Observational analysis reveals distinct agentive architectures in biological agents, suggesting AI may benefit from evolutionary insights.
The quest to make artificial intelligence models more human-like could profit from a study of biological agents and their evolution. Recent research suggests that animal species on the evolutionary line to humans employed a series of qualitatively distinct agentive architectures of ever-increasing complexity, with humans then forming shared agencies coordinated via linguistic communication.
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Michael Tomasello (2025) studied this question.
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