of the benefit hoped for, by its probability, at least equal to the similar product relative to the loss. But it is necessary, in order to attain this, to appreciate exactly the advantages, the losses, and their respective probabilities. For this a great accuracy of mind, a delicate judgment, and a great experience in affairs is necessary; it is necessary to know how to guard one's self against prejudices, illusions of fear or hope, and erroneous ideas, ideas of fortune and happiness, with which the majority of people feed their selflove.

Napolean made Laplace the Minister of the Interior in 1799, which he apparently begged for. But he struggled with it, as Napolean recounts,

Laplace was not long in showing himself a worse than average administrator; since his first actions in office we recognized our mistake. Laplace did not consider any question from the right angle: he sought subtleties everywhere, only conceived problems, and finally carried the spirit of "infinitesimals" into the administration.

Let's be careful not to read too much into this one anecdote, as it has an n of one. But still, it's scary that thinking too much is a plausible way for a politician to fail.

In other contexts, this paradox is often called "paralysis by analysis." Insofar as it holds true, what exactly would mediate the trade-off between probabilistic thinking and timely, necessary action?

I think it's secular vs sacred. In the real world you need to make assumptions to actually make things happen, but in the world of intellectuals, as Robin Hanson says, "sharp people... distinguish themselves by not assuming more than needed to keep the conversation going."

There's no doubt Laplace caught onto this. For example, when asked by Napolean why he didn't mention religion in his tome on probability, he famously replied that he "had no need of that hypothesis."

Again, not sure how far this example generalizes and I'd like to see some systematic data, but this is something to ponder.

Reform "Marco Polo"

2011-06-12T20:14:00.000-05:00

Back when I was a lifegaurd, I spectated countless sessions of this game. And what a truly awful game it is. Nobody has fun, and the noise pollution is unabashed.

It's once again summer up here in the northern hemisphere, and as my base tan isn't going to improve itself, I have been putting in work by the pool. So this weekend I had to endure another few games of "Marco Polo."

Here's one easy improvement. Just add a finite limit to the number of times the person who is "it" can call "Marco." Say, 20. This will prevent him or her from spamming that ability and actually introduce some strategy.

More generally, the fact that people play so much Monopoly, Tic-Tac-Toe, and Marco Polo, despite their terribleness, is one of the strongest arguments I can think of against status quo bias.

Trade-Off #20: Quality vs Quantity

2011-06-11T07:07:00.001-05:00

If the above photo had two flowers instead of just this one, would each seem slightly less pretty? I don't know for sure (we are talking about aesthetics, after all), but I imagine that most would say yes, because each flower would stand out less from the background and seem less unique. The only exception would be if the flowers somehow contrasted or augmented each other's beauty.

In scarce environments, and aside from such cases where individuals interact to produce effects greater than the sum of their parts, the average quality of an agent's choice will be inversely related to its quantity. Here are some examples:

People often wonder whether they should spend lots of time and energy pursuing one high-quality mate, or distribute those resources pursuing many lower-quality ones. This is a very general quandary, which many if not all reproductive species face. (see here)
In searching a text, an increase in the proportion of relevant results to total results typically comes at the cost of missing more of the possible relevant results from the whole search space. (see here)
For an individual using an online social network, adding more "friends" usually decreases the quality of his relationship with his average connection. (see here)

Trade-offs are found everywhere, even in making a list of the most important and widespread trade-offs. So given the quality vs quantity trade-off that we face in adding more trade-offs to this list, the first draft of the canon will end here.

(photo credit to domesticated diva)

Validating The Next Revolutions

2011-06-05T20:45:00.000-05:00

From my hopefully not overly-insular vantage point, the two books which have had the biggest impact in the first half of 2011 have been Richard Arum and Josipa Roksa's Academically Adrift and Tyler Cowen's The Great Stagnation.

There are many similarities between them. They both address broad, ongoing trends in American society, in higher ed and macroeconomics. They have both been read largely in e-book format, AA due to the prohibitive price of the print version, and TGS due to some brilliant/lucky marketing. And, oddly, their approaches both owe at least some homage to the views of entrepreneur and raconteur Peter Thiel, who has widely-discussed qualms with higher ed, and who won the dedication of TGS for his insight into the lack of innovation and growth in our economy.

This last point deserves some drawing out. For all the hype, the overarching theme of neither book is necessarily novel. Arum and Roksa make many points that were assumptions, not conclusions, of conversations at Vassar's cafeteria. No one ever wondered with incredulity, "wait, instructors are gaming their end of semester ratings?" The case is similar for Cowen's thesis. Individuals who decry the sluggish innovation and dormant middle class prospects in America are hardly in short supply. Just notice how many express fears that America doesn't "make anything" anymore.

But what both books do accomplish is to make these everyday arguments more rigorous. And, perhaps because the authors are academics, they also serve to validate what might otherwise be seen as merely mumbles and whimpers amongst the broader populace.

The impact of these books also speaks to the fact that we as a culture are still only barely embracing the brave new world of the internet. Content-wise, these both could easily have been "merely" articles. Publishing in some gated academic journal would obviously have reached few, but even if they had been published in the popular press, I doubt they would have had the same success. Regardless of the e-book format, we still love the idea of the book. For instance, I get expontentially more comments and questions IRL about my shelfari page than my del.icio.us page, although I've surely invested more time and energy into curating the latter.

Cowen himself says, on his blog, that, "we’ve yet to really organize our economy around the internet, as we someday will, and then the gains will be enormous." Perhaps the impact of these e-books could be considered Exhibit A of both our current lack of mobilization around the internet idea economy, as well as its potential once we do get our act together.

Boredom Trade-Offs?

2011-06-04T19:35:00.000-05:00

Aaron Haspel says that "an above-average capacity for boredom is optimal; a superior one is disastrous." Somewhat similarly, Mike Tully argues that becoming bored with a pursuit will inhibit artistic and athletic greatness.

Perhaps we can think of the capacity for boredom as a cognitive trait that pushes you towards the plasticity side of the plasticity vs specialization trade-off.

But really this idea seems a bit too vague. It's not clear whether one's capacity for boredom extends uniformly across all domains, and there are many other factors involved.

For example, you could argue that Ted Williams was able to specialize because he never grew bored of baseball, or you could argue that he specialized because he so quickly grew bored of everything else. With the former frame he has a below-average capacity for boredom, while with the latter it's above-average, but the end result is still the same.

Which Parts Of Crowds Are Wise?

2011-05-30T21:11:00.000-05:00

Peter Freed has written a pretty ambitious critique of Jonah Lehrer's summary of this study (pdf) on the wisdom of the crowds. The crux is that:

But now that I realized he really meant median, and that maybe he didn’t know what median meant. Because median guesses are not guesses by a crowd, as Lehrer states. They are guesses by a single person... [Lehrer] is talking about that 0.7% single-person data point: one person, selected after giving their answer, got close to the correct answer on one of six questions. One person guessed 10,000 when the answer was 10,067. That’s one hit out of 144 x 6 = 864 attempts. That seems about right to me, from a common sense perspective. Which is to say, that is a shitty batting average.

Scrolling through the comments, I was pleased to see Ian Sample point out the critique of Freed's critique that I was going to make:

In Wisdom of Crowds studies you can look at the mean and / or the median. The median usually gives the best result if the guesses *do not* follow a normal distribution. The mean, of course, exploits the error-cancelling advantage that WOC is known for, that is, as many people under-estimate as over-estimate the right answer, so averaging cancels all but systematic biases. But to my point. To dismiss the median answer – one guy’s response – misses the fact that without the crowd you have no median answer to dismiss. Without the crowd, you do not know which value to pick. That’s the whole point. The crowd steers you to the median value, which in many cases outperforms the mean.

The median is indeed generated by only one person, but it becomes interesting only in the context of all the other estimates. It is useful here because it offers resistance to outliers. For example, some less numerate soul might have guessed 1,000,000, which is way off from the true value of ~ 10,000, thus skewing the arithmetic mean. In that case you'd much prefer a more robust statistic like the trimmed mean or the median.

In prediction markets, the most recent price of a transaction doesn't always best represent the current beliefs of the market. There's more info if you look at the whole distribution of orders. Similarly, it is unfair of Freed to dismiss the whole data set just because one type of estimator is flawed. This is one of the coolest parts of statistics, using potentially counter-intuitive methods to extract useful info out of data, to find the wisdom in the crowds.

Fighting The Lernaean Hydra Bias

2011-05-15T21:33:00.005-05:00

I'll just only mention the heads I do cut off

In one Greek myth, Hercules takes on the task of killing a serpent-like, many-headed beast. This is made more difficult by the fact that its heads regenerate, so even if Hercules chops one off with his sword, another will simply sprout in its place. John Ioannidis uses this frustrating scenario as an analogy for a problem in the world of scientific publishing in his discussion of meta-analyses (doi:10.1002/jrsm.19).

The example Ioannidis employs to explain this problem is his experience doing a meta-analysis on the pharmacogenetics of certain polymorphisms for asthma treatment (doi:10.1097/01.fpc.0000236332.11304.8f). There were many studies that fit the criteria, but they each evaluated their own endpoints and genetic contrasts. That is, in most of the studies, the vast majority of possible correlations that could have tested with the data between phenotype and genotype were either not done or not reported.

So the surface problem, in so far as this case generalizes to others, is that published studies are not as exhaustive as they could be. But the central, troubling implication is that these studies do not fail to be exhaustive because of time or computational constraints, but because the researchers want to emphasize the usefulness and/or interestingness of their results. This is more insidious--this is why the hydra heads regenerate.

Now, one can use meta-analysis to retrospectively "chop off" findings that are truly insignificant by combining the results of many different data sets. But meta-analysis itself can be biased in many ways (e.g., during study selection), and moreover, later researchers can just come back to the issue and cherry pick more novel associations, thus "sprouting" more statistically significant findings.

When faced with the hydra, Hercules knew he couldn't go it alone, so he called on his nephew for help, who suggested that they cauterize the stumps with fire before the heads could regrow. An analogy to this strategy might be to post warnings on the electronic copy of papers that have been called into question by later studies. Such a warning would be much milder and hopefully less political than a retraction, which typically implies some sort of error. Publishing a potentially informative result that is eventually overturned is still laudable.

But instead of this type of patchwork fix, a more fundamental approach seems more fruitful. In the original myth, only one of the hydra's heads was truly immortal, and this was the one that Hercules needed to chop off to finally defeat the beast. The immortal head of the scientific publishing hydra is the incentive structure pushing researchers towards significance hunting in the first place.

Reworking these incentives is what Ioannidis is fundamentally arguing for, as the way to kill the Lernaean hydra bias once and for all: more standardization, more consortia, and more of a push towards openness and replicability. Every study might combine previous data with its own for estimating the posterior probability of the parameters it is examining, and all research might be seen as a continuous and cumulative meta-analysis. Maybe one day.

(photo credit to Frank Rafik)

Color Me Old-Fashioned

2011-05-14T12:02:00.001-05:00

A fantastic idea from Risto Saarelma on how to re-design the comment section of the website Less Wrong:

Provide an ambient visual cue on how old a comment is. First idea is to add a subtle color tint to the background of each comment, that goes by the logarithm of the comment's age from reddish ("hot", written in the last couple of hours) to bluish ("cold", written several months or more ago). Old threads occasionally get new comments and get readers in via them, and the date strings in the comments require some conscious parsing compared to being able to tell between "quite recent" and "very old" comments in the same thread by glance.

Too true. Who takes the time to read the actual date of a comment? This way you wouldn't have to.

This sort of subtle clue is something that people will appreciate and pick up on quickly. For example, on the blog Marginal Revolution you can always tell whether Tyler or Alex is posting because Tyler only capitalizes the first word in the title of his posts whereas Alex capitalizes all of the words in his titles. Knowing this, you won't have to waste time scanning the byline as you plow through your RSS feeds because you'll already know who wrote it from the title.

Three Thoughts For Spring

2011-04-24T19:15:00.001-05:00

1) If there are things that you can do to increase your perspective on your current problems, like taking a weekend off or writing a journal, then there also should be things you can do to decrease it. But I can't think of any. So is perspective the sort of thing where your typical state is a steady decrease unless you actively increase it through certain, discrete actions? You either have to agree with this model or describe specific ways you can lose perspective.

2) Who will systematically review the systematic reviews? Cochrane reviews, that's who.

3) One thing I wonder, as I try to get into Anki, is how we could make spaced repetition learning into a game. And I don't mean some lame game, like "how many flaschards can I get right today?", but a sweet game, with long-term goals and leveling up and side-missions and bad guys to defeat. I don't know if it could be done, but couldn't you imagine this as a big part of the future of education?

Sometimes Simple?

2011-04-22T19:03:00.001-05:00

"Everything is more complicated than you think." - Synecdoche, New York

Is this true? No way. We can easily come up with counterexamples. Take any superstition, like some time in your youth that you were afraid of monsters in your closet and it turned out to just be a broom propped up at a weird angle. Which is more complicated--the angled broom or the hidden monster? That's a layup.

