Outline

Ingegneria Sismica

Ingegneria Sismica

Gender Representation in Generative AI Image Creation and Adolescents’ Emotional Responses: A Dual Perspective from Semiotics and Affective Computing

Author(s): Jing Cai1, Jing Fu1, Yaokang Li2
1School of Computer Science and Engineering, Guangzhou Institute of Science and Technology, Guangzhou 510540, China
2School of Artificial Intelligence, Guangzhou Institute of Science and Technology, Guangzhou 510540, China
Cai, Jing., Fu, Jing., and Li, Yaokang. “Gender Representation in Generative AI Image Creation and Adolescents’ Emotional Responses: A Dual Perspective from Semiotics and Affective Computing.” Ingegneria Sismica Volume 43 Issue 2: 1-16, doi:10.65102/is2026884.

Abstract

In recent years, with the widespread use of generative artificial intelligence image technology by young people, numerous examples have emerged of these images being employed to convey emotions and gender identity through visual symbols. Using both semiotics and affective computing, this study will conduct content analysis, experimental research and in-depth interviews to explore the symbolic encoding features of gender representation in AI-generated images and adolescents’ emotional responses, as well as their underlying connections. Based on the above results, both traditional gender stereotypes in terms of clothing, posture and environment are still visible; at the same time, technology is also creating various forms of gender expression. Adolescents’ Emotional Responses to Stereotypic and Pluralistic Representations: Cognitive Conformity vs. Curiosity/Identification. Collect physiological and psychological data on young people using affective computing technology to provide objective support for studying the impact of gender symbols on them. Combine semiotic analysis and affective computing to build a new research system for exploring how gender cognition develops in AI environments; at the same time, provide theoretical support and practical suggestions for regulating the creation of AI images and promoting the healthy emotional growth of adolescents.

 

Keywords
Generative AI images; Gender Representation; Adolescents; Emotional Response; Semiotics; Affective Computing

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