In a whirlwind conclusion to the prosecution of former National Security Agency official Thomas A. Drake, Mr. Drake agreed to plead guilty to a misdemeanor charge of “exceeding authorized use of a computer.”
Prosecutors were unable to sustain any of the felony counts against Mr. Drake that were contained in last year’s ten-count indictment, including charges of unauthorized retention of classified material under the Espionage Act of 1917.
A copy of the June 9, 2011 plea agreement is here.
Mr. Drake had been suspected of unauthorized disclosures of classified information to the press, though he was not specifically charged with that offense, and he denied committing it.
Much of the case was conducted behind closed doors and off the public record, so many intriguing aspects of its ultimate resolution remain obscure for the time being. But it seems clear that the Obama Administration misjudged the merits of its case against Drake, pursuing minor infractions with disproportionate zeal.
Meanwhile, Mr. Drake’s legal team, public defenders James Wyda and Deborah L. Boardman, did a superb job of defending their client in a challenging legal environment. Drake’s supporters at the Government Accountability Project managed to win a remarkable degree of public sympathy and support for a supposed felon.
Speaking of disproportionate zeal, I wrote last Monday that there was “no possibility” of avoiding trial on June 13. Consider this a correction.
See related coverage in the Washington Post, Politico, New York Times, Wall Street Journal, Washington Times, AP, MSNBC and Emptywheel.
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.