Personhood and AI: Why large language models don’t understand us

AI and Society:1-8 (forthcoming)
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Abstract

Recent artificial intelligence advances, especially those of large language models (LLMs), have increasingly shown glimpses of human-like intelligence. This has led to bold claims that these systems are no longer a mere “it” but now a “who,” a kind of person deserving respect. In this paper, I argue that this view depends on a Cartesian account of personhood, on which identifying someone as a person is based on their cognitive sophistication and ability to address common-sense reasoning problems. I contrast this with a different account of personhood, one where an agent is a person if they are autonomous, responsive to norms, and culpable for their actions. On this latter account, I show that LLMs are not person-like, as evidenced by their propensity for dishonesty, inconsistency, and offensiveness. Moreover, I argue current LLMs, given the way they are designed and trained, cannot be persons—either social or Cartesian. The upshot is that contemporary LLMs are not, and never will be, persons.

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Jacob Browning
New York University

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References found in this work

Making it Explicit.Isaac Levi & Robert B. Brandom - 1996 - Journal of Philosophy 93 (3):145.
The Expressive Function of Punishment.Joel Feinberg - 1965 - The Monist 49 (3):397-423.
The phenomenology of spirit.G. W. F. Hegel, H. C. Brockmeyer & W. T. Harris - 1868 - Journal of Speculative Philosophy 2 (3):165 - 171.
Heidegger on being a person.John Haugeland - 1982 - Noûs 16 (1):15-26.

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