Assess whether an agent may take actions without a human gate (282fa5)

Situation

Vendor-diligence reviewer for AI tools in a city using a hiring-screen algorithm has one working extract — training-data provenance questionnaire — after a customer complaint that a chatbot invented a refund policy. If training-data provenance questionnaire cannot support an agent may take, the honest AI Governance output is hold.

Decision

Vendor-diligence reviewer for AI tools in a city using a hiring-screen algorithm must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using training-data provenance questionnaire after a customer complaint that a chatbot invented a refund policy.

Hypotheses to test

• Vendor-diligence reviewer for AI tools can defend Policy or governance breach from training-data provenance questionnaire after a customer complaint that a chatbot invented a refund policy in a AI Governance challenge.
• Vendor-diligence reviewer for AI tools cannot defend Policy or governance breach from training-data provenance questionnaire; Model defect is what the extract actually supports after a customer complaint that a chatbot invented a refund policy.
• A customer complaint that a chatbot invented a refund policy never reached the population in training-data provenance questionnaire — reopen intake, do not close an agent may take.
• Two facts in training-data provenance questionnaire after a customer complaint that a chatbot invented a refund policy conflict for vendor-diligence reviewer for AI tools; hold this Vendors and Agentic Systems file.

Analysis required

• Reproduce the incident row in training-data provenance questionnaire and say whether it ever touched production data.
• Split policy-or-governance failure from a model defect using prompts, outputs, and human edits in training-data provenance questionnaire.
• Reproduce the incident row in training-data provenance questionnaire and say whether it ever touched production data.
• For this AI Governance Vendors and Agentic Systems file, read training-data provenance questionnaire against a customer complaint that a chatbot invented a refund policy and write the one fact that would move an agent may take for vendor-diligence reviewer for AI tools.

Recommendation

Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance / Vendors and Agentic Systems packet (training-data provenance questionnaire after a customer complaint that a chatbot invented a refund policy). The follow-on Vendors and Agentic Systems action is what vendor-diligence reviewer for AI tools does next: implement the option, assign an owner, and log the missing fact.

Command returns

• Bottom-line AI Governance option on an agent may take, then the evidence in training-data provenance questionnaire, then the action for vendor-diligence reviewer for AI tools
• Hypothesis scorecard against training-data provenance questionnaire: supported / rejected / untestable
• What changes an agent may take if a customer complaint that a chatbot invented a refund policy is later withdrawn
• Named option among Policy or governance breach, Model defect, Dual failure and the fact that kills the others