“For those who believe in transparent government and fact-driven legislation, the power shift in the U.S. Congress represents a unique opportunity to open up one important Congressional institution — the Congressional Research Service — and bring back another one — the Office of Technology Assessment — twelve years after it was disbanded,” suggests Christian Beckner in Homeland Security Watch.
The Army Science Board has drastically reduced public disclosure of its unclassified advisory studies, Inside the Army reported. And by doing so, it may have undermined the impact of its own work. See “Citing Security, Army Tightens Reins On Science Board Research” by Fawzia Sheikh, Inside the Army, November 13.
The unprecedented prosecution of two former pro-Israel lobbyists who are charged with improperly receiving and disseminating classified information has unpleasant implications for reporters who cover national security, among others. The case was reviewed by civil libertarian Nat Hentoff in “Bush Revives Espionage Act,” Village Voice, November 10.
“The mainstream news media is too fond of articles in which it is said some flavor of demonical terror menace can be put together from cookbooks found on the Internet,” George Smith blasts on his Dick Destiny blog.
Federal Computer Week did a profile this week of, ahem, me. See “A career as a secrecy watchdog” by Aliya Sternstein, FCW, November 13.
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.