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Original scientific paper

https://doi.org/10.52685/cjp.22.64.6

Non-Stupidity Condition and Pragmatics in Artificial Intelligence

Bojan Borstner orcid id orcid.org/0000-0002-0775-2200 ; University of Maribor, Maribor, Slovenia
Niko Šetar orcid id orcid.org/0000-0003-4264-0762 ; University of Maribor, Maribor, Slovenia


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Abstract

Symbol Grounding Problem (SGP) (Harnad 1990) is commonly considered one of the central challenges in the philosophy of artificial intelligence as its resolution is deemed necessary for bridging the gap between simple data processing and understanding of meaning and language. SGP has been addressed on numerous occasions with varying results, all resolution attempts having been severely, but for the most part justifiably, restricted by the Zero Semantic Commitment Condition (Taddeo and Floridi 2005). A further condition that demands explanatory power in terms of machine-to-human communication is the Non-Stupidity Condition (Bringsjord 2013) that demands an SG approach to be able to account for plausibility of higher-level language use and understanding, such as pragmatics. In this article, we undertake the endeavour of attempting to explain how merging certain early requirements for SG, such as embodiment, environmental interaction (Ziemke 1998), and compliance with the Z-Condition with symbol emergence (Sun 2000; Tangiuchi et al. 2016, etc.) rather than direct attempts at symbol grounding can help emulate human language acquisition (Vogt 2004; Cowley 2007). Along with the presumption that mind and language are both symbolic (Fodor 1980) and computational (Chomsky 2017), we argue that some rather abstract aspects of language can be logically formalised and finally, that this melange of approaches can yield the explanatory power necessary to satisfy the Non-Stupidity Condition without breaking any previous conditions.

Keywords

Artificial intelligence; symbol grounding; pragmatics; language; computationalism.

Hrčak ID:

278882

URI

https://hrcak.srce.hr/278882

Publication date:

7.6.2022.

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