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09:30

Compartmentation is hard, but the Big Data playbook makes it harder still

A new study of Palantir’s systems and business methods makes sobering reading for people interested in what big data means for privacy.

Privacy scales badly. It’s OK for the twenty staff at a medical practice to have access to the records of the ten thousand patients registered there, but when you build a centralised system that lets every doctor and nurse in the country see every patient’s record, things go wrong. There are even sharper concerns in the world of intelligence, which agencies try to manage using compartmentation: really sensitive information is often put in a compartment that’s restricted to a handful of staff. But such systems are hard to build and maintain. Readers of my book chapter on the subject will recall that while US Naval Intelligence struggled to manage millions of compartments, the CIA let more of their staff see more stuff – whereupon Aldrich Ames betrayed their agents to the Russians.

After 9/11, the intelligence community moved towards the CIA model, in the hope that with fewer compartments they’d be better able to prevent future attacks. We predicted trouble, and Snowden duly came along. As for civilian agencies such as Britain’s NHS and police, no serious effort was made to protect personal privacy by compartmentation, with multiple consequences.

Palantir’s systems were developed to help the intelligence community link, fuse and visualise data from multiple sources, and are now sold to police forces too. It should surprise no-one to learn that they do not compartment information properly, whether within a single force or even between forces. The organised crime squad’s secret informants can thus become visible to traffic cops, and even to cops in other forces, with tragically predictable consequences. Fixing this is hard, as Palantir’s market advantage comes from network effects and the resulting scale. The more police forces they sign up the more data they have, and the larger they grow the more third-party databases they integrate, leaving private-sector competitors even further behind.

This much we could have predicted from first principles but the details of how Palantir operates, and what police forces dislike about it, are worth studying.

What might be the appropriate public-policy response? Well, the best analysis of competition policy in the presence of network effects is probably Lina Khan’s, and her analysis would suggest in this case that police intelligence should be a regulated utility. We should develop those capabilities that are actually needed, and the right place for them is the Police National Database. The public sector is better placed to commit the engineering effort to do compartmentation properly, both there and in other applications where it’s needed, such as the NHS. Good engineering is expensive – but as the Los Angeles Police Department found, engaging Palantir can be more expensive still.

Don't be the product, buy the product!

Schweinderl