After a court issued a ruling last spring that a Yemeni detainee held in U.S. custody should be released, the opinion was briefly published in the case docket and then abruptly withdrawn for classification review. When it reappeared, reporter Dafna Linzer discovered, it was not only redacted but had been significantly altered.
“The alterations are extensive,” she found. “Sentences were rewritten. Footnotes that described disputes and discrepancies in the government’s case were deleted. Even the date and circumstances of [the detainee’s] arrest were changed.”
Yet in what seems like an insult to the integrity of the judicial process, no indication was given that the original opinion had been modified — not just censored — as a consequence of the classification review. ProPublica obtained both versions of the ruling and published a comparison of them, highlighting the missing or altered passages. See “In Gitmo Opinion, Two Versions of Reality” by Dafna Linzer, ProPublica (co-published with The National Law Journal), October 8.
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.