What question did this study set out to answer?

This paper aims to develop a closed-loop decision architecture that aligns institutional purpose with operational decisions in AI environments.

June 14, 2026Open Access

AI-Augmented Impact Frames: A Closed-Loop Architecture for Purpose-Aligned Decisions

Key Points

This paper aims to develop a closed-loop decision architecture that aligns institutional purpose with operational decisions in AI environments.
Introduces the concept of impact frames as linkages between intent, evaluation criteria, and feedback signals
Describes how AI systems can reshape interpretive structures
Presents a design-oriented perspective on governance architectures
Demonstrates how AI can stabilize and transform decision-making frameworks under complexity
Highlights the role of structured representations in aligning purpose and operational decisions

Abstract

This paper introduces a closed-loop decision architecture for aligning institutional purpose with operational decisions in AI-mediated environments. It presents the concept of impact frames as structured representations linking intent, evaluation criteria, and feedback signals. The paper shows how AI systems can both stabilise and transform interpretive structures, affecting how meaning is encoded and acted upon. It contributes a design-oriented perspective on governance architectures capable of maintaining alignment under conditions of complexity and technological mediation. This paper is part of the Coherence Programme. Further materials and companion papers are available at: https://thecoherenceprogramme.org/

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