Creating example-based explanations

Example-based explanations show users similar cases to help them understand AI decisions. Instead of explaining how the AI works, they show examples that make the logic clear. These explanations work because humans are naturally good at spotting patterns and making comparisons.

Real estate apps demonstrate this approach perfectly. When estimating a home's value at $1M, the app displays actual comparable homes nearby. Users see a 5-bedroom house at 1115 Berkeley Ave that sold for $1,180,000 and a 3-bedroom at 1216 Windermere that sold for $1,650,007. This makes the valuation understandable without any technical explanation.

The power comes from selection. Showing random similar homes won't help. The examples need to highlight what drives the price difference. Is it the number of bedrooms? The square footage? The neighborhood? Good examples make these factors obvious through comparison.

Users trust what they can verify themselves. Seeing real sold prices from actual addresses feels more convincing than any algorithm explanation.