Some recent reports of the Congressional Research Service that have not previously been made readily available in the public domain include the following (all pdf).
“Climate Change: Science and Policy Implications,” January 25, 2007.
“Foreign Science and Engineering Presence in U.S. Institutions and the Labor Force,” updated January 12, 2007.
“U.S. Military Dispositions: Fact Sheet,” updated January 30, 2007.
“Navy Ship Names: Background For Congress,” updated January 17, 2007.
“Latin America: Terrorism Issues,” updated January 22, 2007.
“U.S. National Science Foundation: An Overview,” updated January 24, 2007.
“War Powers Resolution: Presidential Compliance,” updated January 16, 2007.
“Laos: Background and U.S. Relations,” updated February 5, 2007.
“Kyrgyzstan’s Constitutional Crisis: Context and Implications for U.S. Interests,” updated January 5, 2007.
At the conclusion of a widely cited article on U.S. policy towards Iran in the latest issue of The New Yorker, Seymour Hersh referred to a November 2006 report by CRS “on what it depicted as the Administration’s blurring of the line between C.I.A. activities and strictly military ones.”
The referenced report is “Covert Action: Legislative Background and Possible Policy Questions,” November 2, 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.