Although there is no foolproof system of preventing unauthorized disclosures of classified information (“leaks”), there are a variety of new technical tools that can deter such disclosures or facilitate identification of those who compromise information security, according a 2002 CIA Task Force Report that was released last year under the Freedom of Information Act.
See “Interagency Task Force Report on Unauthorized Disclosure of Classified Information” (pdf), CIA Directorate of Science and Technology, 25 March 2002.
A supplementary paper argued that new legislation against leaks was “urgently needed.” The author singled out the National Security Archive and the Federation of American Scientists for propagating the “popular myth that the government over-classifies everything, and classifies way too much.” See “Leaks: How Unauthorized Media Disclosures of US Classified Intelligence Damage Sources and Methods” (pdf), Foreign Denial and Deception Committee, 24 April 2002.
The interagency process ultimately rejected the view that new legislation was needed. An October 2002 report to Congress from the Attorney General indicated that existing tools to combat leaks appeared to be adequate.
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.