Microsoft’s Guidelines for Designing Human-AI Interactions
At the start
1. Make clear what the system can do.
Help the user understand what the AI system is capable of doing.
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.
During Interaction
3. Time services based on context.
Time when to act or interrupt based on the user’s current task and environment.
5. Match relevant social norms.
Ensure the experience is delivered in a way that users would expect, given their social and cultural context.
4. Show contextually relevant information.
Display information relevant to the user’s current task and environment.
6. Mitigate social biases.
Ensure the AI system’s language and behaviors do not reinforce undesirable and unfair stereotypes and biases.
When Wrong
7. Support efficient invocation.
Make it easy to invoke or request the AI system’s services when needed.
9. Support efficient correction.
Make it easy to edit, refine, or recover when the AI system is wrong.
8. Support efficient dismissal.
Make it easy to dismiss or ignore undesired AI system services.
10. Scope services when in doubt.
Engage in disambiguation or gracefully degrade the AI system’s services when uncertain about a user’s goals.
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.
Over Time
12. Remember recent interactions.
Maintain short-term memory and allow the user to make efficient references to that memory.
15. Encourage granular feedback.
Enable the user to provide feedback indicating their preferences during regular interaction with the AI system.
18. Notify users about changes.
Inform the user when the AI system adds or updates its capabilities.
13. Learn from user behavior.
Personalize the user’s experience by learning from their actions over time.
16. Convey the consequences of user actions.
Immediately update or convey how user actions will impact future behaviors of the AI system.
14. Update and adapt cautiously.
Limit disruptive changes when updating and adapting the AI system’s behaviors.
17. Provide global controls.
Allow the user to globally customize what the AI system monitors and how it behaves.