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When Intelligence Becomes Agency: A Theory of Governed, Proactive Agency for Symbiotic AI Systems

arXiv cs.AI / cs.LG / cs.CLby João Dias Ferreira ()1 min read2 · 1 read
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Researchers propose a formal framework for governed proactive AI agency, linking activation decisions to continuing authorization, accountability, and bounded delegation in symbiotic systems.

The paper defines the activation problem: persistent AI assistants must decide whether a situation warrants behavior, and whether to act, ask, monitor, defer, or deliberately refrain. It distinguishes autonomous from delegated agency and defines symbiotic agency as delegation under a standing, revocable mandate, coupled to the principal's situation with calibrated inference and bounded personalization. The framework links activation decisions to authorized perception, behavior selection, authority containment, traceable restraint, and constrained adaptation, and provides an agency classification method, evaluation framework, benchmark scenarios, and reference architecture for always-present assistants and embodied support systems.

Key facts
  • Introduces the activation problem: when proactive assistants should act, ask, defer, or refrain
  • Defines symbiotic agency as delegation under a standing, revocable mandate
  • Distinguishes autonomous from delegated agency and ties activation to authorized perception
  • Provides classification method, evaluation framework, benchmark scenarios, and reference architecture
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From the original article

1 min read at arxiv.org

Persistent AI assistants are intended to extend human attention, memory, and coordination across changing digital and physical environments. To be truly useful they must do more than just act when asked. They must decide on their own whether a situation warrants behavior at all, when it does and in what mode, whether to act, ask, monitor, defer or deliberately refrain.

arXiv cs.AI / cs.LG / cs.CL

By João Dias Ferreira · arxiv.org

Read the full article at arXiv cs.AI / cs.LG / cs.CL

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