Research program
RAIDops
Trustworthy AI becomes operational when governance is designed into the work: roles, artifacts, evidence, review paths, and escalation—not added as a final checkpoint.
The question
How can ethics, assurance, human factors, and accountable review become normal parts of AI delivery without collapsing into paperwork or last-minute approval?
What the work examines
- Lifecycle patterns that connect responsible-AI intent to engineering practice.
- Decision rights, evidence ownership, stage gates, and escalation mechanisms.
- The organizational capabilities needed to make review repeatable and useful.
- Maturity signals that distinguish performative governance from operational assurance.
Current direction
The program currently organizes 24 recurring design patterns into a working catalog and maturity model. The next phase is to refine the manuscript and test how the patterns behave in real product and platform environments.