So the better question is: are things on average more complicated than you think? It sort of seems like it. But part of the problem is that we tend to simplify old beliefs to make our current ones look more intelligent in comparison. Consider the history of Dale's principle. Some authors understand this to mean that neurons can only release one type of neurotransmitter. If stated in this form, it's clearly wrong, and so newer researchers can claim credit for debunking it. But when you look at its inception, it turns out that "one neuron = one neurotransmitter" is probably not what the principle was actually meant to imply. So our intuitions about how our beliefs tend to change probably speak more to what we currently believe about the past than to what we will believe in the future.

If we could show conclusively that things in general are more complicated than we think they are, that'd be good to know, because if reality tends to deviate in some predictable way from your expectations, then you're doing something wrong. But I'm not sure that the answer will turn out to be so simple.

Milestones In...

2011-04-18T16:03:00.002-05:00

I've recently discovered Nature's milestones index, which links to timelines of the major advances in the research of many fields: light microscopy, gene expression, development, etc. These were chosen by panels of many experts. For example, these 40 helped decide the milestones in cancer research. The timelines have links that explain why each milestone was important, like this one on the first methods of DNA sequencing. Awesome.

I wonder if there's some way that we could allow people to vote on these milestones in a similar way that others have set up for people to vote on milestones in computer science? If so, we could tap into what seems to me like the most productive form of crowdsourcing, where experts define the field, and then the masses rank the entries in that field.

The Wisdom Of Whuber

2011-04-17T11:36:00.004-05:00

That's William Huber, whuber for short, dispensed in his answers at the relatively new stats Q&A site, Cross Validated. His answers are the best on there, reputation normalized to the number of answers (with shrinkage). Here he writes about whether the median is a better summary stat than the mean:

Statistics does not provide a good answer to this question, IMO. A mean is ok to use, too, and is relevant in mortality studies for example. But ages are not as easy to measure as you might think: older people, illiterate people, and people in some third-world countries tend to round their ages to a multiple of 5 or 10, for instance. The median is more resistant to such errors than the mean.... Thus, for demographic, not statistical, reasons, a median appears more worthy of the role of an omnibus value for summarizing the ages of relatively large populations of people.

Here he writes about the biggest questions in statistics, from which I'll reproduce two (emphasis his):

Coping with scientific publication bias. Negative results are published much less simply because they just don't attain a magic p-value. All branches of science need to find better ways to bring scientifically important, not just statistically significant, results to light. (The multiple comparisons problem and coping with high-dimensional data are subcategories of this problem.)
Probing the limits of statistical methods and their interfaces with machine learning and machine cognition. Inevitable advances in computing technology will make true AI accessible in our lifetimes. How are we going to program artificial brains? What role might statistical thinking and statistical learning have in creating these advances? How can statisticians help in thinking about artificial cognition, artificial learning, in exploring their limitations, and making advances?

And here he writes about whether you should use a normal distribution to assign student grades:

I think that if any of those 800 students were to read this question, they might be offended. How well did they perform? How much learning was accomplished? That is what a grade should reflect, not some arbitrary statistical summary of their position in a group. IMHO this question should be recast in terms of teaching objectives, not statistical procedure, such as "what is a good way to convert raw scores to grades in a way that respects student accomplishments and advances the learning objectives of this class?" Statistics can help, but blind statistics--like standardization--will not.

Although they are often quite quantitative, his answers show how good stats rely on far more than just math.

Testing Robustness vs Fragility In Chemotaxis

2011-04-16T11:30:00.002-05:00

receptor modulation, from doi:10.1371/journal.pone.0011224

Bacterial chemotaxis depends (like most biological functions) upon an intricate signaling network, in which all of the molecules (mostly enzymes) must work in unison. Oleksiuk et al have just published a paper (doi:10.1016/j.cell.2011.03.013) showing convincingly that ambient temperature would affect many of the molecular components of this pathway in E. coli, but the system is optimized to work despite variations in temp.

For example, they show that the pathway's receptor kinases have modification states (see above) with opposing temperature dependencies. So, when the temp changes, the activities of receptors with different mod states compensate for one another to allow the system to maintain the same function.

Since there is apparently a canonical trade-off between robustness and fragility, E. coli's robustness to variability in temperature should come with some costs. One form this cost could take is that it would make a mutation to a temp sensor gene more deleterious. Another form this cost could take is that it would make the bacteria more susceptible to viruses that mess with parts of the temperature regulation system. Maybe some group will show one such cost to be present, or even to be the dominant force? We'll see.

Ranking Ideas In Science

2011-04-11T22:45:00.000-05:00

Last summer I bought and read The 100 Most Important Science Ideas after noticing it in a bookstore (my first mistake--I should have checked the ratings online first). I learned a fair amount from it, but I have to say it fares miserably in its attempt to actually rank ideas in science. First, it only covers three subjects: genetics, physics, and math. Second, even within those subjects, the topics are listed merely by date of discovery, not importance. Finally, there was little to no space devoted to methodology.

Subsequent attempts to find lists of the most important science ideas, via google searches and cold e-mails to potentially knowledgeable people, have also left me empty-handed. Lame.

A good system to rank science ideas, both historically and as they are published, would be so money. The historical list would be really useful for educating the next generations and as outreach to the public. And dynamic, post-peer review ratings would help researchers use their precious time reading the best papers, instead of relying solely on the impact factor of the journal.

Given the above, you can imagine my immense pleasure to see Scott Aaronson's announcement today of a site that allows anyone to vote on milestones in computer science.

There are at least a couple of ways this voting could be done. The first way, as they currently have the site set up, is that users can pick and choose to vote any individual idea on the list up or down. The advantage of this is that users can choose to vote only on the ideas that they actually know something about.

The second way is that the site could present two options to users, the users would choose which of those two are better, and then an algorithm would use those preferences to rank all the ideas. The advantage of this is that it's more fun. Indeed, you might recall that a similar system was employed by the young Mark Zuckerberg in facemash. Wait, you haven't seen The Social Network? C'mon now, it's #190 on the top 250. Step your game up.

Anyway, bravo to Jason, Ammar, and Scott. Now we just need to create similar lists for all other scientific disciplines, incentivize people to vote on them, and aggregate the results. We'll also def need some kind of normalization to account for the fact that computational pursuits will have at least 10x the votes, because those people are on their computers like all day.

When Can We Measure Grit?

2011-04-09T12:26:00.001-05:00

Jonah Lehrer's interesting, 15,000 character article about measuring NFL quarterbacks concludes by saying that we have neglected grit in favor of IQ because "grit can't be evaluated in a single afternoon". But this is clearly not true, as earlier in the same article he notes that Angela Duckworth has developed a survey for grit that predicts (well) both Westpoint cadet graduation rates and spelling bee performance. Here (pdf) is Duckworth's rating system for grit, including "self-report and informant-report versions of the Grit Scale, which measures trait-level perseverance and passion for long-term goals." So what's the deal?

I suspect grit is shunned as an aptitude test not because it is un-measurable, but because it is game-able. That is, if NFL scouts started judging players on how they rated themselves 1-10 on perseverance and passion, the players would all give themselves 10's on everything, except maybe one or two 9's to maintain some semblance of honesty. With millions of dollars on the line, wouldn't you?

Still, it does seem to me that you could measure grit in an afternoon, if you wanted to. You'd just have to test it when the player doesn't suspect she is being tested.

Three Cool Active Ideation Innocentives

2011-04-05T00:17:00.000-05:00

1) A Communication Platform to engage the “Hidden Community” of Family Caregivers. Link. Reward: $8,000, Deadline: 5/2/11, Description: There are more than half a billion people taking care of someone elderly at home worldwide and the number is growing. Most of these dedicated "at-home" caregivers are not professionally trained to deal with such things as dementia, personal hygiene, medical conditions and complications. Our investigations lead us to believe that this "Hidden Community" would benefit greatly from educational materials, product information /recommendations and established healthcare techniques. We are looking for a "communication platform" to reach out to these individuals to provide educational information and respond to feedback to meet their needs.

2) Educating About the Importance and Acceptance of Purifying Drinking Water. Link. Reward: $5,000, Deadline: 4/27/11, Description: [This org] strives to bring clean, safe water to people in developing countries. With this Challenge they would like suggestions for addressing one of the biggest problems they encounter in this process – namely, that of educating illiterate populations about the importance of purifying drinking water.

3) Humanitarian Air Drop. Link. Reward: $20,000, Deadline: 5/2/11, Description: Humanitarian food and water drops can only be done over an unpopulated drop zone because there is danger of falling debris to people below. We are looking for an alternative way to drop large amounts of Humanitarian food and water packages from an aircraft into populated areas such that there is no danger of falling objects (i.e. non-food items) causing harm to those on the ground.

If you have any ideas on these, write them up and make money!

Trade Offs In Self-Identifying

2011-03-28T23:58:00.000-05:00

Katja Grace has written a fascinating mini-dialogue between two of her mental modules, one of which is irrationally anxious and one of which is rationally calm. She concludes,

Identifying with being rational is a useful trick because it provides a convenient alternative emotional imperative – to follow the directions of the more reasonable part of oneself – in any situation where the irrational mental module can picture a rationalist.

She links to, and seems to conflict with, Paul Graham's famous advice to keep your identity small. His idea is that since "people can't think clearly about anything that has become part of their identity, then all other things being equal, the best plan is to let as few things into your identity as possible."

As I wrote back in Feb '09 when his article was published, there has to be a trade-off to this, because there are trade-offs to everything. My stab at it was that self-identification is a useful shortcut:

If you identify yourself with fewer things, then you will constantly have to make decisions.... [W]e can only make so many decisions before we become tired and revert to shortcuts that expend the least possible energy. So you can't keep your identity small, because you will be worn out by making trivial decisions throughout the day. But what you can do is loosely identify with various identities and be constantly open to change.

But Katja's internal dialogue suggests why identifying yourself with particular stances is a useful shortcut. That is, self-identifying allows you to save the time spent explaining to yourself precisely why you should take a certain stance every time you encounter a slightly novel scenario.

Now, Paul is right that there are still advantages to keeping your identity small. Even definable forms of rationality have their failures. So, this seems like a specific case of the more general trade-off, plasticity vs specialization. You can either pay a cost in time explaining to remain plastic and able to change, or you can specialize and potentially bias yourself, but free up resources for use elsewhere.

George Ainslie has written extensively about interpersonal bargaining, so if you are interested in these issues you should check out one of his books (here and here). Lots of terminology (i.e., you will def learn what hyperbolic discounting means), but worth the investment.

Commonly Held But False Beliefs Impede Tech Development

2011-03-26T20:20:00.000-05:00

That is the stance of George Church, who works on new methods of DNA synthesis and, more generally, genetics. In this Nature Biotech article, he also says, of his conversations with fellow scientists:

Sometimes they'll say something is impossible, but if you drill down they say that it's really expensive, and if you drill further, they say it's really expensive now.

One of the issues is that people mean different things when they say words like "impossible." They are referring to different time scales, different probability measures (does impossible mean in 1 in 1000 or 1 in 1,000,000 worlds?), and different reasons why (intrinsic to the tech, coordination problems, regulation, etc). Really want we want is incentives to make people more precise about their predictions.

What How You Read A Paper Says About You

2011-03-19T13:40:00.000-05:00

abstract only = lazy bum

intro only = n00b

methods only = nerd

results only = conceited

discussion only = naive

intro + methods = tease

intro + results = arrogant

intro + discussion = proud owner of a Jump to Conclusions Mat

methods + results = overly-technical

methods + discussion = gullible

results + discussion = impatient

intro + methods + results = somebody who is no fun at parties

intro + results + discussion = somebody who is way too much fun at parties

methods + results + discussion = somebody who doesn't go to parties

figures only = honorary member of the Derek Zoolander Center For Kids Who Can't Read Good And Wanna Learn To Do Other Stuff Good Too

text only = too lazy to deal with pop-up windows

figures first, then full text = overachiever

The Seven Most Discussed Scientific Biases

2011-03-17T20:41:00.001-05:00

From David Chavalariasa and John Ioannidis (pubmed, doi:10.1016/j.jclinepi.2009.12.011):

confounding bias = when you think you are measuring the effect of variable X on variable Y, but in reality there is another variable Z that correlates with X and also affects Y, which you haven't considered.
selection bias = when you think that all the various sub-groups of the population are proportionally just as likely to be in your sample, but in reality certain groups are more likely to be present than proportional, because of the way you collect your data.
publication bias = when you are more likely to publish or tell others about your results if they 1) conform to what you expect, or 2) are what you think others would prefer to hear.
response bias = when respondents answer your questions in the way they think you want them to answer, rather than according to their true beliefs; this could also happen in animal research if you reward animals for responding in a certain way outside of the main test.
attention bias = when you focus only on data that supports your hypothesis and ignore data that would make your hypothesis less likely.
recall bias = when respondents are more likely to remember the content of your question if they hold a certain belief on it.
sampling bias = when you think your sample is representative of the population, but really it is not, because it is skewed in ethnicity, attractiveness, age, gender, and/or etc, casting doubt on your generalizations from the sample to the population. (this is actually a sub-category of selection bias, with the distinction of external vs internal validity that sounds cool but also troublesomely postmodern)

The legendary Ioannidis apparently had a dream of writing a "book of bias," but settled for this paper. They also have a cool cluster map of how all the biases relate to one another, but unfortunately this paper is not open access so I can't post it here for your viewing pleasure. The above is based on text-mining from pubmed, which of course has its own biases.

