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Emotion artificial intelligence : Deep mediatised and machine-reflected self-emotions

Feher, Katalin (2022) Emotion artificial intelligence : Deep mediatised and machine-reflected self-emotions. In: Mediatisation of Emotional Life. Routledge, London; New York, pp. 41-55. ISBN 9781032181066

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Abstract

The digitally mediatised self is becoming intensively involved in emerging Emotion AI services. The purpose of this chapter is to conceptualise how Emotion AI recognises the quantified and mediatised self, and how the self reflects emerging AI-driven media technologies? Three interrelated concepts interpret the changes, such as growing dependence on media technology, the disappearance of media into the lifeworld, and deep mediatisation. These concepts draw a digitalised-mediatised self with a quantified and representative entity. A metaphor of “water reflection” and the “Mirror Ritual” art project extends the theoretical considerations to present how the self resonates with AI technology through emotion and love. The resulting conceptualisation proposes considering the competing future perspectives of the self with options of blended self-AI or AI-augmented self. The ultimate question is the well-being and satisfaction of the self, even if AI ethics detects controversial cases and biases due to cultural and moral codes. The chapter contributes to comprehensively understanding the available key terminology, development and art of the field.

Item Type: Book Section
Subjects: H Social Sciences / társadalomtudományok > H Social Sciences (General) / társadalomtudomány általában
H Social Sciences / társadalomtudományok > HE Transportation and Communications / Szállítás, hírközlés > HE2 Communications / hírközlés
H Social Sciences / társadalomtudományok > HM Sociology / társadalomkutatás > HM5 Social psychology / szociálpszichológia
H Social Sciences / társadalomtudományok > HM Sociology / társadalomkutatás > HM6 Sociology of culture / kultúra szociológiája
Depositing User: Dr. Katalin Feher
Date Deposited: 18 Aug 2023 07:23
Last Modified: 18 Aug 2023 07:23
URI: http://real.mtak.hu/id/eprint/171443

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