Kobe In Crunch Time: Efficiency vs Predictability

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

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

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 wild 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

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

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

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

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

"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

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

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

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

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

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

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)