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.