mlsanityData to 7 Oct 2026

Can AI and humans genuinely communicate?

arXiv 2402.09494 ↗First posted 14 Feb 2024cs.HC cs.AIcited by 1

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Abstract (arXiv)

Can AI and humans genuinely communicate? In this article, after giving some background and motivating my proposal (sections 1 to 3), I explore a way to answer this question that I call the "mental-behavioral methodology" (sections 4 and 5). This methodology follows the following three steps: First, spell out what mental capacities are sufficient for human communication (as opposed to communication more generally). Second, spell out the experimental paradigms required to test whether a behavior exhibits these capacities. Third, apply or adapt these paradigms to test whether an AI displays the relevant behaviors. If the first two steps are successfully completed, and if the AI passes the tests with human-like results, this constitutes evidence that this AI and humans can genuinely communicate. This mental-behavioral methodology has the advantage that we don't need to understand the workings of black-box algorithms, such as standard deep neural networks. This is comparable to the fact that we don't need to understand how human brains work to know that humans can genuinely communicate. This methodology also has its disadvantages and I will discuss some of them (section 6).

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 20 of its 93 references that are in the map. First posted on arXiv 14 Feb 2024.

Builds on

20 of 93 references.

References · 20

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8 more
  1. 2022The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMscited by 57
  2. 2020Word meaning in minds and machinescited by 51
  3. 2023Towards A Holistic Landscape of Situated Theory of Mind in Large Language Modelscited by 32
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  5. 2023Creating a Large Language Model of a Philosophercited by 20
  6. 2023Does ChatGPT have Theory of Mind?cited by 16
  7. 2023Structural Similarities Between Language Models and Neural Response Measurementscited by 6
  8. 2019Making AI meaningful againcited by 5

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