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Building an AI Review Process

This lesson guides PMs through creating an AI review process, emphasizing the importance of stakeholder involvement, risk assessment, documentation, and ongoing monitoring. With examples from Google and Facebook, it highlights the real-world application and potential pitfalls of AI governance.

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Introduction

Alright, PMs, it's time to roll up those sleeves and dive into the nitty-gritty of designing an AI review process. This isn't just a checklist for compliance, but a roadmap to building AI products that won't end up in headlines for the wrong reasons. We'll pull back the curtain on how the big leagues—like Google and Facebook—tackle this and why you should care.

Why You Need an AI Review Process

Let's start with the 'why'. Imagine your AI product is a self-driving car. Without a review process, you're basically driving blindfolded. An AI review process acts as your GPS, keeping you on the ethical road and avoiding those legal potholes.

Why this matters for PMs: You're the captain of the ship. If it sinks, you can't just point fingers. A solid AI review process protects your product, your team, and yes, your career.

What comes next

Key Components of an AI Review Process

1. Stakeholder Involvement

Gather your crew: Involve developers, legal advisors, ethicists, and yes, even marketing folks. You need diverse perspectives to foresee potential issues.

2. Risk Assessment Framework

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Finish: Building an AI Review Process

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