A Prolegomenon on the Philosophical Foundations of Deep Learning as Theory of (Artificial) Intelligence

Scientific paper - Original scientific paper

• Author: Sandro Skansi; MBZ: 343196
• Author: Marko Kardum; MBZ: 363922
• Author's institution: University of Zagreb; Faculty of Croatian Studies; (Department of Philosophy and Cultural Studies)
• Scientific / art field, discipline and subdiscipline: HUMANISTIC SCIENCES; Philosophy

Abstract (english)

This paper examines the philosophical foundations of deep learning. By pointing to the beginnings of deep learning and artificial neuron as a logical model of a human neuron, it is possible to claim that artificial intelligence was developed even before its official creation and that it was strongly connected to propositional logic. Bearing in mind some major setbacks in the development of neural networks, we show that deep learning can be treated as the theory of artificial intelligence and that it falls under artificial intelligence paradigm by claiming that everything can be done with learning alone and that all intelligent behavior is learnable. Thus, deep learning is a philosophical or an epistemological approach in which a form of radical empiricism must be advocated. Therefore, there is nothing in the mind that was not in the senses, and there cannot be anything in the mind that is not learnable.

• Keywords (english): artificial intelligence; cybernetics; deep learning; empiricism; neural networks
• Language: english
• Publication type: Scientific paper - Original scientific paper
• Publication status: Published
• Peer review: Peer review
• Publication version: Published version
• Journal title: Disputatio philosophica : international journal on philosophy and religion
• Numbering: vol. 23, no. 1, pp. 89-99
• p-ISSN: 1332-1056
• DOI: https://doi.org/10.32701/dp.23.1.6
• URN:NBN: urn:nbn:hr:111:956092
• Publication: 2021
• Document URL: http://bib.irb.hr/1178269
• Type of resource: Text
• Access conditions: Open access
• Created on: 2023-03-16 11:26:59