Big Data Surveillance Results in Bad Policy
Evgeny Morozov makes a point about surveillance and big data: it just looks for useful correlations without worrying about causes, and leads people to implement “fixes” based simply on those correlations—rather than understanding and correcting the underlying causes.
As the media academic Mark Andrejevic points out in Infoglut, his new book on the political implications of information overload, there is an immense—but mostly invisible—cost to the embrace of Big Data by the intelligence community (and by just about everyone else in both the public and private sectors). That cost is the devaluation of individual and institutional comprehension, epitomized by our reluctance to investigate the causes of actions and jump straight to dealing with their consequences. But, argues Andrejevic, while Google can afford to be ignorant, public institutions cannot.
“If the imperative of data mining is to continue to gather more data about everything,” he writes, “its promise is to put this data to work, not necessarily to make sense of it. Indeed, the goal of both data mining and predictive analytics is to generate useful patterns that are far beyond the ability of the human mind to detect or even explain.” In other words, we don’t need to inquire why things are the way they are as long as we can affect them to be the way we want them to be. This is rather unfortunate. The abandonment of comprehension as a useful public policy goal would make serious political reforms impossible.
Forget terrorism for a moment. Take more mundane crime. Why does crime happen? Well, you might say that it’s because youths don’t have jobs. Or you might say that’s because the doors of our buildings are not fortified enough. Given some limited funds to spend, you can either create yet another national employment program or you can equip houses with even better cameras, sensors, and locks. What should you do?
If you’re a technocratic manager, the answer is easy: Embrace the cheapest option. But what if you are that rare breed, a responsible politician? Just because some crimes have now become harder doesn’t mean that the previously unemployed youths have finally found employment. Surveillance cameras might reduce crime—even though the evidence here is mixed—but no studies show that they result in greater happiness of everyone involved. The unemployed youths are still as stuck as they were before—only that now, perhaps, they displace anger onto one another. On this reading, fortifying our streets without inquiring into the root causes of crime is a self-defeating strategy, at least in the long run.
Big Data is very much like the surveillance camera in this analogy: Yes, it can help us avoid occasional jolts and disturbances and, perhaps, even stop the bad guys. But it can also blind us to the fact that the problem at hand requires a more radical approach. Big Data buys us time, but it also gives us a false illusion of mastery.
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