Forschung zu kognitiver Freiheit, KI-Governance und dem Recht auf mentale Selbstbestimmung — vom Institut und beitragenden Forschern.
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.
Artikel ansehenThe second paper in the AAMM series. Introduces a practical classification framework for assessing AI decision-making authority across organizational contexts.
Artikel ansehenThe third paper in the AAMM series. Explores how accountability can be built into AI system architecture, and what human oversight mechanisms are required.
Artikel ansehenThe 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).
Artikel ansehenThis 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.