Added 3/21: Eduardo Zugasti has translated this post to Spanish here.

Trade Off #19: Exploration vs Exploitation

2011-03-15T20:37:00.000-05:00

When an agent first enters a system, it will have to decide whether it should stay still and try to understand its surroundings, or to begin to move towards what it initially considers the most attractive direction. And indeed, at any point in its existence in that system, it will still face this trade-off: should it "explore" by gaining more info about the system, or should it "exploit" its knowledge by devoting resources to mining the option that currently has the highest expected value?

The downside to the strategy of "all exploration" is that you never reap the benefits of your information, while the downsides to "all exploitation" are that 1) you can get locked into local maxima, and 2) you can't adapt when circumstances change. There are many domains in which we find this trade-off:

One might think of basic science research as "exploration" and of applied science research as "exploitation." That is, investing in basic science now takes scarce resources, but makes future applied efforts more powerful. (see article, pdf)
In the multi-armed bandit problem, a gambler is faced with multiple levers to pull from, each of which has an unknown but unique distribution of payouts. He can either sample a diverse set of levers to discover more info about their expected reward, or he can just choose the lever with the highest current expected payout. (see here)
Organizations can "exploit" their worker's knowledge by forcing them to socialize to their particular code more quickly, but this leads to less "exploration" and ultimately a lower equilibrium knowledge level for the org. (see article, pdf--this is a classic paper, with 6000+ citations)

In previous revisions of the canon, this trade off was subsumed by switching costs vs change gains. But now I think that they really are distinct, because this trade-off describes a continuous case whereas switching costs vs change gains is binary. But yes this is confusing, and yes that is a bad sign: building a taxonomy of trade-offs has not proven as easy as I initially thought!

Of the two downsides to the "all exploitation" strategy, the local maxima problem seems like it could be surmounted, if one became very good at prediction. But the utility of exploration in allowing an agent to adapt to a changing environment seems to be very robust.

The one way that the "all exploration" strategy might break down is if one's end goal was merely and wholly understanding--if, in other words, it were the case that "the journey is the destination." So if you've always thought that phrase sounded like commie fiddlesticks, then this trade off might be right up your alley.

(photo credit to flickr user Ronny R)

The Defects Of Others

2011-03-12T13:03:00.000-05:00

First here's Anne Lamont in her book of advice, Bird by Bird (via Ben Casnocha):

A person's faults are largely what make him or her likable. I like for narrators [of novels] to be like the people I choose for friends, which is to say that they have a lot of the same flaws as I. Preoccupation with self is good, as is a tendency toward procrasination, self-delusion, darkness, jealousy, groveling, greediness, addictiveness. They shouldn't be too perfect; perfect means shallow and unreal and fatally uninteresting.

Then here's Santiago Ramon y Cajal in the foreword to a later edition of his Advice for a Young Investigator (Swanson translation):

However, we decided not to undertake a detailed editing of this modest little product of youth. Whether good or bad, every book has a spiritual personality. The public knows this and demands that the author respect it; they do not want it replaced under the guise of improvement. And this could very easily happen today, when, on the threshold of old age, we appear (and occasionally are) somehow defective. It is precisely this feature that attracts the reader's attention and gains his sympathy--just as with men, we admire and respect books for their good qualities; but we can only love them for certain faults that they display.

It seems legit that in both friends and books (and is not a book a sort of friend?) we tend to prefer those with some defects, some sort of burden. Why might this be? Possibly it's because just anyone could like perfection, but it takes one's uniqueness to accept and even appreciate defects.

How To Find Which Basketball Stats Matter

2011-03-08T00:48:00.001-05:00

Dave Johns today summarized whether basketball stats can actually tell how much a player is helping his team. It seems that there are two key problems:

1) The one stat we know must be good in the long run, adjusted plus-minus, is too noisy to make good inferences based on short run data.

2) The stats that we do have lots of short-run game data on, like points, rebounds, and FG%, we don't know how to interpret in terms of how much they actually help the team. For example, Kevin Love is piling up boards, but does that actually help the Timberwolves win ballgames?

One approach to solve these problems would be to use a large set of training data for both adjusted +/- and summary stats, spanning many years. For each player and each game (or even each quarter), you try to use the statistics from (2), like points and rebounds, as features to try to predict the player's adjusted +/- in that time period. Some of the statistics will be able to predict the +/- really well, whereas others won't. So going forward, we'll be able to say which of the stats are good short-run proxies for long-run +/- and which are not. That's it. It will be beautiful.

For a few minutes I thought about trying to do this myself, but I couldn't find easy enough access to raw +/- data. That is to say, screen scraping nba.com does not sound like much fun. If anyone knows of a nice and clean data set, holla acha boy.

Frankly I was surprised Johns didn't mention this approach in his article (thus this post), but I assume that it's what teams using bball sabermetrics are doing. The approach is similar to the netflix prize or to many articles in machine learning, like Burstein et al '09, who predict the function of proteins based on training features. I'm pasting their figure 1 below for a schematic of the process, although note theirs is binary whereas our classification system would be continuous. Think of the "features" as either simple stats like assists, or more complicated ones like under-/over-shooting, and think of "classification algorithms" as either naive things like "how many points did the player score?", or more complicated things like John Hollinger's PER.

doi:10.1371/journal.ppat.1000508

Use Words To Convey Probabilities

2011-03-01T14:10:00.009-05:00

William Strunk, author of what is surely the most highly cited text on writing, The Elements of Style, favors the use of words as vehicles for bold statements. From the foreword,

[H]is original Rule 11 was "Make definite assertions." That was Will all over. He scorned the vague, the tame, the colorless, the irresolute. He felt it was worse to be irresolute than to be wrong.

But what if you are not certain of a belief, something that should happen to reasonable people nearly all of the time? Apparently Strunk suggests you should hide this, as it makes you look "colorless" and low status.

On the contrary, we should use employ the wide range of our language to calibrate our words to the probability that we assign to events. However, we want to use words that unambiguously assign probabilities. Ideally, we'd have a clear mapping between our words and the probabilities we assign to the events those words describe. There have been at least two attempts to do this, as described by wikipedia. Combining what I see as the benefits of both of these scales, going forward I'll try to use the following system:

"Surely" = > 99% probability
"Likely" = ~ 90 - 99% probability
"Probable" = ~ 60 - 90% probability
"Chances about even" = ~ 40 - 60% probability
"Improbable" = ~ 10 - 40% probability
"Unlikely" = ~ 1 - 10% probability
"Surely not" = < 1% probability

One key arbitrary choice here is putting "likely" above "probable" in the hierarchy, which feels right but doesn't have much precedence. Any suggestions?

Against The Word "Scientist"

2011-02-28T14:42:00.000-05:00

After seeing Dan Ariely's rant about how unwilling companies are to test things empirically, this ngram showing that "natural philosopher" used to be the term describing one who did experiments, Aaron Haspel's slightly too profound tweet that "what scientists say is not science" (that should be obvious), Katja's exposition of how schools fail to teach science in a way that students can actually apply to their lives, and unconsciously synthesizing all of this info at some point during its consolidation from short-term memory in the hippocampus into long-term memory in the cortex, I have come to the opinion that the word "scientist" should not be used to describe any people or profession. Instead it seems better to refer to those who work in science labs as "researchers" or more specifically by their specialty, like immunologist. If the research community, and by that I refer to the group of people who fantasize daily of having a paper published in Nature, were to stop monopolizing the term "scientist," perhaps others would be more apt to employ the scientific method in their own endeavors, to the benefit of all.

Why Not Uniqueness?

2011-02-26T16:33:00.000-05:00

First, check out the comments on my recent post about uniqueness, in which I was (rightfully) ripped to shreds. It is wonderful to have such a critical readership! What Brian's critique suggests is that humans, when they want to be unique (which is often), tend to do so in a particular way that most other animals do not. That is, humans are more likely to share major beliefs with others in their immediate group, in order to signal their loyalty, and instead try to differentiate their group from other groups. He's mostly right and I was lazy to write that in the first place. Also in the comments, Justin asks "what's so bad about uniqueness"? Bingo responds basically as I would (must be in the DNA), but in the next three paragraphs I'll expand a bit on that.

Betting on horse races is systematically biased such that longshots are overbet and the favorites are underbet. There are many explanations for this, but I think the best is that the bettors, who are typically also spectators, prefer to have their "own horse" that they in particular can root for. Similarly, participants in the intellectual sphere like to have their own "horse" in any ongoing subject of conversation, in part because it allows them to signal their uniqueness, and in part because it is simply more fun (these two parts are probably correlated). This implies that the marketplace of ideas, much like the horse betting market, is likewise systematically biased; "favorites" or obvious ideas are not valued as highly as they ought to be. So the key reason intellectual uniqueness (or intellectual hipsterdom) is bad is because it diffuses our focus from the most important questions and problems.

One key question: is informing people about this phenomenon likely to change their behavior? Probably not. Think of hipsters. Every hipster knows that hipsters are generally annoying, and most hipsters are personally annoyed by other hipsters, but this stops almost no one from acting in their self-interest and being hipster-ish themselves. So this is probably a dead end.

What we can do is make rating systems that quantify and rank, as precisely as possible, the various options in each of the idea spheres. This way people can talk all they like about their particular "horses" in the intellectual marketplace, but when it comes time to make important decisions, we can rely upon the ratings rather than these uniqueness-biased discussions. (A prediction market is an example of a rating system, and when possible to set up these tend to perform the best. But they are not always feasible to set up, so we should consider other options too.) Figuring out how to set up rating systems to answer important questions, and how to incentivize idea consumers to actually rate things in such systems, seem like key questions, and they are questions this blog will continue to track closely.

Hanson To Fellow Bloggers: Do As I Say, Not As I Do

2011-02-26T14:27:00.000-05:00

Robin Hanson responds to Vladimir M's post about when one should or should not trust an academic consensus. First a bit from Vladimir,

When looking for information about some area outside of one’s expertise, it is usually a good idea to first ask what academic scholarship has to say... [I]t would be astonishing if there didn’t exist at least some areas where the academic mainstream is detached from reality on important issues... Areas affected by ideological biases... tend to drift much further into outright delusion, possibly lacking a sound core body of scholarship altogether... I’ll have to read much more on the technical background of these subjects before I can form any reliable opinion on these questions.

Then Robin,

But if you plan to mostly ignore the experts and base your beliefs on your own analysis, you need to not only assume that ideological bias has so polluted the experts as to make them nearly worthless, but you also need to assume that you are mostly immune from such problems!... If ideology severely compromises others’ analysis on this subject, then most likely it severely comprises yours as well. You should mostly just avoid having opinions on the subject. But if you must have reliable opinions, average expert opinions are probably still your best bet.

The conundrum is that Robin himself does this all the time. See for example this post literally two days earlier, where he is skeptical of an academic consensus because he has reason to believe that the authors are biased, does some digging on his own from the raw data, and draws some interesting conclusions. That's exactly what Vladimir is saying one ought to do.

So Robin's disagreement seems a bit inconsistent, but it's really not. He has admitted that he doesn't specialize as much as he thinks people should. Specialization requires trusting the surface arguments in most fields in order to focus on one's own. In other words, he thinks people should generally not be contrarian, if only because it's a waste of time. Consensus definitions of hypocrisy emphasize that it's OK (i.e., not hypocritical) to preach temperance for others when you yourself have not conquered your passions, as long as you do not claim to have done so. So Robin is not being hypocritical.

Still, it might be nice if he admitted to often not following his own "don't be a contrarian" rule.

Trade Off #18: Speed vs Accuracy

2011-02-20T13:04:00.000-05:00

As you decrease the time in which you complete a task, you must give up some of the control which allows you to ensure that each part of the process goes as desired. This trade off between speed and accuracy is very widespread and is one of the most intuitive trade offs in the canon.

