I jumped straight into crowdsourcing and local guides without really thinking through who actually suffers most from missing map data.
Start by clarifying the problem scope—what 'unmapped' means, which regions are affected, and why it matters to Google's mission. Then propose a scalable, multi-pronged solution leveraging user contributions, AI/ML, and partnerships, and prioritize based on impact and feasibility. Finally, outline success metrics and potential risks.
Pro tip: Emphasize that the solution must be sustainable and scalable, not just a one-time fix, and tie it back to Google's core mission of organizing the world's information.
Ask questions to understand the scope: which regions are unmapped, what data is missing (roads, businesses, etc.), and why it matters to users and Google.
Consider who needs this data (local users, businesses, humanitarian orgs) and what their pain points are to ensure the solution delivers value.
Generate ideas across different approaches: crowdsourcing, AI/ML from satellite imagery, partnerships with local governments/NGOs, and incentivizing contributions.
Evaluate ideas on impact vs. effort, and propose a phased approach starting with a minimum viable product in a pilot region.
Outline how to measure success (coverage, accuracy, user engagement) and potential challenges (data quality, privacy, scalability).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.