In 1993, Electronic Frontier Foundation co-founder John Gilmore observed, famously, that, 'The Internet perceives censorship as damage, and routes around it.' Now it's 2015, and the University of Maryland law professor Frank Pasquale has made an addendum: 'The same could be said about privacy.' With more corporate and governmental transparency, clear and effective regulation, and a widespread awareness of the dangers and mistakes that are already occurring, we can wrest back some control of our data from the algorithms that none of us fully understands.Black Box Society: The Secret Algorithms That Control Money and Information It is up to us to study the effects of those algorithms, whether they are racist, sexist, error-laden, or simply invasive, and take countermeasures to mitigate the damage. I’m inclined to believe it’s already too late-and that algorithms will increasingly have effects over which even the smartest engineers will have only coarse-grained and incomplete control. Pasquale stresses the need for an “intelligible society,” one in which we can understand how the inputs that go into these black box algorithms generate the effects of those algorithms. Philosophy professor Samir Chopra has discussed the dangers of such opaque programs in his book A Legal Theory for Autonomous Artificial Agents, stressing that their autonomy from even their own programmers may require them to be regulated as autonomous entities. Once the genie is out of the lamp through comprehensive and multifaceted monitoring of your Web habits, your purchases, searches, and social media activities go on sale and resale to the highest bidders, with everyone profiting except you-unless you consider invasive personalized ads a benefit. This customer information is considered highly valuable and lucrative, and Facebook has partnered with brokers like Turn (700 million user profiles) to get its hands on it (as I chronicled in my feature “ You Are What You Click”).

Pasquale writes that some third-party data-broker microtargeting lists include “probably bipolar,” “ daughter killed in car crash,” “rape victim,” and “gullible elderly.” There are no restrictions on marketers assembling and distributing such lists, nor any oversight, leading to what Pasquale terms “runaway data.” With such lists circulating among marketers, credit bureaus, hiring firms, and health care companies, these categories-which cross the line into racial or gender classification as well-easily slip from marketing tools into reputation indicators. Some of these categories are dicey enough that you wouldn’t want to be a part of them.

The black box society