The U.S. Navy has issued updated instructions on the use of nicknames to refer to Navy activities, events and other information.
“A nickname is a combination of two separate unclassified words, assigned an unclassified meaning that is employed for unclassified, administrative, morale, or public information purposes. Nicknames may be assigned to actual, real-world events, projects, movement of forces, or other non-exercise activities,” the new policy states.
“Nicknames should not be confused with code words. A code word is a single word assigned a classified meaning by appropriate authority to ensure proper security concerning intentions and to safeguard information pertaining to actual, real-world military plans or operations classified as CONFIDENTIAL or higher once activated.”
The choice of nicknames should not “express a degree of aggression inconsistent with traditional American ideals or current foreign policy.” Nor should it “convey anything offensive to good taste or derogatory to a particular group, sect, or creed.”
See “Code Word, Nicknames, and Exercise Terminology System” (pdf), OPNAVINST 5511.37D, January 30, 2007.
A dictionary of thousands of code words, nicknames and related terms was compiled by Bill Arkin in Code Names, published in 2005.
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.