** The new Journal of National Security Law & Policy has recently published its second issue featuring several meaty articles on interrogation, torture and the rule of law. The full contents of the issue, along with subscription information, are available online here.
** “Regulatory transparency–mandatory disclosure of information by private or public institutions with a regulatory intent– has become an important frontier of government innovation.” A new journal article assesses when and how such transparency works. See “The Effectiveness of Regulatory Disclosure Policies” by David Weil, et al, Journal of Policy Analysis and Management, Vol. 25, No. 1 (abstract only).
** The case of Sam Adams, the intelligence analyst who challenged official assessments of the size of Viet Cong forces during the Vietnam War, is revisited in a new book. “It’s the first complete narrative of the intelligence war at the heart of what went wrong in Vietnam, and it also happens to be highly relevant to what’s happening today in Iraq,” suggests the publisher. See “Who the Hell Are We Fighting? The Story of Sam Adams and the Vietnam Intelligence Wars,” by C. Michael Hiam, Steerforth Press, published April 25, 2006.
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.