Vital Systems Security

One of the blog phenomena of this electoral cycle has been 538, a blog written by a statistician who uses simulation techniques to create predictive models for electoral outcomes. I haven’t looked into the details, but in their broad structure these models are similar to the simulations that we have been looking at from the 1960s on in the context of defense and emergency management. They incorporate a bunch of electoral and demographic data, and then run simulations using a randomizer (like a Monte Carlo simulation). Effectively, this randomizer produces a large number of different “worlds” — which are just outcomes of the simulator. Back in the day it took weeks to run one such simulation. But now, with massive computing power, every time new data comes in — in the form of new polls — they plug them in and run the simulation again. It is then possible to run standard statistical analyses on the outcomes of these simulations, essentially treating them like an archive of past events. If you check out the charts on the right side of the home page, you see an “electoral vote distribution” graph. This essentially shows the number of simulations that produced a given outcome in terms of electoral votes. From this you get some probabilities that a given candidate will win or lose, but also win or lose with different combinations of state-level outcomes.

In fact, this sort of thing is becoming increasingly routine. I have seen similar techniques applied, for example, to baseball statistics. (One particularly interesting example was an attempt to use simulations to figure out how likely it was that the record for consecutive games with a base hit would be tied or broken — the answer is fairly likely). And this is definitely the technique used in many formal catastrophe models.

In her recent book Just One Child, anthropologist Susan Greenhalgh traces the origins of China’s infamous ‘one child policy’ to a group of defense scientists who specialized in cybernetics and ‘control theory’. Her book is unabashedly both an analytic project and a criticism of the roots of the policy, that is to say, she begins from the claim that the ‘one child policy’ is an ethical bad and uses her analysis to discover what led to such unethical policy. Her claim that missile scientists were at the route of the policy, in other words, is a denunciation of a particular application of ‘natural science’ in government policy. First, I will tell a little bit of her story, which is incredibly interesting in its resonances with some of the topics we have been following in VSS. Then, I want to show how the perspective we have developed in the VSS research collaboration can productively engage as well as put in perspective her denunciation of cybernetic planning.
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It’s hallucinatory Friday in VSS land — and that must mean DARPA. Wired has an article about a $1.3 million contract to Lockheed for an “Integrated Crises Early Warning System.” They are seeing this, it seems, as a kind of “situational awareness” — but one that has less to do with enemy positions and more with, well, the social. ” David Honey, who is the head of DARPA’s Strategic Technology Office is quoted in the article as saying that “Commanders will always need to have an accurate picture of enemy positions, as well as friendly units and allies. But increasingly it’s social, cultural, political and economic information, foreign language capabilities and other clues – that are proving essential.” And who better for that than Lockheed?

Interestingly, the article points out, there is a history of similar efforts. For example, an integrated crisis warning system that was funded by the agency in the 1970s, and some other more recent efforts, including the ACUMEN (Anticipatory Culture-Based Modeling Environment) model, from which the diagram above is taken.

But actually it was something else in the article that really caught my eye. Wired makes a joke about “forecasting riots” — like the weather, ha ha. But in fact, as we have been finding out in our work on the Office of Emergency Preparedness, in the late 1960s and early 1970s it does seem that models of riots and models for things like natural hazards occupied a common space — or, more accurately, they were modeled using similar techniques. Hopefully we will have more to say about this when we start moving through the mountain of material that Onur and Brian brought back from the archives.