One reason why classification is an unreliable guide as to what should or should not be published by the press is that classification policy is implemented erratically by the government.
In a new report for Congress, the Government Accountability Office found numerous problems in classification activity at the Department of Defense.
“Our review of a … sample of 111 classified DOD documents from five OSD offices shows that, within these offices, DOD personnel are not uniformly following established procedures for classifying information, to include correctly marking classified information,” the GAO report said.
“In our review of the OSD documents, we questioned DOD officials’ classification decisions for 29 documents–that is, 26 percent of the sample.”
“The majority of our questions centered around two problems: the inconsistent treatment of similar information within the same document, and whether all of the information marked as classified met established criteria for classification.”
See “Managing Sensitive Information: DOD Can More Effectively Reduce the Risk of Classification Errors” (pdf), June 30, 2006.
A companion report reviewed classification activity at the Department of Energy.
See “Managing Sensitive Information: Actions Needed to Ensure Recent Changes in DOE Oversight Do Not Weaken an Effective Classification System” (pdf), June 30, 2006.
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.
When properly structured — with specific numeric targets, secured financial obligations, independent monitoring, and meaningful enforcement — CBAs transform data center deals into durable community partnerships.