Responsible AI is not a final review step. It shapes the problem definition, data choices, evaluation, interface, monitoring, and decisions about whether a system should exist at all.
- 01
Map people and harms
Identify who benefits, who carries risk, who is missing from the data, and how failure could affect different groups.
- 02
Measure beyond accuracy
Evaluate subgroup performance, calibration, robustness, privacy, security, accessibility, and the cost of false confidence.
- 03
Design human control
Make uncertainty visible, support review and appeal, preserve meaningful choice, and avoid interfaces that overstate capability.
- 04
Govern the lifecycle
Document decisions, control access, monitor real-world impact, investigate incidents, and define clear ownership for change.