My first instinct was to jump straight to technical solutions like ID verification or credit card checks, but that ignores like 90% of the actual problem space.
Start by framing the problem around TikTok's dual goals: protecting minors and maintaining a frictionless signup experience for legitimate users. Then propose a layered, risk-based approach that combines age estimation, behavioral signals, and verification triggers, while acknowledging trade-offs and privacy considerations.
Pro tip: Emphasize that no single method is foolproof; instead, focus on raising the cost of lying and detecting suspicious behavior post-signup. Mention that TikTok already uses age estimation technology and that PMs should partner with Trust & Safety, Legal, and ML teams to iterate on solutions.
Define success metrics (e.g., reduce underage accounts, minimize false positives) and constraints (privacy regulations, user friction, technical feasibility).
List available signals: self-reported age, device data, behavioral patterns, content interactions, and third-party age verification services.
Propose a combination of preventive measures (e.g., age estimation at signup, parental consent flows) and detective measures (e.g., behavioral analysis, periodic re-verification).
Use a risk-based approach to prioritize high-impact, low-friction interventions; suggest A/B tests to measure effectiveness and user impact.
Define metrics to monitor performance, gather feedback, and continuously improve the system as evasion tactics evolve.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.