Making AI meaningful again
Not on the map. Why?
Abstract (arXiv)
Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial intelligence encouraged by these successes, especially in the domain of language processing. We then show an alternative approach to language-centric AI, in which we identify a role for philosophy.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Jan 2019.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 3; 2024: 1.
5 papers.
- 2023Contrasting Linguistic Patterns in Human and LLM-Generated News Textcited by 62
- 2023Meaning and understanding in large language modelscited by 5
- 2024Can AI and humans genuinely communicate?cited by 1
- 2021An argument for the impossibility of machine intelligencecited by 0
- 2023Why machines do not understand: A response to Sogaardcited by 0
- 2024Can AI and humans genuinely communicate?14 Feb 2024
- 2023Meaning and understanding in large language models26 Oct 2023
- 2023Contrasting Linguistic Patterns in Human and LLM-Generated News Text17 Aug 2023
- 2023Why machines do not understand: A response to Sogaard7 Jul 2023
- 2021An argument for the impossibility of machine intelligence20 Oct 2021