Design a Feature to Combat Misinformation on a Social Platform

Product Strategy
Hard
Meta
51.7K views

Design a mechanism or feature for Instagram/Facebook to effectively combat health-related misinformation without overly restricting free speech.

Why Interviewers Ask This

Interviewers at Meta ask this to evaluate your ability to balance complex ethical constraints with scalable product solutions. They specifically test your understanding of free speech principles, your capacity to design for trust and safety without stifling user expression, and your strategic thinking in prioritizing high-impact health interventions over broad censorship.

How to Answer This Question

1. Clarify the scope: Define 'health misinformation' (e.g., unverified medical claims vs. opinion) and identify the target audience (users, creators, or both). 2. Acknowledge constraints: Explicitly state the tension between safety and free speech, proposing a 'nudge' strategy rather than removal where possible. 3. Propose a multi-layered solution: Suggest a combination of pre-bunking (educational prompts), post-bunking (context labels), and algorithmic down-ranking for low-quality sources. 4. Define success metrics: Select specific KPIs like click-through rates on context cards, reduction in shares of flagged content, and user sentiment analysis. 5. Discuss trade-offs: Explain how you would A/B test these features to ensure they do not negatively impact overall platform engagement or create bias against legitimate minority viewpoints.

Key Points to Cover

  • Prioritizing contextual information and education over outright content removal to protect free speech
  • Defining clear boundaries for what constitutes 'misinformation' versus 'opinion' or 'anecdote'
  • Implementing a tiered response system that scales from user nudges to persistent labels based on severity
  • Selecting measurable success metrics focused on behavior change (reduced sharing) rather than just flag counts
  • Demonstrating awareness of Meta's specific values regarding open platforms and community-driven moderation

Sample Answer

To combat health misinformation while respecting free speech, I propose a 'Context-Aware Nudge System' integrated into the Instagram and Facebook feed algorithms. First, we must define the scope: focus on content making definitive medical claims lacking peer-reviewed citations, rather than personal anecdotes. The core feature involves a two-stage intervention. Stage one is proactive: when a user attempts to share content flagged by our internal fact-checking partners or third-party health organizations as potentially misleading, a non-intrusive modal appears. Instead of blocking the share, it offers a 'Learn More' button linking to a neutral summary from authoritative sources like the WHO or CDC, framing it as 'Here's what experts say about this claim.' Stage two is reactive: if the content is widely shared but disputed, we attach a permanent, visible label below the post stating 'Disputed Claims' with a link to the evidence, without removing the original post. This preserves the creator's voice while providing critical context to viewers. We would measure success by tracking the reduction in shares of flagged content after seeing the nudge and monitoring engagement rates on the educational links. Crucially, we must A/B test these flows to ensure we aren't inadvertently suppressing legitimate health discussions or creating perception of bias, ensuring our approach aligns with Meta's commitment to open communication alongside community safety.

Common Mistakes to Avoid

  • Suggesting immediate deletion of all flagged content, which ignores the free speech constraint central to the prompt
  • Focusing solely on technical detection algorithms without considering the user experience or behavioral psychology aspects
  • Failing to define specific metrics for success, leading to a vague solution that cannot be validated
  • Overlooking the risk of bias in labeling systems and not proposing a mechanism to audit or mitigate it

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