User Needs + Defining Success
Even the best AI will fail if it doesn’t provide unique value to users.
Data Collection + Evaluation
Decide what data are required to meet your user needs, source data, and tune your AI.
Mental Models
Introduce users to the AI system and set expectations for system-change over time.
Explainability + Trust
Explain the AI system and determine if, when, and how to show model confidence.
Feedback + Control
Design feedback and control mechanisms to improve your AI and the user experience.
Errors + Graceful Failure
Identify and diagnose AI and context errors and communicate the way forward.
