PAIR AI Design Principles
Google's People + AI Research (PAIR) design principles for creating human-centered AI products that balance user autonomy, safety, and helpfulness while adapting to user feedback and real-world contexts.
-
User Autonomy
Design for the appropriate level of user autonomy in AI-supported workflows, considering different user tasks, expertise, and the effort required to steer the AI system.
-
Data & Model Alignment
Align datasets and models with people’s real-world interactions with AI systems, accounting for unexpected tasks and contexts that may emerge as the product scales.
-
Evolving Safety
Treat safety as an evolving endeavor with multifaceted strategies that adapt to changing technology, user contexts, and complexity over time.
-
Adapt with Feedback
Create bidirectional feedback loops where AI learns from users to personalize experiences, and users adapt their behaviors in response to AI outcomes.
-
Helpful AI
Create AI experiences that enhance aspects of work and play that people enjoy, focusing on seamless integration and inspiration rather than just efficiency gains.
Know of a set of design principles that should be here? Contribute an example