Prosecutors in the pending leak case of former State Department contractor Stephen Kim said they had discovered that the classified information Mr. Kim is accused of disclosing to a reporter without authorization had been circulated within the government more broadly than they had realized.
That discovery requires further investigation and disclosure to the defense, prosecutors said in a recent status report to the court.
“In short, the undersigned prosecutors have learned that the intelligence report identified in the Indictment had been used for purposes of drafting a separate intelligence product, which product was never finalized prior to the unauthorized disclosure at issue,” the status report said. “Some of the drafting occurred within the time period deemed relevant by the Parties.”
“The undersigned prosecutors are investigating this drafting process to determine its scope and what discoverable material may arise from it. The undersigned prosecutors have advised that their review of this additional information could take two additional months to complete before any materials related thereto are produced to the defense. While counsel for the defendant have not been informed of the content of this new information, counsel reasonably expect that it could have a material impact on their understanding of the government’s case, and likely will prompt additional discovery requests.”
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.
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.