The Facebook Live team is debating: should we implement AI content moderation that might flag false positives or rely on user reports?

Introduction

The Facebook Live team is facing a critical decision: implement AI content moderation with potential false positives or rely on user reports for content moderation. This trade-off involves balancing the need for real-time content moderation with the risk of erroneously flagging legitimate content. I'll analyze this scenario using a structured approach, considering various stakeholders, metrics, and potential outcomes.

Step 1

Clarifying Questions (3 minutes)

• Context: I'm thinking about the current state of content moderation on Facebook Live. Could you provide more information on the existing moderation process and its effectiveness?

Why it matters: Helps understand the baseline and areas for improvement Expected answer: Current system relies heavily on user reports, with some delay in addressing issues Impact on approach: Would influence the urgency of implementing AI moderation

• Business Context: Based on recent trends, I assume live video is a growing priority for Facebook. How does improving Live content moderation align with our overall business strategy?

Why it matters: Ensures the solution supports broader company goals Expected answer: Critical for user trust and advertiser confidence Impact on approach: Would justify significant resource allocation

• User Impact: I'm considering the different user segments affected. Can you share data on the types of users most impacted by inappropriate content on Live?

Why it matters: Helps tailor the solution to protect vulnerable users Expected answer: Younger users and certain geographic regions more affected Impact on approach: Would focus on specific user segments for initial rollout

• Technical Feasibility: Considering the real-time nature of Live, I'm curious about our AI capabilities. What's our current accuracy rate for AI content moderation in video?

Why it matters: Determines if AI is ready for real-time implementation Expected answer: 85-90% accuracy, with ongoing improvements Impact on approach: Would influence the balance between AI and user reports

• Resource Allocation: I'm thinking about the team needed for this project. What resources do we have available for developing and maintaining an AI moderation system?

Why it matters: Ensures we can support the chosen solution long-term Expected answer: Dedicated AI team available, but limited content review staff Impact on approach: Would lean towards automated solutions with human oversight