AI Accountability Includes Who Benefits

A recent RegulatingAI Podcast conversation with Professor Sandra Wachter asks who benefits from AI—and who should be accountable when it causes harm. The episode, published October 28, 2026, also discusses public contributions to AI infrastructure and responsibility when autonomous agents cause harm. (regulatingai.org)

My work-focused takeaway: accountability should cover both the costs of failure and the outcomes an organization says it is pursuing. Before scaling an AI initiative, make those intended outcomes concrete, name who is responsible for reviewing them, and agree what evidence would prompt a change of course. That’s a governance proposal, not a claim that the episode prescribes a particular process.

When AI work depends on public resources or affects the public, who should help define what counts as a meaningful benefit—and how should that commitment be reviewed?