You can test yourself on this trade off by going to any typing test website and varying the speed with which you type. At more words per minute you will tend to have more misspelled words, while at fewer wpm you will have fewer misspelled words. Other examples:

Watson, the AI created by IBM to compete at Jeopardy, faces a speed vs accuracy trade-off in that the longer it has to search its databases and run its algorithms, the more confidently it can assign a high probability to one of its answers. (see here)
If you take longer to respond to emails, people will expect your responses to be more accurate, whereas if respond right away, their expectations will be much lower. This is because they intuitively recognize the trade off you face between speed and accuracy. (see here)
In the world memory championships, as contestants take longer to look at a card, their mental representation of it become richer, making subsequent recall more accurate. So they must race to make it interesting. (see here)

This trade-off seems to not apply everywhere, in that people's predictions about soccer games may actually decrease in accuracy with more conscious attention. But this is probably because people tend to over fit their models to the data with too much conscious processing, an example of the precision vs simplicity trade-off.

To say that there is a trade-off doesn't completely preclude free lunches. Ray Allen can shoot 3's more accurately than I can, and he can shoot them faster. The key is that if Allen were to shoot basketballs at 2x his own comfortable speed, he'd no doubt be less accurate. So, with respect to just this speed vs accuracy trade off, the amount he has practiced seems like a free lunch, but we know that once we consider other trade-offs, it is not.

(photo credit to flickr user Odd; the slower the sun sets, the more accurately you can predict the exact moment it will cross the horizon)

Squirrel Uniqueness

2011-02-17T21:16:00.000-05:00

Kimberly Pollard and Daniel Blumstein recently published a study (HT Ed Yong) examining whether group size correlates with the individuality of squirrel alarm calls:

Discriminating among individuals is a critical social behavior in humans and many other animals and is often required for offspring and mate recognition, territorial or coalitional behaviors, signaler reliability assessment, and social hierarchies. Being individually discriminated is more difficult in larger groups, and large group size may select for increased individuality–signature information–in social signals, to facilitate discrimination. Small-scale studies suggest that more social species have greater individuality in their social signals, such as contact calls....

[W]e show a strong positive evolutionary link between social group size in sciurid rodents and individuality in their social alarm calls. Social group size explained over 88% of the variation in vocal individuality in phylogenetic independent contrasts. Species living in larger groups, but not in more complex groups, had more signature information in their calls.

Extrapolating not unjustly from this, it seems that humans, the most social of all animals, should have the strongest drive towards uniqueness. So the desire for your own opinion, as opposed to just the best one, is probably an evolved tendency. We should all be similarly troubled by this.

In Praise Of The Obvious

2011-02-13T01:13:00.000-05:00

Ryan Holiday recently wrote a post encouraging us, in a roundabout way, to seek the counter-intuitive. On the contrary, I think the counter-intuitive is overrated. Consider:

It is very difficult to find an RSS feed that only lists the basic, most important findings from any particular field, even though this would be the most useful to an outsider.
Inception is unlikely to win the Oscar for best picture (currently 80 to 1), even though it has by far the highest weighted average rating of any movie this year.
Academics love to conduct and publish paradigm-shifting research, but are much less interested in replications or confirmations. This leads to lots of problems.

The best way to explain these conundrums is to admit that we love the counter-intuitive, we love to associate ourselves with it, and we love to demonstrate our uniqueness in doing so. Far from encouraging these tendencies, we should instead shun them. If the obvious thing is best, we must endorse it just as strongly, or we risk sending confusing signals to others.

Granted, there are some trade offs here, mainly between finding new ideas and reducing uncertainty about our current ones (an example of the more general breadth vs depth trade off). That is, if we only focused on what was currently obvious, we wouldn't come up with any new angles. But, at the margins of our current intellectual climate, it still seems to me that we should prefer more obviousness.

Frustratingly, all else equal, counter-intuitive thoughts are a good sign that somebody has a deep understanding of a subject and has thought it through beyond the status quo. So if we really want to encourage obviousness, we need to value the traits that lead to it, like formality and diligence, even more so than we value traits that lead to novel ideas, like creativity. As Ice T says, it's not about being mad about everything, it's about being really mad at the right things.

So Bad It's Good, On imdb

2011-02-10T01:34:00.000-05:00

My roommate was recently trying to convince me to watch The Room, employing the argument that, although it is poorly rated at a 3.2, it is "so bad it's good." The question is, can we quantify this?

The intuitive way seems to be to look at the distribution of scores, and indeed that is what Tomasz Węgrzanowski has suggested. The idea is that your typical movie tends to have a single peak at its mode, and the percentage of votes will drop off monotonically on both sides of that peak. Movies that are "so bad it's good," on the other hand, will have a bimodal distribution, with lots of high scores (9's and 10's) and lots of low scores (1's and 2's), and few in-between.

For example, The Hunt For Red October is a fairly standard movie, and you can see that it does show a bell-shaped trend, albeit with a ceiling effect:

So what does The Room's rating distribution look like? Frighteningly bimodal:

Eventually we started watching the movie. It is truly disgustingly bad, and in fact it's hard to even call it a movie, as the plot seems to be just a cheap excuse for softcore porn. Infamously, they seem to use the same sex scene twice, although the director vehemently denies this. Whatever. It's hard for me to evaluate whether the movie is "so bad it's good," but the above ratings speak for themselves.

Bottom line: It's a better sign if a movie is rated higher rather than lower. But, holding average rating constant, you should prefer movies with a wider distribution of votes, as they will tend to be more interesting.

Kobe In Crunch Time: Efficiency vs Predictability

2011-01-29T12:58:00.000-05:00

Henry Abbott breaks it down, showing that Kobe isn't that legit in late game scenarios, despite popular opinion, and his own. But here's what Abbott is missing. Kobe probably would have the highest probability of making the last shot of any player in the NBA, if defenses paid equal attention to everyone. Kobe gets his rep for what he could do in this situation, and that matters for something.

The problem is that defenses adjust for this ability. "Doubling-teaming" isn't always a binary yes or no--it's also about being more apt to help off your man in case of a drive, hedge on off-ball screens, and keep Kobe in your plane of vision. Of course, all of this hinders how well the defense can guard Kobe's teammates. So what Kobe should do is look for them. But he doesn't, because he gets too caught up in thinking about how efficient he can be, and forgets that this makes him predictable.

This is a pretty clear demonstration of the trade off. Crunch time offense is a game, and in any game you want a mixed strategy. That means that with some probability you'll do one thing, and with some probability you'll do something else. If you're the Lakers and you commit to Kobe always shooting, or even assign it a higher probability than you should, the other team will be able to take advantage.

Towards A More Risk Loving imdb

2011-01-29T00:18:00.001-05:00

In my view, the "true" rating of a movie is what the average opinion would be if everybody who watches it:

has some basic knowledge of art and human affairs in general (for example, a working knowledge of the canon of classics), but no knowledge about the movie in particular (no previews, hype, etc);
is watching alone, so nobody in the theater is laughing at unfunny times;
experiences neither hunger, thirst, polyuria, tiredness, stress, excessive marijuana-induced paranoia, nor any inclination to rub tongues with the person next to em;
watches on a ridiculously large screen with speaker cables made of pure silver.

Since the above conditions will never all hold, we will all be biased in one or another way when we watch a movie. So we must be wary of the opinion of any given rater. That is, if the first person to watch a movie gives it a 10/10, our estimate for the true rating of a movie should not be a 10, but instead should be adjusted down towards the average.

The above is all obvious. What's less obvious is that there's no easy way to decide how much one should scale down the rating. That depends on how much of a risk you're willing to take with low sample sizes.

Consider The Passion of Joan of Ark, whose 8.3 rating should be enough to place fairly high on the top 250. For example, Sin City also has an 8.3 and it's currently #104. However, TPoJoA only ranks #210, because its paltry 11k votes push down its score so much.

Here's what I'm proposing. Let us, the users, choose our own scaling parameter. Let us define how much of a risk we want to take in trusting smaller sample sizes. Let us choose our own destinies. Because the current system smacks of hegemony, and I, for one, will only stand for it because I have better things to do.

Hanson On Secular Vs Sacred

2011-01-24T01:11:00.001-05:00

He writes:

Ask yourself this simple question: how confident would you need to be on a moral or political conclusion in order to work passionately for it? 99%? 90%? 75%? If you have such an action-threshold, and this threshold is high, well then yes, to let your passion flower, you may need to lie to yourself about your confidence. So that you might actually do something.

Would your overconfidence then lead you to do too many things too enthusiastically? If so, perhaps you’d do better to also allow yourself some other more graded psychological reluctance to passion, to counter this bias.

But it would of course be even better if you could see the nobility and glory in doing your best as a limited but well-meaning creature. You shouldn’t need to be absolutely sure of a conclusion to work sincerely and passionately for it.

The emphasis is mine. In the first two paragraphs he articulates the trade off. Making an assumption, which is assigning something a higher prob of being true than you have evidence for, has the upside of allowing you to actually do things. But making an assumption also has the downside of distorting reality (e.g., making you overconfident), so we want ways to protect against too many assumptions.

In the last paragraph he says that we might circumvent the trade off by admitting that we might be wrong but pushing forward just as hard regardless. I doubt that's possible. Our brains are constantly computing probabilities and using those probabilities to determine policy implications, just as in Bayesian model averaging. So if we downshift the probability that an assumption is true, its relative policy implications also have to fall. There's a reason that overconfident CEOs are more innovative, and people crazy enough to be entrepreneurs are typically overconfident. All else equal, if you have less faith in your conclusions, you will work with at least slightly less passion towards them.

The above applies at any given time point. Now, you might be able to trade off some self-awareness for action now, in order to achieve more self-awareness later. This is sort of like what people do when they "build a slave." But that involves a different trade off; no free lunches here.

Trade Off #17: Secular vs Sacred

2011-01-15T16:06:00.000-05:00

Ever wanted to rid yourself of all assumptions and reason your way to a full, coherent philosophy? You're not alone.

Rene Descartes made the most famous attempt to do so, but by most contemporary accounts he failed miserably. And in truth, if someone ever did succeed in assuming nothing, we'd probably never hear from em again.

That's because assumptions are necessary for action. They are like the ground, without which you can't propel yourself forward. Assumptions come with a price, though, which is that they can distort reality. (The ground distorts reality, too. Relative to the earth's surface our position appears to be constant, even though the earth is actually hurtling through spacetime at ~ 30 km / s.)

So although you'd prefer to assume as little as possible, you must make some assumptions if you want to get anything done. The trade off is in deciding where precisely to draw this line. Examples:

Euclid's fifth assumption was the parallel postulate, that two perpendicular lines extended indefinitely will never meet. Making this assumption enabled him to prove many useful geometrical theorems, but it also obscured some other real ways the universe can behave, which later mathematicians would explore. (see here)
Psychologically, we humans all have a certain amount of anxiety, regarding our place in the universe and our identity. Some believe that everyone has a "dogma quota," which they must assign somewhere, to ethics or empirics or whatever, to overcome this anxiety and function in society. (see here)
In Kuhn's conception of science, the paradigm is the set of all assumptions that allows scientists to solve puzzles and make advances. But it comes at the cost of institutionalizing the assumptions. So even when the reality-distorting effects of the assumptions become obvious, the institutions supporting these assumptions are difficult to overthrow and require mini-revolutions. (see here)

Mathematicians often make broad assumptions when they first prove a theorem, and then someone else will come along later and "generalize" that theorem by coming to the same conclusions with fewer assumptions. Isn't this a violation of the trade off, because the later proof takes the same "action" with fewer assumptions?

Sort of, and it's true that most people make stronger assumptions than they have to. But at the base level certain assumptions are truly essential. For centuries bright minds tried to generalize Euclid's parallel postulate, to prove the fifth assumption from the first four, with no success. It is this "rate-limiting" case where assumptions are essential that this trade-off describes.

We're a bit worried about this trade off conflicting with precision vs simplicity. From a stats perspective, maybe it's best to think of precision vs simplicity as referring explicitly to the number of parameters in the model, while this trade off refers to the form of the model, including the act of modeling itself. But possibly they can and should be united.

(kudos to Denis Collette for the nice photo)

Ed Yong On Loyalty vs Universality

2011-01-12T22:51:00.000-05:00

He explains a study that measured the effects of oxytocin on a number of behavioral correlates in males:

[O]xytocin strengthened the biases of the Dutch volunteers. When they sniffed oxytocin (rather than the placebo), they were quicker to associate positive words with Dutch names than with either German or Arab ones.... [A]fter sniffing oxytocin, they were far less likely to sacrifice the Dutch loners than the German and Arab ones....

This last experiment clearly shows a trend that applied to the whole study: oxytocin boosted favouritism for people who belong to the same group. Only very rarely did it increase negative feelings towards people outside it. For example, in the moral dilemmas, oxytocin made the volunteers less likely to sacrifice members of their own group, but not more likely to sacrifice outsiders.

This sort of favouritism makes a degree of evolutionary sense. It could bolster trust and cooperation within a community, such that groups whose members stuck together more would out-compete those that did not.... But such preferential treatment has an obvious dark side – it leads to all sorts of moral and cultural problems, including inequality, discrimination, prejudice, and conflicts between different groups.

