Our six articles give in-depth guidance across the AI product development flow. Originally launched in 2019, they’ve been updated with new insights.

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.