HAX Design Library

Interactive collection of the 18 Guidelines for Human-AI Interaction, with design patterns for applying them and examples.
Guideline 2 > Pattern 2A > Example

Amazon Prime Video | 2A: Match UI communication precision with system performance — Language

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Guideline 2 > Pattern 2A > Example

Apple Music | 2A: Match UI communication precision with system performance — Language

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Guideline 2 > Pattern 2A > Example

LinkedIn | 2A: Match UI communication precision with system performance — Language

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Guideline 2 > Pattern 2B > Example

Uber Eats | 2B: Match UI communication precision with system performance — Numbers

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Guideline 2 > Pattern 2B > Example

Zillow | 2B: Match UI communication precision with system performance — Numbers

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Guideline 2 > Pattern 2C > Example

Contoso | 2C: Report system performance information

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Guideline 2 > Pattern 2C > Example

SimCam | 2C: Report system performance information

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Guideline 2 > Pattern 2C > Example

Gender Shades | 2C: Report system performance information

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Guideline 2 > Pattern 2C > Example

Dragon Professional | 2C: Report system performance information

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Guideline 2 > Pattern 2C > Example

Kayak | 2C: Report system performance information

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Guideline 2 > Pattern 2D > Example

Business Chat | 2D: Provide low performance alerts

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Guideline 2 > Pattern 2D > Example

Copilot in Outlook | 2D: Provide low performance alerts

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Guideline 2 > Pattern 2D > Example

Word Online | 2D: Provide low performance alerts

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Guideline 2 > Pattern 2D > Example

Google Maps | 2D: Provide low performance alerts

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Guideline 2 > Pattern 2D > Example

Microsoft Teams | 2D: Provide low performance alerts

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Guideline 2 > Pattern 9A > Example

Viva Topics | 9A: Switch classification decisions and G2

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Guideline 2 > Example

Hugging Chat | G2: Make clear how well a system can do what it can do 

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Guideline 2 > Example

Copilot in Word | G2: Make clear how well the system can do what it can do

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Guideline 2 > Example

Copilot in PowerPoint | G2: Make clear how well the system can do what it can do

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Guideline 2 > Example

Google Search | G2: Make clear how well a system can do what it can do

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Guideline 2 > Example

Google Bard | G2: Make clear how well a system can do what it can do

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Guideline 2 > Example

Hugging Chat | G2: Make clear how well a system can do what it can do

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Guideline 2 > Example

Business Chat | G2: Make clear how well the system can do what it can do

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Guideline 2 > Example

Copilot in Outlook | G2: Make clear how well the system can do what it can do

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Guideline 7 > Example

Copilot in Word | G7: Support efficient invocation

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Guideline 7 > Example

Copilot in Outlook | G7: Support efficient invocation

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Guideline 7 > Example

Excel Flash Fill | G7: Support efficient invocation

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Guideline 7 > Example

PowerPoint | G7: Support efficient invocation

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Guideline 7 > Example

Amazon.com | G7: Support efficient invocation

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Guideline 8 > Example

Copilot in Outlook | G8: Support efficient dismissal

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Guideline 8 > Example

Copilot in Word | G8: Support efficient dismissal

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Guideline 8 > Example

Microsoft Forms | G8: Support efficient dismissal

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Guideline 8 > Example

Siri | G8: Support efficient dismissal

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Guideline 8 > Example

Instagram | G8: Support efficient dismissal

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Guideline 9 > Pattern 9A > Example

Viva Topics | 9A: Switch classification decisions

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Guideline 9 > Pattern 9A > Example

Google Photos | 9A: Switch classification decisions

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Guideline 9 > Pattern 9A > Example

Gmail | 9A: Switch classification decisions

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Guideline 9 > Pattern 9B > Example

Copilot in PowerPoint | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9B > Example

Notion | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9B > Example

Copilot in Outlook | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9B > Example

Copilot in Word | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9B > Example

D365 Customer Service | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9B > Example

Nichesss | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9B > Example

LinkedIn | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9B > Example

Google Maps | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9B > Example

Apple Photos | 9B: Rich and detailed edits

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Guideline 9 > Pattern 9C > Example

Bing Search | 9C: Undo automated actions

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Guideline 9 > Pattern 9D > Example

Instagram | 9D: Do G9 through G15

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Guideline 9 > Pattern 9D > Example

Google Photos | 9D: Do G9 through G15

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Guideline 9 > Pattern 9E > Example

Outlook | 9E: Batch-editing data

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Guideline 9 > Pattern 9E > Example

Google Photos | 9E: Batch-editing data

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Guideline 9 > Pattern 9E > Example

Gmail | 9E: Batch-editing data

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Guideline 9 > Example

Copilot in PowerPoint | G9: Support efficient correction

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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 > 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 > 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 > 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 > 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 > 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 > 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 > 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 > 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 > 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 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 > 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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