#agency2 articles

2 articles

AINeutralarXiv – CS AI · Feb 277/108

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A Mathematical Theory of Agency and Intelligence

Researchers propose a mathematical framework distinguishing agency from intelligence in AI systems, introducing 'bipredictability' as a measure of effective information sharing between observations, actions, and outcomes. Current AI systems achieve agency but lack true intelligence, which requires adaptive learning and self-monitoring capabilities.

AIBearisharXiv – CS AI · Feb 277/106

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Agency and Architectural Limits: Why Optimization-Based Systems Cannot Be Norm-Responsive

New research demonstrates that AI systems trained via RLHF cannot be governed by norms due to fundamental architectural limitations in optimization-based systems. The paper argues that genuine agency requires incommensurable constraints and apophatic responsiveness, which optimization systems inherently cannot provide, making documented AI failures structural rather than correctable bugs.