Congress Imposes Limits on Sensitive Security Information
Congress adopted legislation that limits the ability of the Department of Homeland Security to withhold so-called “sensitive security information” (SSI), which is a category of restricted information related to transportation security.
The 2007 Homeland Security Appropriations Act would, among other things, require “the release of certain SSI information that is three years old unless the Secretary makes a written determination that identifies a rational reason why the information must remain SSI.”
The measure was signed into law by the President on October 4.
Former Rep. Helen Chenoweth-Hage (R-Idaho), who died this week, once challenged an airport security official who wanted to pat her down before boarding an airliner. She demanded to see the regulation that authorized such an action. The official refused, indicating that it was SSI and could not be shared with a member of the public. Rep. Chenoweth declined to submit, and took a car instead.
I retold this story in “The Secrets of Flight,” Slate, November 18, 2004.
Whether the government can impose such “secret law” is a question that has recently been presented to the Supreme Court by John Gilmore, who was told that he could not have access to the regulation requiring him to show his identification at the airport.
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.