Went with a top-down approach: US road miles, average pothole density per mile by road type, weighted by urban vs rural split.
Break the problem into a demand-based model: estimate the total road miles in the continental US, then estimate the proportion of those miles that are paved and in poor condition, and finally estimate the density of potholes per mile of poor road. Use round numbers and state assumptions clearly, then sanity-check the final estimate against known data points.
Pro tip: Don't just give a number—show how you'd validate it. Mention that you'd cross-check your estimate with public data (e.g., FHWA road condition reports) and adjust your assumptions if the result seems off by an order of magnitude.
Define what counts as a pothole (e.g., a depression of a certain size) and confirm that we're estimating for all roads in the continental US, including local, state, and interstate highways.
Use population and area to estimate total road miles. For example, assume 4 million miles of public roads in the US (based on FHWA data), with about 80% in the continental US, giving ~3.2 million miles.
Assume that only roads in poor condition have potholes. According to FHWA, about 20% of roads are in poor condition, so ~640,000 miles of road have potholes.
Assume that on a mile of poor road, there might be 10 potholes (a rough average, considering some stretches have none and others have many). This gives 640,000 miles * 10 potholes/mile = 6.4 million potholes.
Compare with known data: if the estimate seems too low or high, adjust assumptions. For example, if pothole density is higher (e.g., 50 per mile), the total would be 32 million. State that the final answer is an order-of-magnitude estimate.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying Google's mission and core competencies, then evaluate whether fixing potholes aligns with them. Use a structured framework to assess strategic fit, feasibility, and potential impact, ultimately concluding that Google should not take on this responsibility directly but could enable solutions through technology and partnerships.
Pro tip: Acknowledge the broader context of civic responsibility and Google's role as a technology enabler, not a service provider. Emphasize that Google's strength lies in scalable, information-based solutions, not physical infrastructure maintenance.
Define what 'fixing all potholes' entails—scope, scale, and stakeholders. Consider if it means direct repair, funding, or enabling others.
Evaluate alignment with Google's mission (organize information), core competencies (AI, mapping, data), and business model. Determine if this is a problem Google is uniquely positioned to solve.
Analyze technical, operational, and financial feasibility. Consider potential impact on users, communities, and Google's brand. Compare with alternative solutions.
Explore how Google could enable solutions without direct responsibility—e.g., providing data to cities, partnering with governments, or developing reporting tools.
Conclude whether Google should take on this responsibility, and if not, what role it could play. Support with reasoning and potential next steps.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.