James the Philistine

Game design is a tricky thing.  One aspect of game design is whether to allow players to perform tedious actions that improve their chances of winning the game (or improve other aspects of the game).  So for instance, in Baldur's Gate, you start by rolling dice to determine how many points you can allocate across different attributes (strength, intelligence, charisma, etc.).  The higher the number you roll, the better your character's attributes will be for the entire game, so it is a fairly important element of the game.  The result is that some players sit there clicking re-roll for hours, hoping for an extremely high number.

In general it might be seen as poor design for a game to reward tedious, joyless actions.  At least, it is something game designers should bear in mind.  So it occurs to me that artists and writers are in the same situation.  There are elements that you can include in a work of art, or a book, that will make it tedious or obscure or simply difficult.  Obviously that's called for sometimes, but it's something that bears some consideration.

In particular I think it's tricky when it comes to allegories and allusions.  I'm generally not a fan of allegory in books and movies, and I think it is really unpleasant to listen to someone "connect the dots."  ("See, the white horse represents Death, and the apple represents his dreams, and so when...")  It's almost as annoying to have to connect the dots yourself.  I think it's okay for there to be puzzles for the audience to solve, but I've almost never seen someone successfully use puzzles of the "decrypt the symbols" variety.

Allusions are trickier, if they are done right they can bring a lot of rich associations to the work, and other times they are merely little rewards for people who get the reference.  But if the work doesn't stand on its own, then it is going to be tough for readers/viewers who aren't steeped in whatever culture your references come from.

Of course the audience should have to do some work—I don't think there are any great books that aren't at least a little difficult.  But it can be overdone.  (Be  honest, how many of the allusions did you catch in this passage from Teju Cole's Open City?  I don't mean to criticize Cole—actually, I'm planning to write a post on how much I like the book—but this is just an insane amount of allusion.  Admittedly it seems mostly harmless in this case.)  It's an aspect of art/literature that requires very careful artistic choices, and it's one reason I favor moody, realistic movies over more stylized approaches.  The point is not necessarily being thrust in your face, but it isn't hiding behind layers of reference and symbolism.  (I really hope I'm not missing a bunch of allegory/allusion in Sang-soo Hong's movies.)

Maybe this is barbaric of me, maybe the pleasure of recognizing symbols/references is important.  What matters is the journey, not the destination.  Wordplay.  Mental agility.  This is what makes great art, and the meaning that is being conveyed is usually trite anyway.

In this connection, I think a lot of what passes for humor really amounts to difficult recognition.  (Aha!  A reference to Brideshead Revisited.  I will laugh to indicate my intelligence and sophistication.)  But while this can be annoying, I do it all the time.  In fact, I sometimes find these kind of references subjectively funny, so I'm not just laughing to show off.  (Or at least I'm not consciously laughing to show off.  It could be that I am programmed to laugh, that the showing off is going on at a subconscious level.)

So anyway it's a tricky area, but despite my reservations, I am a philistine on this point.  I like directness and emotional bareness, not artifice and intricacy and ironic distance.  Or maybe the way to put it is, I think those are more suited for amusement (like Archer) than for great art.  Great art should touch your soul.

Meaning and Magic in Bletchley Park

Sarang's third effort, Bletchley Park, is his most ambitious novel to date.  The story follows Basil Thwaite, a young mathematician recruited to work at the WWII-era code-breaking facility that gives the book its name.  Basil excels at his work, but he struggles to fit in with his fellow cryptographers.  He is not bullied, as he was at public school, but he finds social interaction to be baffling and embarrassing.  He retreats further and further into the clean, crystalline world of math, searching for meaning in the intercepted Nazi messages that flow into Bletchley Park.

Here the story takes a bizarre turn.  Where the rest of the team struggles to decrypt the incoming gibberish, Basil starts to discover too much meaning.  The dramatic moment arrives when Basil, discomfited by an encounter with an attractive coworker, accidentally starts decrypting a message he had already decrypted.  As the message resolves, Basil realizes that its interpretation has changed, that a slight difference in sequence has resulted in an entirely different, but completely intelligible, message.  The first message described a petrol shortage on the eastern front; the second assesses the political reliability of a Vichy official.  Basil is thrilled—he seems to have defeated the Nazis' attempt to smuggle one message under the cover of another.

But as more and more possible meanings emerge, excitement soon gives way to doubt and confusion.  After all, which of the interpretations is correct?  Is it a petrol shortage?  A disloyal operative?  New orders for the U-boats?  A warning about Dutch saboteurs?  It is beyond belief that the Nazis would undertake the laborious task of weaving all of these messages together.  After all, why bother?  But what other explanation could there be?

