HAX Design Library

Interactive collection of the 18 Guidelines for Human-AI Interaction, with design patterns for applying them and examples.

Guideline 3

Guideline 3

Time services based on context

Time when to act or interrupt based on the user’s current task and environment.

Guideline 10

Guideline 10

Scope services when in doubt

Engage in disambiguation or gracefully degrade the AI system’s services when uncertain about a user’s goals.
Guideline 10 > Pattern 10A

Pattern 10A: Disambiguate before acting
Guideline 10 > Pattern 10A > Example

Copilot in Word | 10A: Disambiguate before acting

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Guideline 10 > Pattern 10A > Example

Github Copilot | 10A: Disambiguate before acting

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Guideline 10 > Pattern 10A > Example

iPhone | 10A: Disambiguate before acting

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Guideline 10 > Pattern 10A > Example

Google Search | 10A: Disambiguate before acting

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Guideline 10 > Pattern 10B

Pattern 10B: Avoid cold starts by eliciting user preferences
Guideline 10 > Pattern 10B > Example

Apple Music | 10B: Avoid cold starts by eliciting user preferences

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Guideline 10 > Pattern 10B > Example

Microsoft News | 10B: Avoid cold starts by eliciting user preferences

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Guideline 10 > Pattern 10C

Pattern 10C: Fall back to other strategies
Guideline 10 > Pattern 10C > Example

Box Skills | 10C: Fall back to other strategies

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Guideline 10 > Pattern 10C > Example

Kommunicate chatbot | 10C: Fall back to other strategies

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Guideline 10 > Example

Copilot in PowerPoint | G10: Scope services when in doubt

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Guideline 11

Guideline 11

Make clear why the system did what it did

Enable the user to access an explanation of why the AI system behaved as it did.
Guideline 11 > Pattern 11A

Pattern 11A: Local explanations
Guideline 11 > Pattern 11A > Example

AlphaCode | 11A: Local explanations

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Guideline 11 > Pattern 11A > Example

Google Search | 11A: Local explanations

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Guideline 11 > Pattern 11A > Example

Copilot in Excel | 11A: Local explanations

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Guideline 11 > Pattern 11A > Example

Business Chat | 11A: Local explanations

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Guideline 11 > Pattern 11A > Example

InterpretML | 11A: Local explanations

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Guideline 11 > Pattern 11A > Example

Pinterest | 11A: Local explanations

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Guideline 11 > Pattern 11B

Pattern 11B: Global explanations
Guideline 11 > Pattern 11B > Example

D365 Marketing | 11B: Global explanations

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Guideline 11 > Pattern 11B > Example

InterpretML | 11B: Global explanations

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Guideline 11 > Pattern 11B > Example

Instagram | 11B: Global explanations

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Guideline 11 > Pattern 11C

Pattern 11C: Present properties of system outputs
Guideline 11 > Pattern 11C > Example

Google Maps | 11C: Present properties of system outputs

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Guideline 11 > Pattern 11C > Example

Strava | 11C: Present properties of system outputs

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Guideline 11 > Pattern 11D

Pattern 11D: Map system input attributes to system outputs
Guideline 11 > Pattern 11D > Example

AlphaCode | 11D: Map system input attributes to system outputs

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Guideline 11 > Pattern 11D > Example

Gmail | 11D: Map system input attributes to system outputs

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Guideline 11 > Pattern 11D > Example

Sentiment Analysis | 11D: Map system input attributes to system outputs

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Guideline 11 > Pattern 11E

Pattern 11E: Map user behaviors to system outputs
Guideline 11 > Pattern 11E > Example

Netflix | 11E: Map user behaviors to system outputs

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Guideline 11 > Pattern 11E > Example

Goodreads | 11E: Map user behaviors to system outputs

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Guideline 11 > Pattern 11F

Pattern 11F: Example-based explanations
Guideline 11 > Pattern 11F > Example

Image recognition | 11F: Example-based explanations

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Guideline 11 > Pattern 11F > Example

Computer Vision | 11F: Example-based explanations

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Guideline 11 > Pattern 11G

Pattern 11G: “What if?” explanations
Guideline 11 > Pattern 11G > Example

Copysmith | 11G: “What if explanations”

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Guideline 11 > Pattern 11G > Example

Jasper.ai | 11G: “What if?” explanations

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Guideline 11 > Pattern 11G > Example

NerdWallet | 11G: “What if?” explanations

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Guideline 11 > Pattern 11G > Example

Grammarly | 11G: “What if?” explanations

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Guideline 13

Guideline 13

Learn from user behavior

Personalize the user’s experience by learning from their actions over time.

Guideline 14

Guideline 14

Update and adapt cautiously

Limit disruptive changes when updating and adapting the AI system’s behaviors.
Guideline 14 > Pattern 14A

Pattern 14A: Comprehensive updates
Guideline 14 > Pattern 14A > Example

YouTube | 14A: Comprehensive updates

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Guideline 14 > Pattern 14A > Example

Facebook | 14A: Comprehensive updates

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Guideline 14 > Pattern 14B

Pattern 14B: Immediate, partial, non-disruptive updates
Guideline 14 > Pattern 14B > Example

Google Search | 14B: Immediate, partial, non-disruptive updates

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Guideline 14 > Pattern 14B > Example

Spotify | 14B: Immediate, partial, non-disruptive updates

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