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A Catch-Up Post: New Models

Some things that have caught my eye recently:

Ford is introducing technology that allows controls on automobile behavior to be designed into the key.  “Ensuring Junior Goes for a Mild Ride” in the NYTimes:

Like V-chips that restrict what children can view on television, MyKey allows parents to limit teenage drivers to a top speed of 80 miles per hour, cap the volume on the car stereo, demand seat belt use and encourage other safe-driving habits.

This raises some common questions:  How long will it take for the system to be hacked?  Is there a copyright hook in the design that would trigger a DMCA claim against hackers, or firms that supply hacking technology?  What happens to the data that the system generates?

“This Economy Does Not Compute,” also from the NYTimes, on an Op-Ed page last week:

Certainly, markets have internal dynamics. They’re self-propelling systems driven in large part by what investors believe other investors believe; participants trade on rumors and gossip, on fears and expectations, and traders speak for good reason of the market’s optimism or pessimism. It’s these internal dynamics that make it possible for billions to evaporate from portfolios in a few short months just because people suddenly begin remembering that housing values do not always go up.

Really understanding what’s going on means going beyond equilibrium thinking and getting some insight into the underlying ecology of beliefs and expectations, perceptions and misperceptions, that drive market swings.

Surprisingly, very few economists have actually tried to do this, although that’s now changing — if slowly — through the efforts of pioneers who are building computer models able to mimic market dynamics by simulating their workings from the bottom up.

The idea is to populate virtual markets with artificially intelligent agents who trade and interact and compete with one another much like real people. These “agent based” models do not simply proclaim the truth of market equilibrium, as the standard theory complacently does, but let market behavior emerge naturally from the actions of the interacting participants, which may include individuals, banks, hedge funds and other players, even regulators. What comes out may be a quiet equilibrium, or it may be something else.

I’ve been trying to figure out whether the credit crisis teaches any lessons for information and IP law and policy.  Maybe it doesn’t.  Has anyone looked into the relevance of recent computational economics research to economic models of IP production, distribution, re-use, and consumption?  I’ll give it a go but would welcome pointers.

“How Wall Street Lied to Its Computers,” again from the NYTimes. (I read other stuff, I really do.  Like Sarah Palin, I read The Economist!)

The people who ran the financial firms chose to program their risk-management systems with overly optimistic assumptions and to feed them oversimplified data. This kept them from sounding the alarm early enough.

The crisis can’t be reduced simply to an old model:  GIGO.  But that phrase has a powerful metaphorical and literal ring to it.  Maybe Ford could design a MyKey for risk managers?

2 thoughts on “A Catch-Up Post: New Models”

  1. I think there’s something very interesting going on culturally when people feel a need to defend the computers…to suggest that these wonderful machines didn’t mislead us, but rather duplicitous humans misled the machines.

    I also think that this essay by Taleb (author of The Black Swan) provides helpful perspective on the situation:

    As for the MyKey: I don’t think we should be looking for technical solutions. The bailouts reveal the primacy of politics–something that could be hidden when the SEC was making momentous deregulatory decisions in basement meetings, but which become obvious once the government has to become the lender of last resort. A credit freeze like what we’re seeing today proves definitively the need for collective action–that individual rationality (money-hoarding) can result in collectively disastrous outcomes. It’s amazing how many people dismissed this basic insight for so long…and how seriously they’re still taken today.

    The article on modeling sounds like what Stephen Wolfram has done with cellular automata and Steve Grand’s book Creation. But what if we simply find that the patterns revealed are random….as happened with at least one of Wolfam’s automata:

    Then perhaps we give up on the idea of modeling the human sciences on the natural sciences–something Charles Taylor pleaded for decades ago in Philosophy and the Human Sciences. The arrogance of that project has a Tower of Babel quality today: after piling up a mountain of CDO’s nominally worth trillions of dollars, traders around the world are now wondering whether the money they guard can be translated into real control over real resources. The answer is probably no: that the power of the state is the ultimate guarantor of not merely a stable trading order, but any reliable expectation of control over subsistence.

  2. PS–Given the new Dow plunge today, perhaps we should watch out for self-reinforcing buy technologies. . . . or methodologies. To what extent might a downturn become a panic because lots of computers are programmed to sell once a stock hits a certain level?

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