The problem of overclassification — in which inappropriate restrictions are imposed on the disclosure of information in the name of national security — is at the root of many current disputes over access to government information, including controversies over leaks, FOIA litigation, prepublication review, and others areas of contention.
This has been true for many years, but there is still hardly any systematic method for confronting and correcting overclassification.
In a new article at ForeignPolicy.com, I take a critical look at the current policy landscape, including the newly enacted Reducing Over-classification Act and the pending Fundamental Classification Guidance Review. See “Telling Secrets,” October 15.
The United States federal government invests nearly $150 billion annually in research and development. However, the supporting evidence generates wildly different estimates depending on the methods and available data.
The digital government field has an opportunity to build a more responsive and resilient government by pushing into new frontiers, with new tools, approaches, and even organizations that don’t exist yet. This is the time for radical experimentation, delivery, and exploration.
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.