Fascinating, but I'm not sure we need any group selectionism to understand this. It seems from the above that oxytocin nudges humans towards in-group loyalty on the trade-off between loyalty and universality. So in order to increase the fitness of individuals, oxytocin levels should tend to rise in situations when signaling loyalty is adaptive, and fall when signaling universality is adaptive.

Hmmm... do you think it is more adaptive to signal loyalty or universality during and immediately after sex? Call me prude, but I doubt you'd boost pair bonding by telling someone that you love them, but you love everyone else just as much. Then again, I s'pose that's an empirical question.

What Tech Trades Off

2011-01-08T12:56:00.001-05:00

Ignoring his sometimes outlandish claims, Kevin Kelly's book What Technology Wants has much wisdom to dispense. At its core, the book describes the trade-off between protection and freedom, with respect to a society's level of tech use.

At one extreme, a society can minimize its adoption of technology, protecting its members from potential dangers, but limiting their choices. The Amish are an example of such prudishness.

At the other extreme, a society can maximize its use of technology, allowing its members the most possible choices, but limiting its ability to protect people from the potential dangers of tech. Is anyone so audacious? Kelly doesn't offer examples, but presumably some transhumanists would fit here.

Some benefits of protection from technology are:

The opportunity to nudge people towards choices they might consider more desirable upon sober reflection. (e.g., drug regulation, exploitation in compensated medical trials)
Reduced existential risk, if a particular tech could wipe humans out, and restricting tech development will decrease that probability. (controversial, but nuclear winter, bacteria with reversed chirality, exponentially self-improving unfriendly AI, runaway anthropogenic global warming, etc., could all fit)

Some benefits of freedom in technology are:

An increased ability for people to express their unique preferences and match their aptitudes to their environment. (e.g., transportation tech allows people to move away from the place they were born, if they find it disagreeable)
More rapid feedback via proxies for natural phenomena enables more experimentation, which increases knowledge. (e.g., changes in blood pressure allow you to gauge heart attack risk, so you can measure the effect of a given treatment before you actually die)

Most everyone agrees that by increasing the exposure to tech, you broadly accelerate tech development. As a counter example, think of the Amish, who sometimes free-ride on old tech, but provide few novel inventions themselves. This positive loop makes the consequences of the above trade-off more pressing.

In the long-run, it's hard to see how tech adopters wouldn't out-compete non-tech adopters. This is why the expansion of tech is in some senses "inevitable." But evolution requires replication, and nerds marry late and have few if any kids, so who knows.

(Thanks to the insightful Tyson B for a convo about this)

No Shame Gossip

2011-01-04T23:07:00.000-05:00

Here's Jonathon Haidt in his nugget-rich Happiness Hypothesis:

Gossip is overwhelmingly critical, and it is primarily about the moral and social violations of others. (For college students, this meant a lot of talk about the sexuality, cleanliness, and drinking habits of their friends and roommates.) People do occasionally tell stories about the good deeds of others, but such stories are only one tenth as common as stories about transgressions. When people pass along high-quality ("juicy") gossip, they feel more powerful, they have a better shared sense of what is right and what's wrong, and they feel more closely connected to their gossip partners....

[M]ost people hold negative views of gossip and gossipers, even though almost everyone gossips.... [We] came to believe that gossip is underappreciated. In a world with no gossip, people would not get away with murder but they would get away with a trail of rude, selfish, and antisocial acts, often oblivious to their own violations. Gossip extends our moral-emotional toolkit.... Without it, there would be chaos and ignorance.

Based on the above, it seems like not gossiping would be selfish. By abstaining, you save yourself from feelings of guilt, and you earn a reputation as reserved and trustworthy, if boring. Yet if nobody gossiped, we'd all be much worse off. This can still be true even if the marginal piece of gossip is harmful, and is another example of why categorical imperatives ("don't gossip" has 1.25 million google hits) are often flawed.

The Forager Manifesto

2011-01-02T21:40:00.000-05:00

"There are two kinds of people in the world, those that divide the world into two competing camps and those that do not." - Wise internet proverb

Robin Hanson has a similar thesis that the world can be split into two types of people, "foragers" and "farmers." Foragers tend to hold cultural stances that were adaptive in our evolutionary past, while farmers tend to hold cultural stances that were adaptive during and after the transition to agriculture, ~ 8000 BCE.

Upon first reading this I was quite skeptical, in large part due to the rampant tendency of academics to push false dichotomies. But the explanatory power of the forager vs farmer dichotomy has won me over; in particular see posts on how fear pushes us towards more farmer-like beliefs (here) and why we assume artists should be non-conformist (here). I defy you to explain these as parsimoniously without resorting to a similar argument.

Given the above, it's ironic that on a vacation this past week I purchased for five pesos a used book that can only be described as the forager manifesto: Daniel Quinn's Ishmael. First, Quinn himself divides the world into two distinct populations, the "leavers," which are extant hunter gatherer tribes, and the "takers," which is everybody else. Next, Quinn argues that the "takers" emerged in Mesopotamia in the era of the biblical story of genesis, right at the transition to agriculture. The rest of the book is mostly him signalling allegiance to forager norms and arguing, quite fairly but also tautologically, that all of society's current problems are due to our move away from a forager lifestyle.

So if you love foraging and don't mind trading off life expectancy (avg 30 - 37 yrs at birth, p 54 here) for more leisure and less stress (~ 20 hr "work" weeks, here), then read this book, and go join up with the !Kung pronto.

Hindsight Is 2010

2010-12-29T15:14:00.098-05:00

The NYTM's Year in Ideas is consistently good. My favorites for this edition were D.I.Y. Macro, Performance Enhancing Shoes, Relaxation Drinks, and The 2000's Were a Great Decade. Inspired by their ideas, my retrospective for the year will consist of twelve articles / blog posts, one for each month, that seem especially representative of the year in ideas.

January: "Lessons from a pandemic," Nature editorial, 685 words. The H1N1 virus ended up not being that lethal, but it could have been, and this article highlights the lessons. Among them is that six months is too long of a time for vaccine production, given that viruses now easily spread around the world in "a matter of weeks."

February: "The biomechanics of barefoot running," editor's summary, 283 words. Running on one's toes is healthier than running on one's heels, even though most running shoes promote the latter. This finding is largely academic for me personally, as over the years I have come to loathe jogging. Nevertheless, it is emblematic of the larger "back to nature" craze that has taken over in 2010. This includes the paleo diet, probiotics, and restroom posture designed to prevent hemorrhoids.

March: "Snake oil? The scientific evidence for health supplements," by David McCandless and Andy Perkins, infographic. Aside from being fascinating, this is a good example of an effort to harness the academic lit for the benefits of the masses. Also, it is representative of the open data movement, as the authors transparently aggregate their data set in a google doc, which anyone can view.

April: "The data-driven life," by Gary Wolf, 5808 words. Discusses the growing trend of self-experimentation. More generally, he discusses how many more people are using tech and data to inform decisions, trumping their raw intuition.

May: "The moral life of babies," by Paul Bloom, 6026 words. He discusses how our preference towards actors who "do the right thing" emerges very early. That is, it presumably emerges far earlier than the babies would be cogent enough to consciously reason about morality. This is part of a movement in psychology that is emphasizing the arbitrariness of our beliefs and decisions.

June: "Smarter than you think: IBM's supercomputer to challenge 'Jeopardy!' champions," by Clive Thompson, 6609 words. At any given point, the AI iteratively calculates the probability that an answer is correct, and then checks whether that probability passes a certain threshold. This probabilistic thinking seems to be invading fields beyond just machine learning, so it's important to understand.

July: "New developments in AI," by Steve Steinberg, 5496 words. An innocuous and perhaps unfortunate title, but a tour de force of a blog post. He discusses trends in smart cars and massive knowledge-bases, and speculates on how they will affect society. One sentence that's particularly near and dear to my heart is when he writes, "consider that 'what is the best burrito in SF' (an opinion), and 'what do most people consider the best burrito in SF' (a fact) are normally considered equivalent."

August: "A world without mosquitoes" by Janet Fang, 1929 words. She discusses whether we should try to eliminate all of these nasty, virulent insects. The downside is that it would mess with biodiversity in ways difficult to predict, while the upside is that it could save millions of lives. We will face plenty of these type of trade-offs in the coming years, specifically with respect to climate change and geoengineering, and more generally in changing aspects of our natural world that we disapprove of.

September: "Jumping to joy," by Robin Hanson, 212 words. He wonders whether we should experiment more with different lifestyles, and what our failure to do so implies about our precarious sense of self. Questioning which of our selves is the "real" one is trendy these days, boosted in part by things like the implicit association test. Experimentation is also enjoying a resurgence, championed by Dan Ariely.

October: "Lies, damned lies, and medical science", by David Freedman, 6022 words. Explains the problems with current scientific publication and data dissemination systems. Many scientists broadly agree with these critiques of their infrastructure, but lack personal incentives to change them.

Movember: "Hangover theory and morality plays," by Steve Waldman, 1986 words. He discusses the need to frame causes of the recession in moral terms that anyone can understand, synthesizes relevant economic theories, and holds no punches. It'd be hard to describe the ideas of 2010 without including reactions to the recession.

December: "The hazards of nerd supremacy: The case of Wikileaks," by Jaron Lanier, 4704 words. Wikileaks is one of the defining stories of the year. He explains that we might support the hackers in our hearts, because we perceive them to be the underdogs, but that in our heads we should be much more skeptical.

It's been a fun year of blogging and thanks as always for reading.

Lehrer On Plasicity Vs Specialization

2010-12-21T16:24:00.023-05:00

He discusses it here, a month ago:

Expertise might also come with a dark side, as all those learned patterns make it harder for us to integrate wholly new knowledge. Consider a recent paper that investigated the mnemonic performance of London taxi drivers. In the world of neuroscience, London cabbies are best known for their demonstration of structural plasticity in the hippocampus, a brain area devoted (in part) to spatial memory....

The problem with our cognitive chunks is that they’re fully formed – an inflexible pattern we impose on the world – which means they tend to be resistant to sudden changes, such as a street detour in central London....

The larger lesson is that the brain is a deeply constrained thinking machine, full of cognitive tradeoffs and zero-sum constraints. Those chess professionals and London cabbies can perform seemingly superhuman mental feats, as they chunk their world into memorable patterns. However, those same talents make them bad at seeing beyond their chunks, at making sense of games and places they can’t easily understand.

A beautiful exposition. However, I think the trade-off can be found more generally than in just the human brain. Indeed, most evolving biological systems impose limits on plasticity because of the costs. This suggests new minds or systems we might design will probably deal with this trade-off too. But this is all still hotly debated.

Douglas Adams On Robustness Vs Fragility

2010-12-19T16:22:00.000-05:00

From The Hitchhiker's Guide:

"The major difference between a thing that might go wrong and a thing that cannot possibly go wrong is that when a thing that cannot possibly go wrong goes wrong it usually turns out to be impossible to get at or repair."

Aging And Happiness

2010-12-19T13:10:00.000-05:00

How does subjective well-being vary with age? To find out, Stone et al (here, HT: The Brits (HT: BC)) conducted a large random-digit dial survey of 300,000+ US citizens. They asked about well-being and a few other variables, like age. We can only hope they had a good wireless plan. Here's the big result:

The covariates are unemployment, marital status, whether one has children living at home, and gender. Younger people increase in well-being ratings once you adjust for these because they're more likely to be unemployed. Of course be careful of the axes, as their real rating scale varies from 0 to 10. But the large sample size and continuous trend across age groups lends credence: I buy it.

What about anxiety and age? Here's the proportion of respondents who reported feeling "a lot" of stress the previous day, in different age groups:

I wonder what explains this trend. Perspective? Fiscal and emotional stability? Norepinephrine levels in the amygdala?

Finally, for those readers who do not trust their eyes, here's their table showing the percent of variances explained:

So anger and stress show a pretty consistent decline across age groups, while the curves are more U-shaped for measures of subjective well-being. Note sadness follows an inverted U-shaped curve.

Many top 250 movies explore this curious relationship between happiness and age, like Up, Ikiru, Cinema Paradiso, and The Wrestler. Much of it seems counter-intuitive. Here's a post of mine from '07 wondering whether we become happier with age, but I apparently didn't see the U-shaped curve coming.

Why Nature Didn't Choose Arsenic

2010-12-05T12:47:00.002-05:00

Phosphate is of course a part of the structures of DNA and RNA, but it is also in many metabolic intermediates like ATP and glucose-6-phosphate. The idea that a bacterium could survive without it (see here) would require updating some concepts about the flexibility of reaction rates in physiological systems.

