HAX Design Library

Guideline 13

Learn from user behavior

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

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

Encourage granular feedback

Enable the user to provide feedback indicating their preferences during regular interaction with the AI system.

Guideline 15 > Pattern 15A

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

Guideline 15 > Pattern G15-A > Example

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

Guideline 15 > Pattern G15-D > Example

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

Guideline 16

Convey the consequences of user actions

Immediately update or convey how user actions will impact future behaviors of the AI system.

Guideline 16 > Pattern 16A

Pattern 16A: Feedforward: Convey the consequences of user actions before the user takes action

Guideline 16 > Pattern 16B

Pattern 16B: Feedback: Convey the consequences of user actions after the user takes action

Guideline 16 > Pattern 16C

Pattern 16C: Remind of consequences of a past action and ask for reconfirmation

Guideline 16 > Pattern 16D

Pattern 16D: Convey the consequences of user action in help and documentation

Guideline 17

Provide global controls

Allow the user to globally customize what the AI system monitors and how it behaves.

Guideline 17 > Example

Windows Copilot | G17: Provide global controls