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Emotional responses to human values in technology: The case of conversational agents.

Authors :
Görnemann, Esther
Spiekermann, Sarah
Source :
Human-Computer Interaction; 2024, Vol. 39 Issue 5/6, p310-337, 28p
Publication Year :
2024

Abstract

This article explores the emotional responses of users to conversational agents (CAs) and the underlying values that shape these responses. The authors propose a novel integrated representation called "Emotion Value Assessment" (EVA) that allows researchers and practitioners to explore emotional reactions to technology in relation to the values fostered or harmed. The article provides insights into the interaction dynamics and emotional aspects of technology, which can inform product design and development. The authors conducted a qualitative study using interviews and focus groups to collect data on value implications and emotional responses related to Alexa. The results showed that anger-type emotions were most prominent, often related to functionality and usability issues, while joy was associated with comfort and quality of life. Surprise had both positive and negative connotations, and fear was linked to concerns about privacy and autonomy. The text also provides guidance on how to construct and interpret the EVA. The EVA focuses on three perspectives: emotional response, value quality, and value-bearer. The framework aims to provide a more nuanced understanding of user experiences and the impact of technology on human values. The EVA can be used in various stages of system design and development, providing insights into potential value harms and benefits, as well as informing ethical decision-making. However, the EVA has limitations in terms of generalizability and the complexity of analyzing values and emotions. Future research could explore instrumental relationships between different values and include a wider range of subordinate emotions in the analysis. The article suggests that future research should aim for better [Extracted from the article]

Details

Language :
English
ISSN :
07370024
Volume :
39
Issue :
5/6
Database :
Complementary Index
Journal :
Human-Computer Interaction
Publication Type :
Academic Journal
Accession number :
179415587
Full Text :
https://doi.org/10.1080/07370024.2022.2136094