Theory languages in designing artificial intelligence

Pertti Saariluoma*, Antero Karvonen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

Abstract

The foundations of AI design discourse are worth analyzing. Here, attention is paid to the nature of theory languages used in designing new AI technologies because the limits of these languages can clarify some fundamental questions in the development of AI. We discuss three types of theory language used in designing AI products: formal, computational, and natural. Formal languages, such as mathematics, logic, and programming languages, have fixed meanings and no actual-world semantics. They are context- and practically content-free. Computational languages use terms referring to the actual world, i.e., to entities, events, and thoughts. Thus, computational languages have actual-world references and semantics. They are thus no longer context- or content-free. However, computational languages always have fixed meanings and, for this reason, limited domains of reference. Finally, unlike formal and computational languages, natural languages are creative, dynamic, and productive. Consequently, they can refer to an unlimited number of objects and their attributes in an unlimited number of domains. The differences between the three theory languages enable us to reflect on the traditional problems of strong and weak AI.
Original languageEnglish
Pages (from-to)2249–2258
JournalAI and Society
Volume39
Issue number5
DOIs
Publication statusPublished - Oct 2024
MoE publication typeA1 Journal article-refereed

Funding

Open Access funding provided by University of Jyväskylä (JYU). This research has been supported by Business Finland for the SEED-project

Keywords

  • Artificial intelligence
  • Computational languages
  • Formal languages
  • Natural languages
  • Theory languages

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