Governments are codifying AI rules: risk tiers, documentation, bans on certain uses, and cross-border data rules. Regulation evolves—teams need process to track obligations, not one-time checkbox compliance.
Themes globally
- Risk-based frameworks (EU AI Act direction)
- Sector rules: healthcare (FDA), finance (model risk management), employment
- Consumer protection against deceptive AI claims
- Export controls on advanced chips and models (geopolitical)
Documentation regulators expect
- Risk assessment and mitigations
- Training data summary and known limitations
- Human oversight measures
- Incident reporting procedures
Practical stance
Map your use cases to risk tiers early. High-risk (hiring, credit, critical infrastructure) demands stronger governance than marketing subject lines.
Important interview questions and answers
- Q: Risk-based regulation?
A: Obligations scale with potential harm—not one rule for all AI. - Q: Model card for regulators?
A: Structured summary of purpose, data, metrics, and limitations.
Self-check
- Name two regulatory themes.
- Why tier use cases by risk?
Tip: Tier use cases by risk early; hiring and credit face stricter bars than marketing copy.
Interview prep
- Risk-based approach?
- Obligations scale with potential harm of the use case.
- High-risk examples?
- Hiring, credit, critical infrastructure—stronger governance required.