House Moves to Limit “Sensitive Security Information”
The scope of the “sensitive security information” (SSI) control category that prevents disclosure of certain kinds of transportation security-related information would be significantly curtailed by the House version of the 2007 Department of Homeland Security Appropriations Act.
The House bill would mandate automatic disclosure of SSI when it becomes three years old if it is not part of an active security plan and unless a written determination is made by the Secretary that it must be withheld.
It would also require DHS to revise its written policy on SSI to provide common representative examples of what constitutes SSI, and it would make it easier for parties in litigation to gain access to SSI. See the SSI provision in the 2007 Homeland Security Appropriations bill, which awaits final action on the House floor, here.
The White House denounced the House measure.
“The Administration strongly opposes Section 525 [the SSI provision], which would jeopardize an important program that protects Sensitive Security Information (SSI) from public release by deeming it automatically releasable in three years…,” according to a May 25 Statement of Administration Policy (pdf).
“This provision would require the Secretary to undertake an ongoing, burdensome review process to protect this secure sensitive information that would otherwise remain appropriately protected by regulation,” the White House said (at page 4).
And see, relatedly, “Homeland Security Department: FY2007 Appropriations” (pdf), Congressional Research Service, May 10, 2006.
Commercial artificial intelligence tools have recently emerged that are able to produce police reports. If the resulting reports are inaccurate, incomplete or biased, or if the process leaks confidential information, this could undermine the criminal justice system and harm citizens.
Too often, affected patients, clinicians, and regulators cannot see how the system works, why a decision was made, or whether meaningful human oversight occurred.
Existing tools from other domains, such as existing robust public engagement processes in drug development, when applied to AI deployment can help strengthen public trust in these systems and enhance perceptions of their legitimacy and the decisions they produce.
With thoughtful policy action, it is still possible to build systems that are fair, transparent, and accountable, and to earn the public trust that will ultimately determine AI’s future. We hope policymakers are ready to act.