Overview

Diverse values and cultural perspectives from multiple stakeholders and populations should be codified in mathematical models and AI system design. Model design techniques are necessarily contextual, related to the type of AI technology, the purpose and scope of the system, how users will be impacted, and so forth. However, basic steps should include incorporating input from diverse stakeholder cohorts, ensuring the development team embodies different kinds of diversity to reflect the diversity of AI system end-users and stakeholders, establishing and reviewing metrics to capture diversity and inclusion elements throughout the AI lifecycle, and ensuring well-documented end-to-end transparency on final design choices.