Economic ideology as backseat driving

I try to think of debates over governmental policy as being sort of like arguments over how to drive.

When driving, there are lots of complaints you can make as a backseat driver: e.g., depending on the conditions of the road, the obstacles ahead, and the needs of people in the car, and so on. If someone in the car is bleeding to death, then it may be reasonable to complaint that the car is going too slow; if, on the other hand, the driver is not very skillful or attentive, then it might be reasonable to advise against speeding. On this analogy, reasonable criticism has to be contextual. For instance, only a total weirdo would categorically say, “Hit the brakes!” in every context, unless they’re not in a hurry to go anywhere.

On this analogy, deficit spending is like hitting the gas, and balancing the budget is hitting the brakes. Saying “I’m a fiscal conservative” in politics is like saying you’re a Brakeist in cars. It isn’t a minimally intelligible policy position until you give a little rundown of things going on around you — the places you think we want to go, the needs of the people in the car, and the obstacles ahead, and so on.

‘Newroz’ Venn diagram: pancake edition

Some of our colleagues in BC — Khalegh Mamakani andFrank Ruskey at the University of Victoria — have discovered the first symmetrical 11-dimensional Venn diagram (Newroz). It is pretty.

It is quite a busy diagram, though. I thought it would be fun to see  how it looked if it were represented in 3D.

As New Scientist shows in the above diagram, here is what an individual set  — one of the “rose’s” “petals”, if you will — looks like:

Here’s what I came up with by fiddling with GIMP:

Looks like pancakes. Delicious, semi-transparent blue pancakes.

Netlogo, game theory, and the iterated prisoner’s dilemma

I think it’s safe to say that the Prisoner’s Dilemma is the single most famous illustration of game theory that is out there.

Most of the time, you’re only asked to imagine two rational actors, each deciding whether or not to defect on their partner. But now suppose that you have more than just two actors — suppose, instead, that there is a whole population of people, who constantly meet up and get thrust into the drama of a prisoner’s dilemma.

Further, let’s suppose that these actors have different strategies when they interact. Some folks always cooperate; some always defect. Some will cooperate so long as their partner did last time; others remember being betrayed and hold a grudge. Some are sado-masochists, who will loyally cooperate with those who have punished them sometime in the past; others are cowards, who will only cooperate with those who punished them recently. And some just cooperate or defect randomly. (For fun, you can get a handle on these strategies by imagining they are characters from Batman.)

Using these models, what kinds of strategies do we think will win out in the long run? Do nice guys (“cooperators”) finish last — or does crime really pay? Is it better to forgive, or to be ruthless? Using computer simulations, we can find out! Here are some interesting results from an iterated Prisoner’s Dilemma, simulated using the Netlogo software.*

In this scenario (call it ‘the Cosmopolis’), there are an equal number of people using each different strategy. The defectors (who always cheat) come out on top early, and remain ahead throughout. But in the long run, the ‘unforgiving’ punishers eventually outpace the ‘defectors’. This is a theme that you see recur in many, many different kinds of scenario.

So that’s interesting. Now what happens if a population — a culture — is dominated by one strategy?

In this case, I’ve overpopulated the culture with cowards, and left a few members of the other strategies kicking around. The result? A case of extreme inequality, where cooperators make very little, while the punishers and defectors make a killing.

Suppose that the culture was dominated by pure selfishness: the majority of people defect as a matter of principle. The result: goods are distributed more or less as it is in the Cosmopolis, except that everybody makes a lot less than they could have otherwise.

By contrast, in a culture of altruists, everybody makes a lot more than they would otherwise. The difference is that the punishers are strangely complacent, never overcoming the defectors. Moreover, the “bad” strategies — defectors, cowards, sado-masochists — come out making the most (which is, in my view, a morally perverse outcome).

Finally, in a culture of punishers, the “good” strategies (the punishers, cooperators, and reciprocators) come out ahead of the “bad” strategies (everybody else). This is a unique feature of this situation, since in most cases cooperation is the least successful strategy.

Going by the iterated Prisoner’s Dilemma, I would argue that the punishment world is, perhaps, the best of all possible worlds. Granted, it isn’t as prosperous as altruism world, but it is a world where you do reasonably well and have an incentive to be good. So perhaps Gene Roddenberry had it right.

* Hat-tip: Daniel Little. Uri Wilensky programmed the initial scenario. I added two new strategies, the ‘coward’ and ‘sado-masochist’.

UPDATE: Some of these results are not replicated by Lasse Lindqvist’s model of the Prisoner’s Dilemma.

Using Gephi to model philosophical networks in medieval Christendom

I was playing around with the Gephi beta graph designer, and thought it would be interesting to map out the network of Christian philosophers during the period 1000-1200.

Emphasis on betweenness centrality. Betweenness centrality is a measure of a node’s centrality in a network, equal to the number of shortest paths from all vertices to all others that pass through that node. Lanfranc is hardly a well-known figure in philosophy, but he looms conspicuously large here.

 

Emphasis on degree of linkage. Nodes are emphasized depending on the number of immediate neighbors they have.

Adapted from Randall Collins’s “Sociology of Philosophies” (p.464).