Accountability
Name the people who can approve, limit, pause, and retire a system, and ensure they have enough information to act.
Topic guide
Good AI governance gives the right people enough visibility, authority, and evidence to make responsible decisions — even while the technology and the regulation are both moving under their feet. It connects boardroom accountability to the messy details of data, models, agents, suppliers, and real-world consequences.
Many failures attributed to AI are actually failures of ownership, incentives, escalation, procurement, or plain operational discipline. The model is usually the last thing that needs fixing. Governance becomes useful when it makes those surrounding conditions explicit and ties them to technical evidence.
Name the people who can approve, limit, pause, and retire a system, and ensure they have enough information to act.
Translate broad values into acceptable uses, prohibited outcomes, exposure limits, and escalation thresholds.
Define the tests, monitoring, incident evidence, and independent challenge needed before and after deployment.
Include affected people, explain consequential choices, and provide routes for correction and redress.
Questions for a board