Human-AI Collaboration: Coherence, Responsibility, and Jean-Pol Martin's Framework for Optimal Partnership
By
Martin, Jean-Pol, ChatGPT
A second-rack bagel that's nearly first-rack. Tasty stuff.
Summary
This working paper examines the human conditions required for productive collaboration with artificial intelligence. It argues that AI does not support humans equally in all situations, and that the quality of AI assistance depends on the clarity, coherence, and constructive orientation of the human user. Based on Jean-Pol Martin's New Human Rights framework and the Martin Master Prompt, the article proposes that humans work best with AI when they explicitly define their goals, values, contexts, needs, and contradictions. The six basic needs—thinking, health, security, social belonging, self-realization/participation, and meaning—provide a practical framework for guiding AI use. AI should be treated as a reflection partner rather than an oracle, helping humans structure thought, identify contradictions, and plan coherent action. The central thesis is that the more coherent, constructive, and responsible the human is, the more effectively AI can serve as a tool for reflection, orientation, and human development.
Key quotes
· 4 pulledThe quality of AI assistance depends strongly on the clarity, coherence, and constructive orientation of the human user.
AI should not be treated as an oracle, but as a reflection partner that can help humans structure thought, identify contradictions, and plan more coherent action.
The more coherent, constructive, and responsible the human being is, the more effectively AI can act as a tool for reflection, orientation, and human development.
The six basic needs — thinking, health, security, social belonging, self-realization/participation, and meaning — provide a practical framework for guiding AI use.
This working paper examines the human conditions required for productive collaboration with artificial intelligence. It argues that AI does not support humans equally in all situations. The quality of AI assistance depends strongly on the clarity, cohe
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