Recherche sur la liberté cognitive, la gouvernance de l'IA et le droit à l'autodétermination mentale — par l'Institut et des chercheurs contributeurs.
The first paper in the AAMM series. Examines how AI systems are transitioning from advisory tools to organizational authorities, and the governance failures this creates.
Voir l'articleThe second paper in the AAMM series. Introduces a practical classification framework for assessing AI decision-making authority across organizational contexts.
Voir l'articleThe third paper in the AAMM series. Explores how accountability can be built into AI system architecture, and what human oversight mechanisms are required.
Voir l'articleThe fourth and final paper in the AAMM series. Addresses the collective action problem in AI governance and introduces the AI Governance Border Adjustment Mechanism (GBAM).
Voir l'articleThis paper develops a unified framework describing the transition from the attention economy to the intelligence economy. It proposes that human cognitive contributions to AI systems constitute a productive resource requiring governance and benefit-sharing, formalised through a mathematically grounded model of intelligence production, an ecological niche factor derived from Himalayan field observations, and a governance architecture drawn from Ostromian commons theory and the Nagoya Protocol on Access and Benefit-Sharing.