Toward aitiopoietic cognition: bridging the evolutionary divide between biological and machine-learned causal systems.
Frontiers in cognition January 1, 2025 Tomas Veloz
Autopoietic systems (biological organisms) and machine learning systems (MLSs) differ fundamentally in how causal reasoning emerges and operates. While both can exhibit similar behaviors and cognitive abilities, they are structurally distinct in how causality is operationalized, physically embodied, and epistemologically grounded. In organisms, causal reasoning is tied to self-maintenance across multiple organizational levels, with goals emerging from survival imperatives. In MLSs, causality is implemented through statistical optimization with externally imposed objectives, lacking the material self-reorganization that drives biological causal advancement.