Gender, Emotions, and Artificial Intelligence

The intersection of gender, emotions, and artificial intelligence (AI) is a rapidly growing area of research. AI systems, now ubiquitous, are not neutral; biases in training data and design decisions can inadvertently perpetuate societal inequalities and harmful stereotypes. This is particularly evident in affective AI, which seeks to recognize and respond to human emotions, and in applications like facial recognition where disparities based on gender and skin tone have been observed. Understanding these biases and their consequences is crucial as AI increasingly influences aspects of daily life. Research aims to identify and mitigate these biases, ensuring AI benefits all members of society equitably. This necessitates an interdisciplinary approach, drawing from emotion science, psychology, AI ethics, and related fields.

This Research Topic addresses the critical problem of gender bias within Artificial Intelligence (AI) systems, particularly concerning the representation and understanding of emotions. AI's inherent biases, stemming from biased data and design, can amplify existing inequalities and perpetuate harmful stereotypes across various applications from facial recognition to virtual assistants, affecting areas like criminal justice, healthcare, and the labor market. The primary goal is to foster a deeper understanding of these complex interactions and to identify actionable strategies for mitigating gender biases in AI. This can be achieved through innovative research on bias detection and mitigation techniques in algorithms, development of culturally sensitive affective AI, analyses of the impact of AI on gender equity in employment, and exploration of the ethical implications of AI in relation to gender and emotions. Recent advances in fairness-aware machine learning, explainable AI, and diverse dataset creation offer promising avenues for addressing this challenge. Ultimately, this Research Topic aims to contribute to the development of equitable AI technologies that promote a more just and inclusive society for all genders.

Areas of interest include, but are not limited to the following: - Gender Bias in AI Algorithms: Identification and Mitigation. - Affective AI and the Representation of Emotions: Gender Perspectives. - The Impact of Automation on Employment: A Gender Analysis. - Virtual Assistants and the Social Construction of Gender. - AI and Mental Health: Implications for Gender Equity. - Ethics of AI and Gender: Normative Frameworks and Responsibility. - The Social Construction of Gender in AI Training Data. - AI and Gender-Based Violence: Prevention and Response. - AI Education and Gender: Promoting Diversity and Inclusion. - Representations of Gender in Creative AI: Art, Music, and Literature. These subtopics encompass the main areas of research and discussion within the field of gender, emotions, and AI, as outlined in the given context. This Research Topic welcomes Original Research, Reviews, Mini Reviews, Methods, Theory and Hypothesis and Theoretical Perspectives.