Checklist

AI Pilot Safety, Ethics & Impact Checklist

An interactive, savable checklist to evaluate safety, human-in-the-loop boundaries, data quality and bias, failure modes, operator impact, guardrails, rollback plans, and measurable success criteria before launching an AI pilot.

Interactive Tool

AI Pilot Safety, Ethics & Impact Checklist

This interactive checklist helps teams evaluate safety, ethics, human-in-the-loop boundaries, data readiness, operational impact, and measurable success criteria before launching an AI pilot. Save responses to create a record of decisions, required mitigations, and approval status.

Enter a concise pilot name that identifies the system, line, or problem (e.g., 'Vision QC for Line 3 - Defect Detection').
Internal tracking ID or ticket number if available.
Name and role of the person accountable for the pilot.
Assessment date (YYYY-MM-DD).
Briefly describe the operational problem the AI will address and the expected benefit (quality, throughput, reduced downtime, safety, etc.).
Quantify expected benefits (e.g., estimated % OEE improvement, cost savings, % fewer defects, time saved). Provide ranges if uncertain.
1 = low confidence, 5 = high confidence based on prior evidence or prototypes.
1.0 10.0
List each data source, owner, sample size, known gaps, and typical data quality issues (missing data, noise, label quality).
1 = poor (major gaps), 5 = excellent (representative, labeled, consistent).
1.0 10.0
If yes, list controls and compliance requirements in the mitigation field below.
Describe encryption, anonymization, access controls, retention limits, and approvals required.
Choose the mode of operation and ensure appropriate controls for each.
Assess potential impact: from nuisance to safety-critical outcomes.
Describe exactly what operators or supervisors must do in normal operation and when the system flags uncertainty or anomalies.
List credible failure modes (false positives, false negatives, data drift, connectivity loss) and the operational impact for each.
If yes, a higher level of verification and physical safeguards are required.
Technical and procedural mitigations (fallback modes, alarms, manual overrides, redundancy, training).
Which operator roles are affected? How will workflows change? What new responsibilities are introduced?
Helps scale training and communication plans.
Training should include normal operation, error states, and rollback procedures.
Describe format (hands-on, e-learning), who must complete it, and how completion is verified.
List automatic checks, thresholds, dashboards, alerts, and frequency of human review.
Rollback should be quick and safe with clear ownership.
Provide step-by-step actions and contact points for emergency rollback.
List exact metrics, baseline values, targets, and statistical confidence required for success (e.g., precision, recall, reduction in defects).
How long will you run the pilot before making a go/no-go decision?
Define automatic or manual conditions that will terminate the pilot early.
Who receives regular updates, what data is reported, and how incidents are escalated.
A quick summary risk check that combines safety, data, and operational concerns.
1.0 10.0
Person who reviews this assessment for approval.
Approve, defer until mitigations are complete, or reject.
List outstanding actions, owners and deadlines if decision is defer/reject.
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