Last month, Malmstrom Air Force Base in Montana announced the adoption of what it calls a “100 percent shred policy for all paperwork and materials generated on base” as a way of eliminating unauthorized disclosures.
“Shredding is vital to the overall security of our base and our mission,” said Eileen Gallagher, 341st Communications Squadron Base Records Manager. See “Getting into the habit: 100 percent shred policy begins March 17,” Malmstrom AFB, March 10, 2009.
As authority for the new shredding policy, the Air Force cited a March 2008 directive on Operations Security (pdf), which does indeed specify a “100% Shred Policy” (at section 1.4.18.2):
“Whenever feasible, all unclassified paper products across AFSPC [Air Force Space Command], except for newspapers and magazines, will be shredded prior to disposal or removal from the workplace for recycling, preventing our adversaries from exploiting the enormous amounts of crucial information we generate while accomplishing our various mission areas.”
On close inspection, however, the words “prior to disposal” seem to be crucial. The 100% shred policy apparently applies only to records that have been specifically approved for disposal, and not literally to “all paperwork and materials generated on base.” Air Force Manual 33-363 on “Management of Records” (pdf) directs all Air Force employees to adhere to legal requirements on preservation of official records.
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.