Primum non nocere: Applies to policy recommendations too


Posted on October 7, 2017  /  0 Comments

Yesterday I was at the launch of a report on cloud computing by the Lee Kuan Yew School of Public Policy funded by Microsoft in Manila. Listening to the presentations and then reading the report, I was surprised that there was no discussion whatsoever on any risks that may come with a move to cloud by developing countries. I had written such a discussion for UNCTAD a few years back and blogged about it subsequently.

But it’s too easy to beat up on other people. We should always apply these kinds of tests on ourselves. Today’s NYT discussion of the role of computers in the scandalous gerrymandering in the US makes me ask whether we have adequately discussed the harms that could be caused by our demarcation work. We will address the possible harms soon.

But this isn’t just a politics story; it’s also a technology story. Gerrymandering used to be an art, but advanced computation has made it a science. Wisconsin’s Republican legislators, after their victory in the census year of 2010, tried out map after map, tweak after tweak. They ran each potential map through computer algorithms that tested its performance in a wide range of political climates. The map they adopted is precisely engineered to assure Republican control in all but the most extreme circumstances.

In a gerrymandered map, you concentrate opposing voters in a few districts where you lose big, and win the rest by modest margins. But it’s risky to count on a lot of close wins, which can easily flip to close losses. Justice Sandra Day O’Connor thought this risk meant the Supreme Court didn’t need to step in. In a 1986 case, she wrote that “there is good reason to think political gerrymandering is a self-limiting enterprise” since “an overambitious gerrymander can lead to disaster for the legislative majority.”

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