The Allied leadership becomes frustrated as Bletchley Park's output becomes sporadic and unreliable, and severe pressure is placed on Basil's superiors to fix the problem.  But there is no way to justify choosing one interpretation over another.  It is unacceptable to give the generals dozens of interpretations of each intercepted message; it is equally unacceptable to pick interpretations at random.  The Allies expend significant resources in a desperate attempt to test the different interpretations, but no systematic pattern emerges.  The longer Basil works on an intercepted message, the more interpretations he produces, but all interpretations seem to have an equal (and low) chance of being correct.

In the hands of a lesser writer, Bletchley Park could easily dissolve into a hazy morass, but Sarang doesn't let the Allies' dilemma overwhelm the story.  In fact, as Bletchley Park becomes near-useless, Basil becomes increasingly detached from his work.  Distrusted by some of his coworkers and despised by others, he spends his time reading philosophy, history, and economics, occasionally venturing to the local pub for beer-soaked debates.  Bletchley Park shifts back and forth between Basil's forceful, slightly muddled arguments and tense discussions within the Allied leadership.  As Basil broadens his analysis, the military view narrows, and we see an inversion of sorts.  Basil is concerned with the big questions of the Empire:  Indian home rule, Palestine, the sterling area.  Meanwhile the Empire is increasingly focused on the narrowest of questions:  what is it to make of the profusion of increasingly erratic intelligence coming from Bletchley Park?

Some readers will find Sarang's meandering, discursive storytelling unsatisfying, while others will find his hyper-realistic sex scenes unsettling.  But the book is the most emotionally honest that Sarang has written, and the first that can really be called a book of ideas.  One gratifying result is that Sarang has managed to avoid the irony/sincerity debate entirely.  The book is so earnest, and yet appears so light and effortless, that it seems to exist on a different dimension, like an imaginary number hovering over the real number line.  It is not always a pleasure to read, but it leaves the reader with such a whirlwind of ideas that few readers will be able to put it out of their minds until long after they finish it.

A Strange Kind of Courage

The older I get, the more I think that everyone should take a decision-making class at some point, probably early in college.  To use one of my favorite examples (which I actually did learn in college, but not very well):  Imagine that you have a machine, like a slot machine, with two different levers.  You can pull one of the levers each day (each day you choose which lever to pull).  Each time you pull a lever, you get a payout of some kind.  Assuming the payout is always desirable (you can never get too much of whatever the machine is dispensing), you should choose the lever that you expect will result in the higher payout.

But there is no transparency about how payouts are determined.  All you can do is observe past payouts and try to extrapolate into the future.  Are the payouts predictable according to an orderly function?  Does lever A always pay out 5 and lever B always pay out 10?  (Should you check lever A every once in a while just to make sure it is still paying only 5?)

So you can work through different approaches, and I think AI/machine learning classes deal with examples like this.  But what is great about the example is that it brings up deeper issues about what we can learn about the world. For instance, it's a pretty neat illustration of the classic Hume point:  even if there is a strong empirical regularity in the payouts, who is to say that the next payout will behave according to that regularity?  You have no direct access to the machine's algorithm, so it is always a matter of assuming, on some level, that the future will resemble the past.  And even if you don't want to embrace extreme skepticism on this point, you still have to make assumptions about the validity of extrapolating from one set of data to another.  Models stop being true, and they don't always do it in predictable ways.  (There are also infinitely many models that would generate any observed set of payouts, so you have the issue of choosing which of those models is better or worse.)

And so it's a great introduction to empirical methods, and the limits of those methods.  And I think that would be true of a bunch of other decision-making examples (although it's something I'm still not very knowledgeable about).  For instance, a related problem is the bounded-rationality (or limited-processing-power) problem.  The basic idea is, say you want to optimize something, but your time and effort are themselves limited.  So you might ask, "How much time should I spend investigating the optimal solution to problem A vs. problem B?"  But solving that problem (which you could call problem C) itself requires time, so really you have to allocate among A, B, and C.  But that allocation problem (allocating time among A, B, and C) is itself a distinct allocation problem, and so now you have problems A, B, C, and D.  And so on.

In real life you just make some kind of ad hoc decision based on your intuition.  And so it becomes clear that the basic tools of decision-making, like quantitative analysis, only get us so far, and we are left with ineradicable subjectivity and imperfection.  And that is a crucial lesson, because it empowers us to be decisive even in the fact of uncertainty and doubt.  In other words, the intellectual journey goes something like this:

1.  Comprehending the difficulty of making choices under uncertainty.

2.  Learning some quantitative approaches that have promise.

3.  Learning some of the limitations of those approaches.

4.  Realizing that decisions have to be made notwithstanding the recognized limitations, and therefore adopting appropriate standards for what counts as a good basis for a decision.  Something better than coin-flipping and worse than perfection.

