Current theory work
Networked Accountability
Accountability is not only a role or a policy. It is an emergent property of the network through which evidence, uncertainty, dissent, and authority move.
The question
What makes a concern visible, credible, and actionable inside an AI program—and what causes it to be filtered out before it reaches a decision?
What the work examines
- How review-network structure shapes risk visibility, ownership, and action.
- How expertise, status, and relationships affect whose uncertainty is believed.
- How dissent survives handoffs, becomes diluted, or reaches an escalation path.
- Which mechanisms turn unresolved concern into accountable organizational action.
Current direction
I am developing a mechanism-based theory and empirical agenda spanning qualitative fieldwork, network analysis, and agent-based simulation. The aim is to explain—not merely describe—why apparently similar governance systems produce different outcomes.