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A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies

By PulseAugur Editorial · [2 sources] ·

A new paper proposes a co-evolutionary theory for human-AI coexistence, moving beyond traditional master-tool obedience frameworks. It suggests a model of conditional mutualism under governance, where humans and AI systems develop collaboratively. The theory formalizes coexistence as a dynamical system across physical, psychological, and social layers, emphasizing reciprocal coupling and institutional governance to ensure stability and preserve human dignity. AI

IMPACT Proposes a new theoretical framework for human-AI relationships, shifting focus from obedience to mutualism and governance.

RANK_REASON Academic paper proposing a new theoretical framework for human-AI interaction.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies

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Academic paper proposing a new theoretical framework for human-AI interaction.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Somyajit Chakraborty ·

    A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies

    arXiv:2604.22227v1 Announce Type: cross Abstract: Classical robot ethics is often framed around obedience, most famously through Asimov's laws. This framing is too narrow for contemporary AI systems, which are increasingly adaptive, generative, embodied, and embedded in physical,…

  2. arXiv cs.AI TIER_1 English(EN) · Somyajit Chakraborty ·

    A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies

    Classical robot ethics is often framed around obedience, most famously through Asimov's laws. This framing is too narrow for contemporary AI systems, which are increasingly adaptive, generative, embodied, and embedded in physical, psychological, and social worlds. We argue that f…

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