And hopefully then comes realization that this is where we live our lives, somewhere between coin-flipping and perfection.  The idea that decision-making can be reduced to a "science" can be discarded, and so can the idea that "you can't do better than coin-flipping."  (I guess there are corner cases where coin-flipping is as good as anything else, but there are plenty of cases that aren't like that.)  Decision-making is just a messy business, but you have to go forward with it anyway, with the best tools you can bring to bear.  You may be making the wrong decision, but what does that have to do with the price of tea in China?  You are always running the risk of making bad decisions.  You are always relying on imperfect, ad hoc judgments.  Once this is internalized, there is no reason to shy away from a possibly bad decision in any particular instance.  It's a strange kind of courage, since it comes from the recognition that you can never be very confident in your decision-making, but what matters is that it emboldens you to make decisions when it is necessary.

Scientism and Libertarianism

There has been a recent flare-up in the scientism debate, with Richard Dawkins Steven Pinker (sorry!) trying to reclaim the term, Douthat responding to Dawkins Pinker, Douthat making the case against Sam Harris, and Ta-Nehisi Coates going after Bloomberg's technocracy.  I intend to think and write more about it, but to start I want to make a comparison that I think captures an important dynamic in the debate.

So here it is:  scientism is like libertarianism in several ways, and this helps explain why it is so galling to me.  Consider:

1.  Libertarians cloak themselves in the language of freedom, going so far as to name their ideology after liberty, which is almost universally admired.  Science chauvinists (my term for practitioners of scientism - "scientist" having been taken) do the exact same thing, invoking "science" as if the debate were "science:  thumbs up or thumbs down?"

2.  But of course everyone supports science (and liberty) in the abstract.  What people object to is the use of the term "science" to advance a narrow and tendentious version of the concept.  Again, it's the same trick libertarians try to pull.  Everyone is in favor of liberty, but not everyone agrees that income taxation is morally equivalent to chattel slavery.

3.  And if you take a properly broad view of science (or of evidence-based reasoning, if you prefer), you will find that the decision to be pro- or anti-science gets you almost no traction in particular cases.  This example came up in a discussion with Grobstein.  Imagine that my girlfriend has cheated on me, and I have discovered the lapse.  (This example is not based on real life.)  Imagine I find some studies that suggest that, among people whose partners cheat on them and who forgive the cheating partner, 85% are happy with the decision, while among those who break up over the infidelity, 75% come to regret it.

These numbers are highly suggestive, but imagine that my friends urge me to break up with her anyway.  They know her, they know me, they know the facts of the situation, and they think I should break up with her over the infidelity.  As Grobstein pointed out when we talked, the study is only as good as its construction, and its conclusion is only applicable within its proper scope.  Its subjects are people who are similar to me in one respect, but there may be salient differences not evident on the face of it, and a study of people who are more similar to me may yield different results.  On top of that, my friends have access to all kinds of data that may be relevant, and that data was (of course) not taken into account in the scientific study.

So what is the "scientific" thing to do?  I hope it's clear that this is not a helpful question, or at least it doesn't add anything to the overarching question, which is "what is the right thing to do?"  Anyone who claims I should forgive her because that's the "scientific" thing to do is engaged in (a mild form of) scientism.

And the same goes for freedom in a lot of policy discussions.  If I levy a tax and use the proceeds to make public areas accessible to disabled people, have I reduced freedom or increased it?  If I regulate a market in such a way that it becomes much more active (for instance, by solving asymmetrical information problems), have I increased liberty (the freedom to trade) or reduced it (by imposing regulatory burdens)?

Again, I hope that it's clear that the "more freedom!" framework is fruitless here.  And in fact it's fruitless in almost any policy discussion.  It is a high-level value that should guide our instincts, but it is not a clearly articulable principle that can be deployed like a surgical instrument.  All of the interesting questions involve the fine details of the tradeoffs we make between kinds of freedom, and between freedom and other values.  The question is almost never resolved by an investigation into whether freedom is good or not.

And that's what I think about science.  Science as an approach to life is very powerful.  I wouldn't want to live in a society that wasn't steeped in the scientific virtues:  inquisitiveness, respect for data, hypothesis-testing, etc.  But the idea that we can deploy "science" as a fine-grained tool to sort good ideas from bad is misguided and dangerous.  And it is especially obnoxious to be accused of being anti-science when I refuse to embrace some narrow conception of science like cost-benefit analysis.