HAX Design Library

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

Guideline 2

Guideline 2

Make clear how well the system can do what it can do

Help the user understand how often the AI system may make mistakes.
Guideline 2 > Pattern 2A

Pattern 2A: Match the level of precision in UI communication with the system performance – Language
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

Pattern 2B: Match the level of precision in UI communication with the system performance – Numbers
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

Pattern 2C: Report system performance information
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

Pattern 2D: Provide low performance alerts
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 6

Guideline 6

Mitigate social biases

Ensure the AI system’s language and behaviors do not reinforce undesirable and unfair stereotypes and biases.
Guideline 6 > Example

Bing Search | G6: Mitigate social biases

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Guideline 6 > Example

Siri | G6: Mitigate social biases

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Guideline 6 > Example

MyAnalytics | G6: Mitigate social biases

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Guideline 6 > Example

Android | G6: Mitigate social biases

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Guideline 6 > Example

Bing Search | G6: Mitigate social biases

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Guideline 7

Guideline 7

Support efficient invocation

Make it easy to invoke or request the AI system’s services when needed.
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

Guideline 8

Support efficient dismissal

Make it easy to dismiss or ignore undesired AI system services.
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

Guideline 9

Support efficient correction

Make it easy to edit, refine, or recover when the AI system is wrong.
Guideline 9 > Pattern 9A

Pattern 9A: Switch classification decisions
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

Pattern 9B: Rich and detailed edits
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

Pattern 9C: Undo automated actions
Guideline 9 > Pattern 9C > Example

Bing Search | 9C: Undo automated actions

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Guideline 9 > Pattern 9D

Pattern 9D: Do G9 through G15
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

Pattern 9E: Batch-editing data
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

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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