“Ridiculously optimistic” machine learning algorithm is “completely bullshit,” says expert.
In 2014, the former director of both the CIA and NSA proclaimed that “we kill people based on metadata.” Now, a new examination of previously published Snowden documents suggests that many of those people may have been innocent.
Last year, The Intercept published documents detailing the NSA’s SKYNET programme. According to the documents, SKYNET engages in mass surveillance of Pakistan’s mobile phone network, and then uses a machine learning algorithm on the cellular network metadata of 55 million people to try and rate each person’s likelihood of being a terrorist.
Patrick Ball—a data scientist and the director of research at the Human Rights Data Analysis Group—who has previously given expert testimony before war crimes tribunals, described the NSA’s methods as “ridiculously optimistic” and “completely bullshit.” A flaw in how the NSA trains SKYNET’s machine learning algorithm to analyse cellular metadata, Ball told Ars, makes the results scientifically unsound.
Somewhere between 2,500 and 4,000 people have been killed by drone strikes in Pakistan since 2004, and most of them were classified by the US government as “extremists,” the Bureau of Investigative Journalism reported. Based on the classification date of “20070108” on one of the SKYNET slide decks (which themselves appear to date from 2011 and 2012), the machine learning program may have been in development as early as 2007.
In the years that have followed, thousands of innocent people in Pakistan may have been mislabelled as terrorists by that “scientifically unsound” algorithm, possibly resulting in their untimely demise.