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Opacity, Transparency, and the Ethics of Affective Computing.

Authors :
Kumar, Manohar
Aijaz, Aisha
Chattar, Omkar
Shukla, Jainendra
Mutharaju, Raghava
Source :
IEEE Transactions on Affective Computing; 2024, Vol. 17, p4-17, 14p
Publication Year :
2024

Abstract

Human opacity is the intrinsic quality of unknowability of human beings with respect to machines. The descriptive relationship between humans and machines, which captures how much information one can gather about the other, can be explicated using an opacity-transparency relationship. This relationship allows us to describe and normatively evaluate a spectrum of opacity where humans and machines may be either opaque or transparent. In this paper, we argue that the advent of Affective Computing (AC) has begun to shift the ideal position of humans on this spectrum towards greater transparency, while much of this technology is shifting towards opacity. We explore the implications of this shift with regard to the affective information of humans and how the threat to human opacity by AC systems has various adverse repercussions, such as infringement of one's autonomy, deception, manipulation, and increased anxiety. There are also distributive consequences that expose vulnerable groups to unjustified burdens and reduce them to mere profiles. We further provide an assessment of current AC technology, which follows the descriptive relationship between humans and machines from the lens of opacity and transparency. Finally, we foresee and address three possible objections to our claims. These are the beneficence of AC systems, their relation to privacy, and their restrictive capacity to capture human affects. Through these arguments, the paper aims to bring attention to the ontological relationship between humans and machines from the perspective of opacity and transparency while emphasizing on the gravity of the ethical concerns raised by their threat to human opacity. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19493045
Volume :
17
Database :
Complementary Index
Journal :
IEEE Transactions on Affective Computing
Publication Type :
Academic Journal
Accession number :
175943087
Full Text :
https://doi.org/10.1109/TAFFC.2023.3278230