A model you manage shows a measurable increase in engagement but also exhibits statistically significant performance differences across demographic groups. A product stakeholder wants to launch immediately to capture market opportunity. How would you approach this situation — what factors would you evaluate, what mitigations might you propose, and how would you involve stakeholders?

I would treat the engagement uplift and the fairness signal as jointly actionable. First I’d quantify both: for example, engagement +8% overall but conversion for Group B is 12 percentage points lower than Group A (p<0.01). I’d run a root-cause analysis — check data imbalance, label quality, features leaking proxy signals, and downstream impact like retention or revenue. I’d surface trade-offs to the PM and legal: short-term revenue vs. brand and regulatory risk. Mitigations could include a phased rollout (10% canary), fairness-aware reweighting or calibrated thresholds to reduce disparity by ~60% while accepting a temporary 1–2% engagement hit, or targeted improvements for the affected group. I’d own an actionable plan: 2–4 week mitigation sprint with engineers, a designer for UX safeguards, and legal, plus monitoring and rollback triggers (e.g., disparity >5 pp or engagement drop >3%).