A 1986 paper by Frank Westheimer, cited 400+ times, abstract here and pdf here, explains why phosphates are preferred. In particular, he notes how the negative charge of the phosphate ester makes it relatively more resistant to hydrolysis, while it still can act as a leaving group if enzymatically activated. Then, in an intriguing section, he discusses why various other alternatives would not make sense, including arsenic:

Another compound that must be considered as a basis for a possible genetic material is arsenic acid, which is also tribasic. The poisonous effects, however, of compounds of arsenic probably cannot be avoided, since these effects are centered in the lower valence states of arsenic, and the reduction of pentavalent arsenic is much easier than that of pentavalent phosphorus. In any case, arsenic esters are totally unsuitable; the hydrolysis of esters of arsenic acid is remarkably fast. The triisopropyl ester in neutral water at room temperature is completely hydrolyzed in a couple of minutes. Apparently the hydrolysis of the diesters is even faster than that of the triesters.

The idea is that esters of arsenic are too liable to be cut by water, thus making them poor linkers for bases of DNA and RNA. But this is assuming that the reaction will occur under relatively stable conditions (i.e., pH and temp), and perhaps those conditions are somehow altered in this particular bacterium, sufficiently lowering the hydrolysis rate of arsenic. We will have to wait and see, but in the meantime where are the prediction markets when we need them?

Trade Off #16: Impulse vs Incentives

2010-12-04T18:42:00.000-05:00

At one of the stoplights on my drive to the gym, there is often someone walking through the cars asking for change. Let's assume, reasonably, that she needs the money more than I do. Let's also assume, somewhat less reasonably, that she'll spend the money in a productive manner. We can now break the decision down into the benefits she'd gain from leveraging my money versus the perverse incentives I'd reinforce by rewarding people for begging in traffic.

Generally, this trade-off is between the benefits from an impulse meant to rapidly improve and stabilize a condition, versus the costs of long-term instabilities that could result. Some examples:

Keynesian econ emphasizes the multiplier of a gov intervention, which they consider to be an impulse, whereas Austrian econ emphasizes the moral hazard (i.e., bad future incentives) of such impulses. ("in the long run we're all dead", also see here)
Radiotherapy has a good chance of killing tumors, and thus can be thought of as an impulse. But it also makes mutations in other genes more likely, which could develop into secondary tumors in the future, and thus can be thought of as bad "incentives." (see here)
WikiLeaks might incite people to speak out against or question their government, thus acting as an impulse to increase freedom, but it also incentives governments to be even more secretive and centralized, thus decreasing freedom. (see here)

The previous trade off we're most worried about conflicting with here is some now vs more later. And indeed, it is true that there is a time component to both of these trade offs. But the difference between them is that in this trade off the two possible outcomes are not quantitatively but instead qualitatively different.

Now, the previous paragraph is somewhat of a technicality, and is probably boring. But if I didn't mention it now, just imagine the kind of incentives that would introduce for sloppiness in the future.

(Kudos to Alan Grinberg for the photo)

Bill Simmons On Uniqueness

2010-11-25T21:06:00.000-05:00

He gripes in his most recent chat:

[I]t's funny to take heat from soccer fans that I'm a bandwagon Tottenham fan. I mean... of course I am. I am something like 17 months into this thing. But what I don't get about sports like the UFC/soccer/NHL (and even baseball with the saber community towards people who just like baseball and don't want to dive into the stats) is why the diehards are so protective/condescending towards casual fans. What's the goal there? To just drive away everyone who might like the sport and want to become more of a fan? I think there's a difference between local bandwagon fans (like the Pink Hat Red Sox fans) and "I am starting to like your sport, I genuinely want to follow it and learn about it" fans and it would just seem like the diehards should embrace the latter group. Or am I crazy?...

I do think that diehard fans tend to exclude newcomers - the same phenomenon works with music, you always want your favorite band to be the little band that not everyone knows about (and never have them get to the U2 level). I think Kings of Leon are a good recent example of this and even the band members hated that they became "mainstream" because it brought in fans that they didn't necessarily want. The best breakdown of this was in Steve Martin's book about his standup career when he talks about becoming hugely famous and how he started dreading doing his shows because he felt like people weren't there for the right reasons. It's an interesting topic I think.

Once more people join a given group, affiliation loses lots of its signaling benefits due to diffusion. So it makes sense that fans who have invested in a team / band would discourage newbies from joining.

But why do the musicians / comedians themselves not want more followers? That's a bit trickier. Simmons mentions Steve Martin being wary of his new fans, but the same is even more true of Dave Chappelle. When he skipped out on the third season of his show, he turned down millions.

Any theory to explain this phenomenon also has to account for the fact that neither athletes nor academics tend to express these sentiments. Jordan, Manning, Hawkings, Volkow--they do not worry about "going mainstream." Indeed they tend to welcome it.

Perhaps the musicians / comedians are signaling loyalty to their core constituents, and the real emotional and financial costs they pay in doing so just makes their signaling more credible. So it seems that the less badly you want to go mainstream, the more your pursuit is about signaling as opposed to results.

Our Regrets Change Over Time

2010-11-20T13:27:00.000-05:00

Ben Casnocha recently posted about the regrets of the dying, and Robin Hanson replied that in fact people on their deathbed do not spontaneously offer such regrets. Robin is technically correct, but he is taking the claim far too literally.

Indeed, there is broader data to suggest that the regrets of older people are quite different from the regrets of younger people. In particular, as time since a decision grows, people tend to shift their regrets towards not making the hedonistic decision.

An '06 study (link, pdf) shows how the intensity of regrets towards work or enjoyment changes as time passes. For events last week, people express slightly higher levels of regret towards enjoying instead of working (2.2 vs 2.0 out of 6). But for events five years ago, people feel more regret for working instead of enjoying (3.4 vs 1.4 out of 6). This change is even more pronounced for feelings of guilt vs missing out, and there's lots of replicating data (for example, see Ran Kivetz's other papers here).

This is part of what makes using the regret heuristic so complicated. One must not only project future regrets for a decision, weighted by the probability of each outcome, but also consider how those regrets might change in direction and strength over time, and integrate over all probabilistic future time points. If this computation were easy, there wouldn't be so much demand for strategies to get an approximate answer.

P-Value Polemics

2010-11-19T01:12:00.000-05:00

As I am always up for a good scholarly debate, I was quite pleased, after reading this '05 article calling for a replacement to the p-value called p-rep (cited 200+ times), to see a somewhat vitriolic '09 rebuttal (pdf). First, the abstract of the '05 paper by P. Killeen:

"The statistic Prep estimates the probability of replicating an effect. It captures traditional publication criteria for signal-to-noise ratio, while avoiding parametric inference and the resulting Bayesian dilemma. In concert with effect size and replication intervals, Prep provides all of the information now used in evaluating research, while avoiding many of the pitfalls of traditional statistical inference."

A rather bold claim! And, shortly after its publication, the journal Psychological Science (6th highest psyc impact factor) recommended that authors report p-rep instead of the traditional p-value. Which makes the rebuttal article by Iverson et al that much more tantalizing. They write:

"This probability of replication prep seems new, exciting, and extremely useful. Despite appearances however prep is misnamed, commonly miscalculated even by its progenitors, misapplied outside a common but otherwise very narrow scope, and its seductively large values can be seriously misleading. In short, Psychological Science has bet on the wrong horse, and nothing but mischief will follow from its continued promotion of prep as a scientifically informative predictive probability of replicability."

Now that is what I call a take down! These same authors calm down quite a bit in their '10 article and even make the level-headed suggestion that p-rep is a step in the right direction, but that is lame so I won't quote from it.

####

Reading about p-values makes me want to start a blog about them (how does such a blog not already exist?!). A good subtitle could be "where one in every twenty posts will be significant by chance alone."

Trade Off #15: Acquiring Info vs Altering Subject

2010-11-15T00:41:00.000-05:00

Paradoxically, when you ask someone a question, their answer will likely be different because you've asked them. On reflection this phenomenon is remarkably general; in acquiring or assessing info about a property of a system, we must be willing to accept the consequences of altering that system. A smattering of examples follow:

Increasing the energy voltage in transmission electron microscopy can lead to higher image resolution (meaning more info), but it also does more damage to the tissue. (see here; there are similar trade offs in lots of med imaging techs, like PET scans, see here)
When a model of a complex psychological phenomenon becomes widespread, reality often begins conforming to the model. This is often called performativity, and it is perhaps why Keynes called economics a "moral" science. (see here)
The Heisenberg uncertainty principle says that the more precisely the position of a particle is measured, the less precisely its momentum can be, and vice versa. The explanation for this is controversial, but it's likely due to observer effects--the measuring apparatus delivers a force to the particle which alters it. (see here)

Most examples that fit into this category are true to at least some degree, but it's often tricky to determine precisely how much variance they explain. For example, even when you run a placebo-controlled drug trial, you must be wary of side effects that can tip the participants off to their treatment status (see here). Regardless, this is a widespread trade off, and it now assumes its rightful place in the canon.

(photo is of a peptide fiber, taken with EM, credit to Christoph Meier)

We're All Individuals Now

2010-11-09T22:58:00.014-05:00

Christian Jarrett explains how we tend to value our uniqueness,

Whether it's a gift for small talk or a knack for arithmetic, many of us have something we feel we're particularly good at... this strength then becomes important for our self-esteem... children tend to choose friends who excel on different dimensions than themselves, presumably to protect their self-esteem from threat... [W]hen making hiring decisions, people tend to favour [sic] potential candidates who don't compete with their own particular strengths... Participants tricked into thinking they'd excelled at the maths [sic] tended to choose the potential team member who was weak at maths but stronger verbally, and vice versa for those participants fed false feedback indicating they'd excelled verbally.

I think this drive can explain two anomalies:

1) We often agree to disagree. Aumann's classic disagreement theorem (pdf) says that rational truth-seekers cannot and will not agree to disagree; given the same priors and the same data, they must each reach the same conclusions. Cowen and Hanson (pdf) discuss how this disagreement result is quite robust. What's the deal? Disagreeing allows us to show off our independence and individual intelligence, which are among the most credible ways to establish uniqueness.

2) Our opinions oscillate in cycles away from what we perceive as the current consensus. A recent PLoS Comp Bio paper shows that in order to explain this "hype cycle" you need to model the preference for individuals to feel unique:

[W]e identify a missing ingredient that helps to fill this gap: the striving for uniqueness. Besides being influenced by their social environment, individuals also show a desire to hold a unique opinion. Thus, when too many other members of the population hold a similar opinion, individuals tend to adopt an opinion that distinguishes them from others....

[T]here is a third, pluralistic clustering phase, in which individualization prevents overall consensus, but at the same time, social influence can still prevent extreme individualism. The interplay between integrating and disintegrating forces leads to a plurality of opinions, while metastable subgroups occur, within which individuals find a local consensus. Individuals may identify with such subgroups and develop long-lasting social relationships with similar others.

There is a trade-off between uniqueness and accuracy in beliefs, so we typically seek uniqueness on opinions for which the cost of being wrong is low: art, politics, sports, etc. That's why there is less of drive for uniqueness regarding med. Few would claim that covering an open wound is a bad idea.

Before you say, "but I'm not an individual!", you need to check out this classic Monty Python scene.

Trust The Ratings Of Others

2010-11-07T22:37:00.000-05:00

An '09 paper (link here, pdf here, HT to TC) claims that people make more accurate emotional predictions about a future event when they are simply told how someone else reacted to that event, as opposed to when they are given info about the event. This is somewhat counter-intuitive, so let's look at their evidence.

One of their tests was speed dating. Each guy submitted a photo and some demographic info about himself. Then, each girl predicted how much she would enjoy the date based on either this photo / info or the enjoyment rating of a girl who earlier had gone on a date with the same guy.Next, the guy and girl had their five minute date, (ignore the heteronormativity, my fellow Vassar alums), and finally the girl rated how much she enjoyed herself on a sliding scale of 1 - 100.

The authors define prediction error as the difference between the girl's predicted and actual enjoyment ratings. Participants made more accurate predictions when they used the first girl's enjoyment rating to predict their own (the avg error was 11.4 +/- 8.7) than when they predicted their enjoyment on the basis of the info (an avg error of 22.4 +/- 10.8).

In classic psyc study fashion, they also asked their participants to say which condition they thought would lead to more accurate predictions. 75% said the info would be more useful than the rating of a girl who had already been on a date with that guy. Oops. Now, indulge me in a few reactions:

1) Why do people underestimate the value of someone else's rating? Probably because people think of themselves and their opinions as more unique than they actually are. This sets up my public choice theory for why popular critics like Anthony Lane tend to be negative and contrarian. Although on the surface this annoys readers, people on a deeper level prefer to read opinions about art that they disagree with, because it allows them to think of their own opinions as more unique.

2) There is only one specified relationship between the study participants: they are all undergrads at the same school. So although the authors toss the word "social network" in towards the end of the paper, their results do not speak to the predictive power of a friend's opinion as opposed to a stranger's opinion. This remains an open question--in predicting their own enjoyment, will people find the opinion of someone in their network more valuable than the average opinion of strangers? Even if you say yes, you must take into account the trade-off of sample size, which is larger when you listen to the masses. The high valuation of sites like facebook relies in large part on the assumption that we'll prefer recommendations from those in our network, but I'm not so sure.

