LLMs, Turing tests and Chinese rooms: the prospects for meaning in large language models

Inquiry: An Interdisciplinary Journal of Philosophy (forthcoming)
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Abstract

Discussions of artificial intelligence have been shaped by two brilliant thought-experiments: Turing’s Imitation Test for thinking systems and Searle’s Chinese Room Argument. In many ways, debates about large language models (LLMs) struggle to move beyond these original, opposing thought-experiments. So, in this paper, I ask whether we can move debate forward by exploring the features Sceptics about LLM abilities take to ground meaning. Section 1 sketches the options, while Sections 2 and 3 explore the common requirement for a robust relation between linguistic signs and external objects. Section 3 argues that concerns about worldly connections can be met and thus that outputs of LLMs should be viewed as genuinely meaningful. Section 4 then turns to the argument that the kind of derived meaning explored in Section 3 is insufficient for LLMs to count as meaningful systems per se, looking at the claim that they must possess original intentionality before we admit them to the space of meaning. I argue that this demand is not a prerequisite for meaning per se, but rather for some kinds of agency or conscious understanding. I suggest that the demands for original intentionality are not currently met by LLMs and that we should be cautious about whether we want them to be.

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Emma Borg
University of Reading

References found in this work

Intentionality: An Essay in the Philosophy of Mind.John R. Searle - 1983 - New York: Cambridge University Press.
Minds, brains, and programs.John Searle - 1980 - Behavioral and Brain Sciences 3 (3):417-57.
The meaning of 'meaning'.Hilary Putnam - 1975 - Minnesota Studies in the Philosophy of Science 7:131-193.
Individualism and the mental.Tyler Burge - 1979 - Midwest Studies in Philosophy 4 (1):73-122.

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