This study responds to Agnieszka Landowska’s paper about the lack of accuracy in emotion recognition.
Abstract
Purpose
This study responds to Agnieszka Landowska’s paper about the lack of accuracy in emotion recognition.
Design/methodology/approach
The approach is purely theoretical. The paper also refers to empirical studies.
Findings
The author first elaborates on Landowska’s “postulates” (normative guidelines) and then shortly expands on how virtual chatbots such as “AI therapists” pose considerable challenges to emotion recognition algorithms as well.
Originality/value
This viewpoint’s value is to elaborate and expand on an ongoing discussion on emotion recognition technologies.
Details
Keywords
Katleen Gabriels and Mark Coeckelbergh
This paper aims to fill this gap (infra, originality) by providing a conceptual framework for discussing “technologies of the self and other,” by showing that, in most cases…
Abstract
Purpose
This paper aims to fill this gap (infra, originality) by providing a conceptual framework for discussing “technologies of the self and other,” by showing that, in most cases, self-tracking also involves other-tracking.
Design/methodology/approach
In so doing, we draw upon Foucault’s “technologies of the self” and present-day literature on self-tracking technologies. We elaborate on two cases and practical domains to illustrate and discuss this mutual process: first, the quantified workplace; and second, quantification by wearables in a non-clinical and self-initiated context.
Findings
The main conclusion is that these shapings are never (morally) neutral and have ethical implications, such as regarding “quantified otherness,” a notion we propose to point at the risk that the other could become an object of examination and competition.
Originality/value
Although there is ample literature on the quantified self, considerably less attention is given to how the relation with the other is being shaped by self-tracking technologies that allow data sharing (e.g. wearables or apps such as Strava or RunKeeper).