3) A subsequent study looked at how people combine their own mental simulations and third-person reports of other's experiences in making judgments. Corroborating the results of this study, they found that people assign far too much weight to their own simulation of how an event will play out as opposed to the feelings of other people who have actually experienced the event. I myself find this all very relevant to imdb's movie ratings. Remind me again why you trust yourself to judge a movie instead of deferring to the aggregated ratings of others?

Making Me Guess

2010-10-25T18:43:00.004-05:00

It is often tricky when you are asked to estimate some odd quantity, like how many people dressed in panda suits there were at a party. The person asking you to guess is usually hoping to surprise you with the large deviation of your guess ("what you'd expect") and the actual quantity. But you, the guesser, can't help but take into account the fact that they are asking you, which they presumably wouldn't be doing unless the quantity to be guessed were extremely unlikely and otherwise surprising.

So, the supposedly naive guesser is forced to either guess especially high and annoy the asker, or guess low and appease the asker. Guessing high makes you look like a smartass, while guessing low is tedious.

As a young lad, I would never really know how to choose between guessing high and low, and the choice often brought on some anxiety. But now I usually just explain the whole situation, indicating how being asked to guess has instantaneously shifted my probability distribution. Incidentally, I no longer have any friends.

(Inspired by a representative convo with Brittany)

Trade Off #14: Precision vs Simplicity

2010-10-24T14:14:00.000-05:00

When you describe something, the more precisely your model explains the given data, the more complicated it must be. Don't believe me? Lo, behold these examples, then:

In describing the path up to my apartment, I could say "there are stairs", or I could say "there are fourteen stairs"; vagueness is less precise but it is also simpler. The bottom line is that having to walk up any number of stairs is too many.
In fitting a model to data, one can explain more variance by including more free variables, at the cost of complication. There are plenty of ways to punish a model for having additional parameters and thus make the model earn each of its parameters through explanatory ability. (see here and here)
The failure of humans to adequately trade off precision and simplicity in certain contexts, like when we say that the prob of X and Y is greater than the prob of just X, is one of our well-documented cognitive biases. (see here)

There are some well-known incidents in the history of science that on first glance appear to be exceptions to this trade-off. For example, Kepler's idea of elliptical planetary orbits eliminated the need for astronomers to model extra epicycles, both simplifying and adding precision to our understanding of planetary motion.

But in the view of this committee, these precision-enabling paradigm shifts are especially complicated, involve the shifting of assumptions at a fundamental level, and only seem simple in distant hindsight. That's one reason why they are so hard to come upon.

(photo of spiral galaxy, which Johannes Kepler probably would have marveled at, goes to NASA's Marshall Center)

Being Skeptical Of Your Skepticism

2010-10-24T01:47:00.000-05:00

If you notice one particular flaw in an author's fact checking or reasoning, to what extent do you discount the rest of what that author claims?

If you hold a narrative view of other's actions--X did Y because she is a Z--then you will tend to assume that the author is a liar and cannot be trusted.

But truth-seeking, like any other human tendency, is on a spectrum. (A psychopath is at one extreme, while Abe Lincoln, god bless his honest soul, held down the other). So that binary categorization is almost surely wrong.

Yet, we are heavily biased towards categorizing people and against seeing the full spectrum. Sometimes this bias is due to laziness, as labeling others as liars liberates us from the effort of actually understanding their claims. But less trivially, labeling others allows us to feel like part of a more exclusive group, a group that would presumably never commit such an error.

Surely, we must downshift our faith in the author's other claims some upon finding that they have made a mistake. But remember the high prior probability that the authors are merely fallible, and don't differ much in the degree of their truth-seeking from the rest of us. Now, if they get two things wrong...

Bottom Line: While it's healthy to be skeptical, it's healthier still, for the body if not the ego, to be appropriately skeptical of your own skepticism.

Zuckerberg On Reward And Interest

2010-10-19T00:04:00.000-05:00

He discusses The Social Network here. Precisely what he says is that Hollywood "can't wrap their head around the idea that someone might build something because they like building things." And... trigger the applause lights.

The reality is somewhere in the middle. To intimate that making facebook was totally intrinsic, which he in fact intimates, is going too far--social esteem from the Peter Thiels and Sean Parkers of the world had to be a motivating factor. But murky middle grounds are much harder to convey in a movie or sound bite. Harder to convey in a blog post, too.

Trade Off #13: Robustness vs Fragility

2010-10-17T22:04:00.001-05:00

One of the more ridiculous scenes in Star Wars: A New Hope is when one measly torpedo hitting a thermal exhaust sets off a chain reaction which destroys the entire Death Star. Even if the Empire doesn't consider a small one-man fighter to be any threat, and even though the shot is ostensibly "one in a million," buying into the whole fiasco requires some boyish naïveté.

But outside of Hollywood, it's surprising how many systems behave similarly. Designs built to maintain function despite large perturbations of a certain type are often highly vulnerable to perturbations from a different angle. It seems that optimizing for robustness to expected deviations generally comes at the expense of increasing fragility to unexpected deviations. Examples:

Forest buffer zones that are designed to prevent against particular types of fires can be superseded by unexpected types of fires, that, for example, come from a different direction. (see diagram here)
A Boeing 777 has complicated chips that can account for variation in the distribution of cargo or atmospheric conditions, but it is vulnerable to an electrical outage or computer error in a way that a simpler plane would not be. (see here)
Genetic regulatory networks are designed to sense and maintain function in a variety of environments, but a mutation that changes the internal connections of this regulatory network is almost always lethal. (see here)

Some have argued that, evolutionarily, there has been selection for suboptimal designs in biological systems in order to make them less vulnerable to unexpected events. If this is broadly true, it would perhaps be useful for us humans to recognize as we go about designing the institutions that shape our market interactions.

On the other hand, this trade-off is a fairly recent idea, it's not particularly well-defined, and it will be important to see what consensus develops towards it before we draw too many implications. Still, as far as this committee is concerned, robustness vs fragility is indeed canonical.

(Photo comes from flickr user Scott Beale)

Trade Off #12: Protection vs Freedom

2010-10-09T12:30:00.000-05:00

Preventing deleterious forces from harming individuals typically comes at the cost of constraining the actions of those individuals in some way. Thus we come to the common trade off between protection and freedom. Examples:

When herds of prey animals are large enough, they stand a chance to fight off a given predator. Thus they tend to aggregate together, lowering their freedom but increasing the probability of their survival. (see here)
Work is one way to trade freedom now for protection from various exogenous forces in the future. Like preparing for the zombie apocalypse. (see here)
Economic interventions that increase freedoms, like organ donation markets, are typically argued against on the basis of protecting individuals from exploitation. (see here)

This is one of the more politically charged trade offs, which I have naturally been avoiding like a beaker of Yersinia pestis. But for me it has proven useful to frame these political debates in terms of trade offs. This enables one to see the other person's side, even when the values which inform actual decisions on those trade offs might differ.

(Credit for photo of Harlech Castle goes to theroamincatholic)

Your Relationship With Your Former Self

2010-10-07T00:26:00.000-05:00

Fernando Pessoa considers this question in The Book Of Disquiet,

I often find texts of mine that I wrote when I was very young--when I was seventeen or twenty. And some have a power of expression that I do not remember having then. Certain sentences and passages I wrote when I had just taken a few steps away from adolescence seem produced by the self I am today, educated by years and things. I recognize I am the same as I was. And having felt that I am today making a great progress from what I was, I wonder where this progress is if I was then the same as I am today.

Pessoa realized he was underestimating his former self after reading his old writing. This makes sense. It's harder to construct a personal narrative of growth when the sentences showing that you used to be just as sweet remain visible, instead of diffusing into infinity like spoken words, or being lost in the synaptic puncta of the cortex, like most thoughts.

So with the masses leaving digital footprints in tweets and status updates, will all we soon find it more difficult to believe in our redemption stories? As the world freaks out about others peering into their privacy, perhaps the person we should be most concerned about finding our innermost thoughts is ourselves, in the future. Our syntax might seem a little too tight, our inner monologues a little too kindred.

This is one of the questions I ponder as I scroll through old posts on a rainy evening. And my other question is... was I more alive then, than I am now?

Trade Off #11: False Alarm vs Oversight

2010-10-04T19:08:00.001-05:00

We can distinguish mistakes into two forms. The first type is a false alarm, in which you overestimate the likelihood that an event will occur, and the second type is an oversight, in which you underestimate the likelihood that the event will occur. Suppressing the probability of an oversight will make a false alarm more likely, and vice versa. Plenty of examples, I'll just give three:

Statisticians make a distinction between "type one" errors, rejecting a null hypothesis when it shouldn't be, and "type two" errors, failing to reject a null hypothesis when it should be. If the null hypothesis is that a given event will not happen, then type one errors can be thought of as false alarms, and type two errors as oversights.
A lifeguard can choose to pay less attention to each individual momentary dip under water, and thus lower his stress from false alarms. But he inevitably does so at the risk of increasing the risk of an oversight--not noticing when someone is underwater for too long.
Rhodopsin switches conformational states in response to photon exposure. We can think of a false alarm as when rhodopsin changes states even when a photon has not hit it, and an oversight as when rhodopsin fails to switch states despite photon exposure. Evolution seems to have strongly selected for minimizing false alarms as opposed to minimizing oversights. (That is, oversights still occur ~ 30% of the time; see here)

This is one of the more solid members of the canon and can be used to explain a lot. Some people choose to ignore it--saying, for example, that a lifeguard should always pay as much attention to his swimmers as possible. But anyone who has been a lifeguard for long knows this is nigh impossible, that the stress builds up, and at some point you have to make trade offs.

(Above photo credit goes wholly to flickr user Abhijit Patil)

Strategic Swearing

2010-09-28T22:45:00.001-05:00

You can find a discussion of it in this (unfortunately gated) article, in the context of med. They discuss two types. The first is "swearing so as to enable empathy and catharsis," in which you swear to mirror the feelings of the patient and spur him to discuss those feelings further. The second is "swearing to create a feeling of social equality," which shows that you are willing to break pointless rules, and instead care about actual results. Generally, they argue that swear words can lend an emotional edge to a sentence that other words cannot. I agree.

It might have been nice if they had discussed swear word overuse. One high school bball coach of mine used to swear only sparingly, but when he did you really listened. Yet if you are known to swear almost never, when you do swear that event itself might detract attention from what you are talking about. Thus it is tricky to approach the equilibrium of swearing that maintains optimal effectiveness in case of maximum need. Very fucking tricky.

Three Surprising Findings On "Genius"

2010-09-27T00:22:00.000-05:00

From Dean Simonton, via Irfan Alvi's review of his book. The more surprising ideas are that:

1) "In some domains, overtraining can be detrimental to creativity. In these cases, cross-training can be more effective." Presumably cross-training involves learning about a variety of different topics. This seems useful either because it allows you to apply ideas in other fields to your own, or because it allows you time away from your main field to avoid getting bogged down in details. Or both.

2) "The creative processes underlying genius-level achievement are still not well understood, although use of heuristics and combinatorial thinking appear to be typically involved." It'd be nice to know precisely which heuristics lead to genius level output!

3) "Psychopathology has a positive correlation with level of genius, but outright madness inhibits genius and higher intelligence tends to provide the capacity to prevent outright madness." This jives with some research. For example, this study considers the effect of the interaction between cognitive ability and neuroticism on managerial performance. Regressing cognition and neuroticism alone explained 4% of the variance in performance, but adding the interaction term raised this to 19%. And after partitioning their sample in half by cognitive ability, they found the higher half had a positive and significant relationship between anxiety and performance, while the lower half had a negative and barely non-significant relationship.

I am still heartily recommending Simonton's Creativity in Science to people interested in these issues.

Trade Off #10: Plasticity vs Specialization

2010-09-25T19:42:00.002-05:00

In college, I was constantly reading neuro lit extolling the virtues of neural plasticity, which is the ability of neurons to change based on feedback from the environment. Plasticity certainly has huge benefits. Specifically, plasticity allows for a better match between phenotype and environment across variable environments than a single, constant phenotype would.

But after a while, the idolatry of plasticity began to annoy me, in part because much of the lit discussed plasticity as if it had no downsides, which seems impossible. (If there really were no costs to plasticity, then evolution should have selected for it like woah).

