Launch Ethical Review for GPT Analysis

Project Context

OpenAI wants to standardize how AI/ML analysts incorporate ethical considerations into GPT-powered analysis workflows used in ChatGPT and internal decision support. Today, teams review fairness, privacy, and misuse risks inconsistently, which has already delayed two launches and created rework for Legal and Policy. You are the program manager for a 12-person cross-functional team and have been asked to launch a lightweight ethical review process in 10 weeks.

Key Stakeholders

The Head of Applied AI wants a fast rollout that does not slow experimentation. Legal and Policy want a documented review gate before any analysis is used in high-impact decisions. The Analytics Engineering manager wants minimal tooling changes because the team is already committed to a separate data platform migration. The Security lead insists that any workflow touching sensitive user data must meet existing access-control requirements.

Constraints

You have a budget of $120,000, no additional headcount, and a fixed deadline aligned to the next quarterly planning cycle. The team includes 4 analysts, 3 data engineers, 2 product managers, 1 policy specialist, 1 legal counsel, and 1 security engineer. The workflow must integrate with existing internal tooling and with OpenAI API-based analysis templates already used by 8 product teams. At least 3 pilot teams must adopt the process before general rollout.

Complications

1. One pilot team argues the review checklist will add 5 business days to every analysis request and is threatening to opt out.
2. Legal has not agreed on the threshold for what counts as a “high-impact” use case.
3. A recent audit found incomplete documentation for data retention decisions in two adjacent workflows.

Deliverables

1. Create a 10-week execution plan with milestones, owners, and dependencies.
2. Define the minimum viable ethical review process for pilot launch, including what is in scope vs. deferred.
3. Propose how you will resolve stakeholder disagreement on review thresholds without missing the deadline.
4. Identify the top risks to launch and specify mitigation and rollback criteria.
5. Define launch success metrics for adoption, review quality, and delivery speed.