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COMPUTING SCIENCE

Machine Politics

Brian Hayes

Beyond Human Control

When computer-aided redistricting was first talked about 30 years ago, it was supposed to end political gerrymandering. So far, it has mainly had the opposite effect, providing a better tool for the manipulation and coordination of political data. As computers and software systems grow more powerful, gerrymandered districts will doubtless become both more effective and more subtly hidden.

The algorithmic approach offers an alternative, but it would require a major shift in attitude and expectations—a meta- political revolution. No longer would redistricting be an opportunity to seize political advantage; it would have to be seen as a neutral or arbitrary event, beyond human control, above politics, subject to luck, much like the random choice of which candidate's name is listed first on a ballot. Redistricting would also be lost as an instrument for achieving social goals, such as creating a more racially balanced Congress.

If algorithmic redistricting is not to become another form of high-tech gerrymandering, the mandated algorithm would have to be spelled out in exacting detail, leaving no discretion to the programmer or the operator of the computer. The specification of the algorithm would also have to be openly published, presumably as part of a statute, so that anyone could write a program to check on the result of the official computation. And the specification would have to be so explicit and detailed that every correct implementation of the algorithm would give identical results on all legal inputs.

Legislators have little experience writing algorithmic specifications. Even for experts, creating a correct and ambiguity-free definition of a practical redistricting algorithm would be a daunting challenge. Of necessity, the algorithm would have to be a simple one. Elaborate weighing and balancing of multiple criteria, or complicated hints and heuristics, would leave too much room for mistakes and mischief. Also, the algorithm would have to be deterministic, so that it would always yield the same result on the same input data. And the required inputs themselves would have to be simple and trusted, perhaps limited to what the Census Bureau supplies.

After a few weeks of experimenting with redistricting algorithms, am I prepared to turn the nation's political map over to computers? I'm unsure. There is no doubt that people can draw much better districts than any simple program can. Unfortunately, people can also draw much worse districts. Thus the question of whether we would be better off with people or machines drawing district lines depends on one's assessment of the intentions and character of the people or the machines who would do the drawing.





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