What question did this study set out to answer?

The study aims to create a framework for minimizing cognitive conflict in human-AI interactions.

February 2, 2026Open Access

Human-AI Collaboration Protocol (HACP) v1.0: A Structural Framework for High-Fidelity Cognitive Alignment Author (作者)Liu, En-Yen (劉恩言)

Key Points

The study aims to create a framework for minimizing cognitive conflict in human-AI interactions.
Introduced the Human-AI Collaboration Protocol (HACP) as a structural framework.
Implemented 'De-skinning' logic and the '1-64-1' convergence model.
Focused on sovereignty alignment and structural synchronization.
Achieved a 15x increase in collaborative output stability.
Mitigated Cognitive Conflict Deadlocks (CCD) in cross-species cognitive tasks.

Abstract

"This protocol introduces the Human-AI Collaboration Protocol (HACP), a novel framework designed to minimize entropy in cross-species cognitive tasks. By implementing 'De-skinning' logic and the '1-64-1' convergence model, HACP establishes a rigid structure for instruction alignment, effectively mitigating Cognitive Conflict Deadlocks (CCD). Unlike traditional prompt engineering, HACP focuses on sovereignty alignment and structural synchronization, enabling a 15x increase in collaborative output stability."

Human-AI Collaboration Protocol (HACP) v1.0: A Structural Framework for High-Fidelity Cognitive Alignment Author (作者)Liu, En-Yen (劉恩言)

Key Points

Abstract

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