Do Machine-Learning Machines Learn?

Selmer Bringsjord, Naveen Sundar Govindarajulu, Shreya Banerjee, John Hummel

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We answer the present paper’s title in the negative. We begin by introducing and characterizing “real learning” (RL) in the formal sciences, a phenomenon that has been firmly in place in homes and schools since at least Euclid. The defense of our negative answer pivots on an integration of reductio and proof by cases, and constitutes a general method for showing that any contemporary form of machine learning (ML) isn’t real learning. Along the way, we canvass the many different conceptions of “learning” in not only AI, but psychology and its allied disciplines; none of these conceptions (with one exception arising from the view of cognitive development espoused by Piaget), aligns with real learning. We explain in this context by four steps how to broadly characterize and arrive at a focus on RL.

Original languageEnglish (US)
Title of host publicationStudies in Applied Philosophy, Epistemology and Rational Ethics
PublisherSpringer International Publishing
Pages136-157
Number of pages22
DOIs
StatePublished - Jan 1 2018

Publication series

NameStudies in Applied Philosophy, Epistemology and Rational Ethics
Volume44
ISSN (Print)2192-6255
ISSN (Electronic)2192-6263

ASJC Scopus subject areas

  • Philosophy

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  • Cite this

    Bringsjord, S., Govindarajulu, N. S., Banerjee, S., & Hummel, J. (2018). Do Machine-Learning Machines Learn? In Studies in Applied Philosophy, Epistemology and Rational Ethics (pp. 136-157). (Studies in Applied Philosophy, Epistemology and Rational Ethics; Vol. 44). Springer International Publishing. https://doi.org/10.1007/978-3-319-96448-5_14