The general downside seems to be that plasticity hinders specialization. That is, if a system has the ability to change easily (i.e. it has high plasticity), then it will tend to expend resources on a wide range of trait values, and will have fewer resources to focus on the most important and relevant traits. A few examples:

Synaptic pruning and other mechanisms for synaptic plasticity allow for learning and memory, but they are energetically costly. Indeed, one hypothesis holds that sleep is the price we have to pay for plasticity the previous day. (see here)
In an evolutionary framework, the major costs to more plasticity are 1) actually sensing the current environmental conditions, and 2) producing the actual trait in a less efficient way. Both of these divert resources from other tasks. (see here and here)
People with autism spectrum disorders often find it difficult to parse novel stimuli, but can sometimes concentrate for especially long periods of time on specific niches. So one might think of the autistic cognitive style as shifted towards the specialization side of this trade off. (see here)

Despite the many applications, the members of the committee and I are a bit wary about this trade off. First, its status depends largely on one's particular definitions of plasticity and specialization. Also, some think it might just be a specific case of trade off #3, switching costs vs change gains.

But given our current working definitions (plasticity = the ability, which is highly correlated with the tendency, for context-dependent change; specialization = funneling energy expenditures to a narrow purpose), and because it is sort of one level "meta" to switching costs vs change gains, we are granting this trade off its own place in the canon.

(Above photo taken by flickr user uncle beast. Plants are often studied w/r/t genetic plasticity because they can't simply pack up shop and move if the environment changes, like an animal or insect could.)

Never Have I Ever

2010-09-23T21:57:00.000-05:00

Robin Hanson published an interesting thought today,

[W]hy are so many of us (including me) so reluctant to experiment with so many joys with strong fans? After all, fans argue, their suggested drug, sex style, or religious experience would only take a few hours to try, and could give us a lifetime of joy if we liked it. It seems we see far larger costs than the time for a trial. My guess: we value our current identity, integrated as it is into our job, hobbies, friends, etc. We fear that if we try new joys, we will like them, and jump to practicing them, which will change us. We fear that by jumping to juicy joys, we won’t be us anymore.

Twenty six google reader "likes" speak for themselves, but one quibble. I think it's more likely that the reason we don't try "fun" things once or twice is not because we fear how we will change, but fear how others might perceive us as having changed.

Consider how Tyler Cowen is so wont to point out that he's never tried coffee, or how Ben Casnocha loves to discuss how he's never smoked weed ("love" might be harsh, but do see his #2).

Our "nevers"'s allow us to signal loyalty to our groups in ways that our "tried once but didn't like it so please still accept me"'s can only dream of.

Trade Off #9: Some Now vs More Later

2010-09-22T23:32:00.000-05:00

In expected value terms, this trade off is everywhere. By doing work, we are trading some of our freedom now for more freedom later, since you can usually buy freedom (see here). When we invest, we give up some cash $ now to get more later, since interest rates typically beat inflation.

But, taking the long view of time preference, why would anyone ever rationally prefer less of something they want? There are a few reasons:

Everything is ephemeral (including, probably, the universe itself). So, there is no guarantee that if you wait until later, either you or the thing you are waiting for will even exist.
Values usually change as time passes. So, you might expect to value something so much less later that you can justify settling for the relatively lesser current amount of it.
If you learn to always delay gratification, you may find it difficult to ever actually reap the rewards you are meant to be aiming for, and continue to put off having fun into it is too late (see here).

You might have expected me to write that "there is only so much you can want of a good thing," but that is hippie nonsense. Also, while it's probably true that humans are irrationally biased to over-value immediate rewards (as in, I want another piece of cake right now), that isn't the whole story of this trade-off.

Ultimately, there actually are some legit reasons to prefer some now to more later. Sometimes there really is a dark, beneficial side to procrastination. Honesty demands us to admit these things, even though it might be simpler and easier to have a rule towards always favoring the delayed reward.

(Photo of clouds covering all but the tops of buildings in london from trexcali)

Trade Off #8: Random vs Determined

2010-09-18T21:45:00.000-05:00

This trade off concerns the decision to either leave things completely up to chance or to wholly micro-manage them, and every option in-between.

Now, it's true that attempting to alter the path of current events is the only way we can shift future outcomes towards our preferences. So because of that we should favor determining events. But there are large costs to determining that typically push us towards the random side of the trade-off, such as:

The opportunity cost of even weighing all the choices and outcomes, when you could be spending that energy on other ends. (see here)
The likelihood that, because we have attempted to change an outcome, we will come to regret our decision and see missed opportunities, which is psychologically taxing. (see here)
The likelihood that, even in taking action, we'll fail to improve outcomes over the status quo. And, despite our best intentions, the non-zero probability that our actions could even have negative expected value with respect to our goals. (see here)

The magistrates of the canon have spoken and decided that this one is huge. In large part, that's because it doubles as one of the fundamental questions about our universe.

(above photo by flickrer Jef Safi)

Long Run Optimism Depends On Short Run Pessimism

2010-09-16T00:09:00.000-05:00

Matt Ridley, according to the highest rated amazon review of his book*, believes that we have little to fear from the the long run sustainability of our energy consumption, because,

Yes, depending on non-renewable fuel, by definition, means that at some point, the fuel will run out. Ridley only points out that naysayers rely on a hidden but faulty premise: that the future will resemble the past. Yes, we will run out of fossil fuels if we keep using it, but whose to say that we will keep using them? ... these folks' error lies in assuming that future ways of production will resemble past ways, and time and time and time again, this assumption has proved erroneous! Ridley's point is that while we can NEVER say that the future WILL solve all pressing problems, so far we have. And we can assume we will in the future because our method of exchange has globalized the "collective brain," assuring that innovation will keep occurring and the best minds will all be working on the pressing problems of the day.

But what if the best minds are convinced by this very argument? Then they will, rationally, cease to work on solutions to these types of problems. So Ridley's argument is only true to the extent that people don't believe in it.

This works on an interpersonal level too. If you truly convince yourself that a situation will end up fine, you have zero incentive to do work to alter it. Thus, in the case that you are not worried at all about a situation, the situation will likely not turn out fine. This has tons of implications... but for tonight I'll just say that it's a cool paradox.

####

* 95.9% of people agree that, instead of reading the book, you mindswell just rely on Kevin Currie's review to draw sweeping inferences.

Intellectual Hipsters

2010-09-13T23:12:00.000-05:00

Yvain defines them as the third person in this scenario:

A naive person might think that [X] is an absolute good thing. Someone smarter than that naive person might realize that [Y] is a strong negative to [X] and desperately needs to be stopped. Someone even smarter than that, to differentiate emself from the second person, might decide [Y] wasn't such a big deal after all.

He also gives some examples, like "don't care about Africa / give aid to Africa / don't give aid to Africa", where the third position is the intellectual hipster.

His idea is pretty similar to my beloved conformity theory. One difference is that I conceptualize opinions moving around a circle (i.e. with two axes) whereas he seems to view them as oscillating between two poles.

To me, it doesn't make sense that beliefs would just jump from one point to another. At least subconciously, there has to be some kind of intermediate stance, like "I'm not sure, but I don't consider this issue interesting." The second axes of "caring" or "interestingness" allows the individual to justify holding the belief at every given time point. Otherwise, belief changing would have to happen on a threshold, and there are no thresholds.

A Critique Of The 10,000 Hour Rule

2010-09-08T18:35:00.002-05:00

Suzanne Lainson offers one here,

[Anders] Ericsson says that if you have experienced people who don't do any better than the average person, then they aren't experts. This seems to provide a good loophole to explain why average people can sometimes beat those with more experience. What he seems to be saying is that his theories are right, and when there appear to be exceptions, the exceptions don't count.

Now that's what I call a take down! The rest of the post is a veritable smattering of research bits, certainly not for the faint of nucleus accumbens, but it is interesting. She concludes that deliberately attempting to practice something for ten thousand hours isn't worth it, because it might not be sufficient for success and random unplanned experiences tend to be more life-defining anyway.

Three End Of Summer Thoughts

2010-09-07T12:17:00.002-05:00

1) As of today there are 800k+ articles currently tagged as "interesting" on del.icio.us, making it one of the site's most popular tags. But of course any link you go through the trouble of tagging you must have found interesting! The only way I can imagine this making sense is if people are using the word "interesting" to distance themselves from the conclusions of the article while admitting that some of the ideas are worth further contemplation. But that is unlikely to be the case for 800k articles, so what gives? (This annoys me more than it probably should.)

2) A co-worker brings in cupcakes early in the morning to share with everyone. I want to wait to have one so I can reward myself for working hard that day. But I'm worried that if I do so there will be none left. Gratification delay and the commons: antagonistic.

3) One question you may need to ask to determine whether you might be living in a simulation: given the ability, would you simulate your own life? Granted, this is frightfully solipsistic, but if I had such a power, I myself can definitely imagine simulating my own life again, tweaking various parameters to test the consequences. But how should I change my behavior based on the non-zero probability that I am living in my own simulation?!

The Arguments For And Against Re-Rating Movies

2010-09-06T14:28:00.004-05:00

The Prosecution: Changing one's mind about the quality of a given movie, or for that matter any given work of art, is a disgusting practice that ought to be accompanied by ruthless social disapproval. Re-rating allows and even encourages one to incorporate other's opinions into one's own ratings, heavily biasing them. Naïvely, many assume that this influence will always move ratings upwards and assure themselves that they won't merely follow the opinions of the most popular critics. But the reality of the conformity cycle is much more insidious: you are just as likely to learn that too many others like a movie and thus dislike it. There is no defense against these influences once you have been exposed to them, thus rating must happen early and remain steady despite the greatest of protestations. Ladies and gentlemen of the jury, I believe strongly, and upon contemplation I believe you will come to agree, that re-rating really is the bane of a high-functioning rating system.

The Defense: The vitriol of the prosecution's ad hominem attacks against everyday folks who happen to re-rate now and then, justified only by some childish appeal for purity, is dangerously short-sighted. If you don't understand a movie the first time you see it, that's not necessarily the movie's fault, it could be your own fault too. Thus it's totally understandable that, if you come to understand some angle of the movie better after conscious or unconscious contemplation, your rating might change. Moreover, the quality of a movie cannot be fully judged right after watching, because the quality of a movie is based not only on your experience during the movie, but also the value over replacement of any subsequent thoughts about that movie after watching. Thus a rating must be dynamic; it will change with the ebbs and flows of one's thought processes, the structure and patterns of one's interior life, and yes, maybe even one's interactions with other people. Re-rating is only natural given all of our other human tendencies, and its availability takes much unnecessary pressure and anxiety off of the initial rating. If we want to evolve as people, and more specifically as a society of movie watchers, then we must be willing to accept the consequences of such dynamicity. The defense rests.

The Verdict: Death by reruns of imdb's bottom 100.

Our Hands Evolved Because Our Feet Evolved

2010-09-05T13:52:00.000-05:00

A legitimately fascinating article (here) by Campbell Rolian, Daniel Lieberman, and Benedikt Hallgrímsson makes this claim, with substantially more precision. From the abstract:

Human hands and feet have longer, more robust first digits, and shorter lateral digits compared to African apes. These similarities are often assumed to be independently evolved adaptations for manipulative activities and bipedalism, respectively. However, hands and feet are serially homologous structures that share virtually identical developmental blueprints, raising the possibility that digital proportions coevolved in human hands and feet because of underlying developmental linkages that increase phenotypic covariation between them....

In particular, selection pressures on the feet led to longer, stronger thumbs, and slightly shorter other fingers. This makes it easier to hold something with the tips of our other fingers and thumb, in part because they are closer together, and in part because the forces on the thumb are dissipated over a larger surface area. This diagram might help you visualize:

modern human's pad-to-pad precision grasping, doi:10.1371/journal.pone.0011727.g001

Rolian et al go on to argue that:

[C]hanges in manual digital proportions that enabled digit tips to be brought into opposition may have been a prerequisite for the development of precision gripping capability in australopiths. Also, although pedal changes associated with facultative bipedalism probably provided australopiths with hands capable of producing and using Oldowan stone tools by at least 3.5 million years ago, it should be noted that manufactured stone tools do not appear in the archaeological record until about 1 million years later. Australopiths may have lacked the cognitive capacity for manufacturing tools and/or their technology was entirely nonlithic.... In short, there are several reasons to believe that selection on the foot caused correlated changes in the hand during human evolution, that selection on the hallux was stronger and preceded selection on the lateral toes, and that these changes in manual digital proportions may have facilitated the development of stone tool technology. (more here)

To over-simplify their claim: while feet were being selected for better load bearing and less mechanical work in running, it just so happened that this also made hands better suited for tool use.

So, the use of tools by early humans was due in large part to random chance. Since any event that relies on coincidence is less likely to be replicated, I read this as making the development of intelligence less likely / inevitable. If so, this means that the lack of other species in the night sky can be explained away in one more way--maybe most biological replicators don't get as lucky as we did in our evolutionary past to get a jumpstart towards tool use. Granted, this is rampant speculation and it's possible that we would have started using tools anyway.

But still, this makes it at least slightly more likely that we'll end up colonizing the known universe, instead of withering away on this doomed planet. And for today, I'll celebrate that.