Product design question
How would you improve trust in the Bing search results for healthcare?
- Microsoft
- Product design
- Hard
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What this question tests
Product thinking on trust and misinformation risk in a high-stakes search vertical.
How to approach it
- Clarify the goal, reducing exposure to low-quality or misleading medical information versus improving perceived credibility.
- Identify the core risk, health misinformation and unverified sources appearing high in search results.
- Propose ranking changes, boost content from licensed medical institutions and peer reviewed sources for health queries.
- Add UI level trust signals, source labels, publish dates, and citations to recognized medical bodies directly in the results.
- Consider a dedicated health panel for common symptom and condition queries, similar to a knowledge panel sourced from vetted content.
- Define success metrics, click-through rate to verified sources and a user-reported trust survey score for health queries.
What a strong answer includes
- Separates ranking changes, which fix what shows up, from UI trust signals, which fix how users perceive it, as two distinct levers.
- Proposes a concrete mechanism, partnering with recognized medical bodies for a verified content boost, not just 'improve the algorithm'.
- Flags the tension between reducing misinformation and not appearing to give medical advice, a real constraint for a search engine.
- Sets a measurable proxy, e.g. percent of health query clicks landing on a vetted source, marked as an assumption.
Common mistakes
- Proposing vague 'better algorithm' fixes with no concrete mechanism.
- Ignoring the legal and liability sensitivity of health content.
- Not defining any way to actually measure trust improvement.
Likely follow-up questions
- How would you define a 'trusted' source objectively.
- How would you handle borderline cases like alternative medicine content.
- How would you measure whether trust actually improved.
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop