ODNI Declassifies Data on Frequency of Surveillance
The Office of the Director of National Intelligence released the “2013 Statistical Transparency Report” detailing the frequency of use of various intelligence surveillance authorities and the estimated number of targets affected by the surveillance.
While the reported numbers give some rough sense of the scale of intelligence surveillance — civil liberties groups said the estimated numbers are bound to be misleadingly low — the report provides no basis for evaluating the utility or legitimacy of the surveillance activities.
How many of the collection activities were authorized on the basis of erroneous information? How many actually produced useful intelligence? The report doesn’t say, and the raw numbers are not a substitute. If they were ten times higher, or ten times lower, we would be none the wiser.
(A supplemental response from ODNI to Senator Wyden was released today.)
See U.S. Phone Searches Expanded in 2013 by Siobhan Gorman, Wall Street Journal, June 27, and related coverage elsewhere (WashPost, Wired, Openthegovernment.org, Huffington Post).
From a secrecy policy point of view, perhaps the most intriguing feature of the new release is the unconventional timing of its declassification. The report is dated June 26, 2014 and was classified at the TOP SECRET/NOFORN level. But it says it was declassified by DNI Clapper three days earlier on June 23, 2014!
This temporally fluid approach to declassification could have many useful applications.
The real opportunity of AI lies not just in the tools, but in an educator workforce prepared to wield them. When done right, this investment in human infrastructure ensures AI accelerates learning outcomes for all students, closing the “digital design divide.”
If carbon markets are going to play a meaningful role — whether as engines of transition finance, as instruments of accurate pricing across heterogeneous climate interventions, or both — they need the infrastructure and standards that any serious market requires.
Good information sources, like collections, must be available and maintained if companies are going to successfully implement the vision of AI for science expressed by their marketing and executives.
Let’s see what rules we can rewrite and beliefs we can reset: a few digital service sacred cows are long overdue to be put out to pasture.