Last year, U.S. Navy Lt. Cmdr. Matthew Diaz was convicted of unlawfully disclosing classified information to an unauthorized person, after he provided the names of prisoners secretly held in military detention at Guantanamo Bay to a civil rights organization. He was sentenced to six months in prison and ordered discharged from the Navy.
Last week, Diaz was honored as a “truth teller” at the National Press Club in Washington, DC for the very same action.
He received the Ridenhour Award, named for the late Ron Ridenhour, who revealed the 1968 massacre of Vietnamese at My Lai.
“Lt. Cmdr. Diaz demonstrated independent judgment, fidelity to the Constitution, and uncommon courage,” according to the Ridenhour Award statement. “By disclosing the names of prisoners secretly detained at Guantanamo, he broke ranks and he violated the law, and for that he has paid a serious price. But we believe that he also demonstrated a profound loyalty to the United States and its enduring constitutional principles.”
The April 3 remarks of Matthew Diaz upon receiving the Ridenhour Award may be found here.
The award ceremony and some of the background to it were described by Joe Conason in “A Truth Teller Who Deserves Justice,” Salon.com, April 4.
A longer treatment of the Diaz case appeared in “Naming Names at Gitmo” by Tim Golden, New York Times Magazine, October 21, 2007.
Remarkably, Diaz appears to be the first American ever convicted under the espionage statutes for disclosing classified information to another American rather than to a foreign person or government, according to a new study of espionage in America.
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.