Confusa Imago and Artificial Intelligence: Peter Abelard’s Theory of Abstraction as a Framework for Understanding the Cognitive Status of AI Systems
DOI:
https://doi.org/10.15633/pch.16104Słowa kluczowe:
abstraction, artificial intelligence, cognitive science, confusa imago, human, Middle Ages, mind, Peter Abelard, philosophy, universalsAbstrakt
This article addresses a philosophical problem arising from recent Vatican documents on artificial intelligence: how can AI systems demonstrate functional generalization while lacking the capacity for abstraction proper to human cognition? Drawing on the medieval philosophy of Peter Abelard (1079–1142), particularly his theory of the confusa imago (confused image) developed in the context of the twelfth-century dispute over universals, this article proposes a novel framework for understanding the cognitive status of contemporary AI systems. Abelard’s distinction between the representational level (confusa imago — an indeterminate mental image common to all instances of a kind) and the intellectual level (intellectus — the conscious act that transforms representation into genuine understanding) maps with striking precision onto the functional architecture of modern artificial neural networks. The article argues that AI systems achieve something structurally analogous to the generation of confused images through statistical learning, without performing the intellectual acts that would transform these representations into authentic concepts. This framework resolves the apparent paradox of generalization without abstraction, provides a principled basis for the claim that human cognitive involvement remains structurally necessary (not merely contingently useful) in human–AI collaboration, and offers concrete implications for the ethical design and deployment of AI systems. The analysis demonstrates that medieval philosophical categories retain unexpected explanatory power for contemporary problems in the philosophy of artificial intelligence.
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