According to Declan McCullagh, a just-released U.S. National Research Council report entitled Protecting Individual Privacy in the Struggle Against Terrorists: A Framework for Assessment concludes that automated identification of terrorists through data mining or any other mechanism “is neither feasible as an objective nor desirable as a goal of technology development efforts.”
I haven’t had the time to read through the 352-page report. The committee that wrote the report includes Stanford professor William Perry, former MIT president Charles Vest, and Microsoft researcher Cynthia Dwork. Such a crew undoubtedly realizes that any data mining technique yields false positives. The big questions are whether the data mining techniques are more effective than the alternatives, and whether the using them is consistent with law and policy.
Based on McCullagh’s summary, the report seems to mainly call for oversight and objective evaluation. Nothing controversial there. And, as he wryly notes, Americans may have watched too many episodes of 24 to have a realistic sense of what data mining can and can’t do.
Still, I think we’d be naive to give up entirely on machine learning approaches to fight crime and improve national security. As with all science, we need to subject hypotheses to rigorous, objective testing. But remember, low-tech approaches have false positives too. There is no moral superiority in being a Luddite.