We were sad to learn that intelligence historian Jeffrey T. Richelson passed away last weekend.
Richelson was one of a small number of pioneers of a new genre of public interest research focused on national security and intelligence. He advanced the boundaries of public knowledge and understanding of the far-flung national security apparatus through his writing based on official documents, carefully read and digested.
Richelson’s book The US Intelligence Community, published last year in its 7th edition, is so richly detailed as to be hard to read– but enormously valuable as a reference. Other works among the entire shelf of books and articles that he authored, such as Spying on the Bomb on the history of nuclear weapons-related espionage, displayed his story-telling gifts more engagingly.
Richelson had a resolutely independent, almost contrarian streak. In the 1990s when it was becoming conventional wisdom to say that the Central Intelligence Agency failed to anticipate the collapse of the Soviet Union, Richelson wrote an article in The National Interest called “The CIA Vindicated” (with Bruce Berkowitz) in which he argued that the opposite was the case.
Not least important, he was a kind and decent person and a generous colleague.
Jeff Richelson was remembered by the National Security Archive here.
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.