Assessing Deep Learning: A Work Program for the Humanities in the Age of Artificial Intelligence

90 Pages Posted: 11 Sep 2023

See all articles by Jan Segessenmann

Jan Segessenmann

University of Fribourg

Thilo Stadelmann

Zurich University of Applied Sciences

Andrew Davison

Faculty of Divinity

Oliver Dürr

University of Fribourg

Date Written: August 28, 2023

Abstract

Following the success of deep learning (DL) in research, we are now witnessing the fast and widespread adoption of artificial intelligence (AI) in daily life, influencing the way we act, think, and organize our lives. However, much still remains a mystery when it comes to how these systems achieve such high performance and why they reach the outputs they do. This presents us with an unusual combination: of technical mastery on the one hand, and a striking degree of mystery on the other. This conjunction is not only fascinating, but it also poses considerable risks, which urgently require our attention. Awareness of the need to analyze ethical implications, such as fairness, equality, and sustainability, is growing. However, other dimensions of inquiry receive less attention, including the subtle but pervasive ways in which our dealings with AI shape our way of living and thinking, transforming our culture and human self-understanding. If we want to deploy AI positively in the long term, a broader and more holistic assessment of the technology is vital, involving not only scientific and technical perspectives but also those from the humanities. To this end, we present outlines of a work program for the humanities that aim to contribute to assessing and guiding the potential, opportunities, and risks of further deploying DL systems. This paper is structured in four modular parts: a general introduction (section 1), an introduction to the workings of DL for uninitiated non-technical readers (section 2), a more mathematical introduction to DL (appendix A), and a main part, containing the outlines of a work program for the humanities (section 3). Readers familiar with mathematical notions might want to skip 2 and instead read A. Readers familiar with DL in general might want to ignore sections 2 and A altogether and instead directly read 3 after 1.

Keywords: Deep Learning, Anthropology, Humanities, Artificial Intelligence, Ethics, Philosophy

Suggested Citation

Segessenmann, Jan and Stadelmann, Thilo and Davison, Andrew and Dürr, Oliver, Assessing Deep Learning: A Work Program for the Humanities in the Age of Artificial Intelligence (August 28, 2023). Available at SSRN: https://ssrn.com/abstract=4554234 or http://dx.doi.org/10.2139/ssrn.4554234

Jan Segessenmann (Contact Author)

University of Fribourg ( email )

Avenue de l'Europe 20
CH-1700 Fribourg
Switzerland

Thilo Stadelmann

Zurich University of Applied Sciences ( email )

Centre for Artificial Intelligence
Technikumstrasse 71
Winterthur, CH 8401
Switzerland

Andrew Davison

Faculty of Divinity ( email )

Trinity Ln
Cambridge, CB2 1TN
United Kingdom

Oliver Dürr

University of Fribourg ( email )

Avenue de l'Europe 20
CH-1700 Fribourg
Switzerland

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