A 2002 report (pdf) prepared by the CIA Counterterrorist Center discusses how terrorists recruit members in prisons such as Guantanamo Bay.
“Terrorists groups, including al-Qa’ida, use incarcerated members to recruit and train new members, and in some cases run terrorist organizations and manage or facilitate terrorist attacks.”
The classified CIA report was previously published on the web site The Smoking Gun.
See “Terrorists: Recruiting and Operating Behind Bars,” CIA Counterterrorism Center, August 20, 2002.
The last page of the document provides an extensive list of sources which are numbered — “but the numbers aren’t keyed to the text,” noticed former CIA analyst Allen Thomson.
He recalled being puzzled by this practice of decoupling the sources from the text more than two decades ago, and investigating the matter at the time.
“The list of sources wasn’t kept for reasons of documenting the reasoning that went into publications,” Mr. Thomson explained. “It was solely a security requirement so that, should somebody think that information had been published at too low a level of classification, the matter could be checked. Curiously, there was no master copy with the sources keyed to the text to aid in such security checking, so I suspect that checking was seldom done, if ever.”
Americans are paying too much for almost everything, because the United States has long treated its trucking industry as an artifact to be preserved rather than as an opportunity for innovation.
These ideas aim to advance the detailed policy solutions needed to foster public trust and implement fairness in the adoption of AI across diverse domains, from healthcare and government benefits to rural access, education, and worker protections.
The evidence is clear: algorithmic pay-setting is established in app-based work, and payroll/timekeeping failures show how software can produce systemic wage harm at scale
While a few states have taken steps to implement decision-making mechanisms for certain AI systems, too many leaders are simply accepting narratives about AI’s purported public benefit at face value – jumping to the “how” of AI implementation before thoroughly vetting potential systems and deciding whether they are appropriate to use at all.