Toward Testing AI: A Socio-Economic View (Technical Report)

May 28, 2026Open Access

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Key Points

This report aims to develop a methodology for analyzing interactions between AI agents and humans from socio-economic perspectives.
Utilizes formal mechanism design to model interactions as a dynamic human-in-the-loop mechanism.
Employs social mechanism theory to evaluate mechanisms' collective properties.
Proposes a Star-Durkheim-inspired test for assessing AI systems' social usefulness.
The proposed test emphasizes collective cohesion and the potential dissolution of social structures over basic capabilities.
Evaluation of AI systems shows a significant focus on social mechanisms rather than mere intelligence.
Integrating economic and sociological perspectives provides a foundation for effective regulation of AI systems.

Technical report presents a framework for testing AI systems' usefulness in social contexts, indicating regulatory implications.

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Draheim et al. (2026) studied this question.

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