The Journal of Defense Research (JDR) was a classified publication sponsored by the Defense Advanced Research Projects Agency to encourage dissemination of classified research on topics of military or national security interest. It began publication in 1969, replacing the former Journal of Missile Defense Research.
Many years later, most of the Journal’s contents still seem to be classified, but the table of contents of the Journal’s first decade (pdf) has been declassified and is now available on the Federation of American Scientists website.
Perhaps unsurprisingly, most of the names of the authors whose work was published in JDR are unfamiliar, with a few exceptions (e.g., Garwin and Augustine; Hugh Everett’s name does not appear). The topics of the papers provide a snapshot of the technologies and the strategic concerns of the time, and give an indication of the scale of classified government research that was devoted to addressing them.
“The JDR is ‘mission essential’ as a classified research tool,” a Defense Science Board Task Force (pdf) stated in 1985. “Being the only classified journal of its type, the JDR is used to communicate ideas amongst the defense community and is a basic tool for researchers.”
Update: Additional JDR index material is available here.
Protecting the health and safety of the American public and ensuring that the public has the opportunity to participate in the federal decision-making process is crucial. As currently organized, FACs are not equipped to provide the best evidence-based advice.
As new waves of AI technologies continue to enter the public sector, touching a breadth of services critical to the welfare of the American people, this center of excellence will help maintain high standards for responsible public sector AI for decades to come.
The Federation of American Scientists supports the Critical Materials Future Act and the Unearth Innovation Act.
By creating a reliable, user-friendly framework for surfacing provenance, NIST would empower readers to better discern the trustworthiness of the text they encounter, thereby helping to counteract the risks posed by deceptive AI-generated content.