AI governance principles and the laws that regulate AI products

In a product manager interview at LinkedIn, you are asked what you know about responsible AI principles and the regulations that currently govern the use of AI. ```hint Separate commitments from obligations Principles are commitments a company chooses; laws attach duties to particular uses and places. Think about which of LinkedIn's uses of AI a regulator would consider high stakes, and why. ``` ### Clarifying Questions - Should the answer focus on the jurisdictions where most LinkedIn members and customers are, such as the EU and the US, or cover the global picture? - Do you want the principles in general, or how they apply to LinkedIn's uses of AI, such as feed and job recommendations, recruiter tools and generative writing help? - Should voluntary frameworks and standards be included alongside binding law? ### What a Strong Answer Covers - The widely shared principles and what each one means in practice - How principles become working processes: impact assessments, testing, documentation, human oversight, monitoring and accountability - The main binding regimes, including risk-based AI law and existing data protection, consumer protection and anti-discrimination law - Which product uses carry the heaviest obligations, and why hiring-related features stand out - Awareness that the rules are changing, and how a PM keeps a product compliant across jurisdictions ### Follow-up Questions - A feature that ranks applicants for recruiters is launching in the EU and in New York City. What obligations would you plan for? - Where would responsible AI principles ask more of you than the law does, and how would you justify that cost? - How would you set up reviews so that new AI features are checked without slowing every launch?