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 2B

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

Dragon Professional | 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

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

Google Gemini | G2: Make clear how well the system can do what it can do

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Guideline 2 > Example

Google Gemini | G2: Make clear how well the system can do what it can do

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Guideline 2 > Example

AI-framed questioning | G2: Make clear how well the system can do what it can do

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Guideline 2 > Example

Visual uncertainty highlighting | G2: Make clear how well the system can do what it can do

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Guideline 2 > Example

AI Critiques | G2: Make clear how well the 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

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 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 5

Guideline 5

Match relevant social norms

Ensure the experience is delivered in a way that users would expect, given their social and cultural context.
Guideline 5 > Example

Copilot in PowerPoint | G5: Match relevant social norms

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Guideline 5 > Example

Microsoft Word | G5: Match relevant social norms

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Guideline 5 > Example

Google Photos | G5: Match relevant social norms

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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 14B

Pattern 14B: Immediate, partial, non-disruptive updates

Guideline 15

Guideline 15

Encourage granular feedback

Enable the user to provide feedback indicating their preferences during regular interaction with the AI system.
Guideline 15 > Pattern 15A

Pattern 15A: Encourage explicit feedback on individual system outputs
Guideline 15 > Pattern 15A > Example

Copilot in Excel | 15A: Encourage explicit feedback on individual system outputs

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Guideline 15 > Pattern 15A > Example

Viva Topics | 15A: Encourage explicit feedback on individual system outputs

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Guideline 15 > Pattern 15B

Pattern 15B: Request explicit feedback on selected system outputs
Guideline 15 > Pattern 15C

Pattern 15C: Reporting inappropriate content
Guideline 15 > Pattern 15C > Example

Word Online | 15C: Reporting inappropriate content

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Guideline 15 > Pattern 15D

Pattern 15D: Use existing public rating or interaction data as feedback for the system
Guideline 15 > Pattern 15D > Example

Contoso | 15D: Use existing public rating or interaction data as feedback for the system

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