Dron, J. The Human Nature of Generative AIs and the Technological Nature of Humanity: Implications for Education. Digital2023, 3, 319-335.
Dron, J. The Human Nature of Generative AIs and the Technological Nature of Humanity: Implications for Education. Digital 2023, 3, 319-335.
Dron, J. The Human Nature of Generative AIs and the Technological Nature of Humanity: Implications for Education. Digital2023, 3, 319-335.
Dron, J. The Human Nature of Generative AIs and the Technological Nature of Humanity: Implications for Education. Digital 2023, 3, 319-335.
Abstract
This paper applies a theoretical model to analyze the ways that widespread use of generative AIs (GAIs) in education and, more broadly, in contributing to and reflecting the collective intelligence of our species, can and will change us. The model extends Brian Arthur’s insights into the nature of technologies as the orchestration of phenomena to our use by explaining the nature of humans participation in their enactment, whether as part of the orchestration (hard technique, where our roles must be performed correctly) or as orchestrators of phenomena (soft technique performed creatively or idiosyncratically). Education may be seen as a technological process for developing the soft and hard techniques of humans to participate in the technologies and thus the collective intelligence of our cultures. Unlike all earlier technologies, by embodying that collective intelli-gence themselves, GAIs can closely emulate and implement not only the hard technique but also the soft that, until now, was humanity’s sole domain: the very things that technologies enabled us to do can now be done by the technologies themselves. The consequences for what, how, and even whether we learn are profound. The paper explores some of these consequences and concludes with theoretically informed approaches that may help us to avert some dangers while benefiting from the strengths of generative AIs.
Keywords
AI; education; technology
Subject
Social Sciences, Education
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
