The Arclight: AI Governance and Self-Correcting Decision Systems for an Uncertain World

How can decisions remain stable in a world where uncertainty cannot be eliminated?

Some parts of this work have been published on SSRN.

As artificial intelligence becomes embedded in economic systems, governance, and infrastructure, decision-making is no longer purely human.

The Arclight Framework explores the structural conditions under which decisions succeed or fail.

Rather than offering prescriptions, it examines how judgment is shaped before choices are made — through constraints, feedback, and system design.

The framework focuses on:

• the limits of prediction

• feedback loops between humans and AI

• self-correcting mechanisms in decision systems

• the role of uncertainty in shaping outcomes

Positioned at the intersection of AI governance, complex systems, and decision theory, this work approaches decision-making as an evolving structure rather than a fixed process.

This book is intended for readers interested in how decisions are formed, destabilized, and potentially stabilized in environments where uncertainty is permanent.