About this Research Topic
Emotions have long been considered a unique human trait, but recent advances in Artificial Intelligence (AI) have led to an increasing interest in the incorporation of emotional intelligence into machines. Natural Language Processing, computer vision, and affective computing techniques, among others, are becoming involved in the detection and analysis of human emotions. The main aim is to allow machines to properly recognize, interpret, and respond to human emotions, enhancing their ability to interact with us in more meaningful ways, especially in multimodal and multimedia settings. The potential applications of this integration encompass a wide range of disciplines, from Customer Relations Management services to Healthcare. However, there are also ethical concerns regarding privacy, discrimination, and potential abuse or misuse that must be addressed.
The objectives of this Research Topic are based on understanding how emotions can be integrated into machines and how this integration can improve human-machine interactions. It aims to explore various techniques to detect and interpret human emotions, as well as the development of algorithms that allow machines to respond appropriately to these emotions. This collection intends to help in the creation of future AIs that are more responsive, empathetic, and intuitive in their interactions with humans, which will lead to better user experiences in fields such as healthcare, education, and entertainment. In addition, ethical considerations around data privacy, bias leading to discrimination, or transparency will be carefully considered, in order to ensure AI is developed and used responsibly and beneficially, following international guidelines.
The collection would aim to bring together researchers and experts to discuss the latest advances and challenges in the field of emotions and AI. Potential authors could submit articles on a wide range of topics related to emotions and AI, such as emotion recognition, affective computing, natural language processing, machine vision, and human-machine interaction. The collection would also welcome papers exploring the ethical, social, and cultural implications of emotions and AI. Additionally, authors can submit articles showcasing real-world applications of emotions and AI in areas such as healthcare, education, entertainment, and customer service. Topics could include, but are not limited to:
• Analysis of the relationship between AI, emotions, and the development of critical thinking;
• Psychological advantages and disadvantages of the use of AI in educational contexts and teaching-learning processes;
• Emotion Recognition: Techniques and algorithms for detecting and interpreting human emotions from various sources such as facial expressions, voice, and physiological signals;
• Affective Computing: The integration of emotional intelligence into machines, enabling them to recognize, understand, and respond to human emotions;
• Natural Language Processing: Utilizing language processing techniques to analyze and interpret emotional content in text and speech;
• Machine Vision: Using computer vision algorithms to analyze facial expressions, body language, and other visual cues to infer emotions;
• Human-Machine Interaction: Exploring how emotions can enhance the interaction between humans and machines, leading to more intuitive and empathetic interfaces;
• Ethical Considerations: Examining the ethical implications of integrating emotions into machines, addressing concerns related to data privacy, bias, discrimination, and transparency;
• Social and Cultural Implications: Investigating how emotions and AI intersect with societal and cultural norms, including the impact on human values, attitudes, and behaviors;
• Real-World Applications: Showcasing practical implementations of emotions and AI in domains such as healthcare (e.g., emotion-aware virtual assistants for mental health), education (e.g., adaptive tutoring systems), entertainment (e.g., emotion-based storytelling), and customer service (e.g., emotion-aware chatbots);
• Algorithm Development: Developing novel algorithms and models that enable machines to accurately perceive and interpret emotions;
• User Experience: Exploring how emotions and AI can improve user experiences, leading to more engaging, personalized, and satisfying interactions in various domains;
• These sub-topics encompass the main areas of research and discussion within the field of emotions and AI, as outlined in the given context.
The Research Topic collection would provide a platform for networking, collaboration, and knowledge sharing among participants from academia, industry, and government.
The objectives of this Research Topic are based on understanding how emotions can be integrated into machines and how this integration can improve human-machine interactions. It aims to explore various techniques to detect and interpret human emotions, as well as the development of algorithms that allow machines to respond appropriately to these emotions. This collection intends to help in the creation of future AIs that are more responsive, empathetic, and intuitive in their interactions with humans, which will lead to better user experiences in fields such as healthcare, education, and entertainment. In addition, ethical considerations around data privacy, bias leading to discrimination, or transparency will be carefully considered, in order to ensure AI is developed and used responsibly and beneficially, following international guidelines.
The collection would aim to bring together researchers and experts to discuss the latest advances and challenges in the field of emotions and AI. Potential authors could submit articles on a wide range of topics related to emotions and AI, such as emotion recognition, affective computing, natural language processing, machine vision, and human-machine interaction. The collection would also welcome papers exploring the ethical, social, and cultural implications of emotions and AI. Additionally, authors can submit articles showcasing real-world applications of emotions and AI in areas such as healthcare, education, entertainment, and customer service. Topics could include, but are not limited to:
• Analysis of the relationship between AI, emotions, and the development of critical thinking;
• Psychological advantages and disadvantages of the use of AI in educational contexts and teaching-learning processes;
• Emotion Recognition: Techniques and algorithms for detecting and interpreting human emotions from various sources such as facial expressions, voice, and physiological signals;
• Affective Computing: The integration of emotional intelligence into machines, enabling them to recognize, understand, and respond to human emotions;
• Natural Language Processing: Utilizing language processing techniques to analyze and interpret emotional content in text and speech;
• Machine Vision: Using computer vision algorithms to analyze facial expressions, body language, and other visual cues to infer emotions;
• Human-Machine Interaction: Exploring how emotions can enhance the interaction between humans and machines, leading to more intuitive and empathetic interfaces;
• Ethical Considerations: Examining the ethical implications of integrating emotions into machines, addressing concerns related to data privacy, bias, discrimination, and transparency;
• Social and Cultural Implications: Investigating how emotions and AI intersect with societal and cultural norms, including the impact on human values, attitudes, and behaviors;
• Real-World Applications: Showcasing practical implementations of emotions and AI in domains such as healthcare (e.g., emotion-aware virtual assistants for mental health), education (e.g., adaptive tutoring systems), entertainment (e.g., emotion-based storytelling), and customer service (e.g., emotion-aware chatbots);
• Algorithm Development: Developing novel algorithms and models that enable machines to accurately perceive and interpret emotions;
• User Experience: Exploring how emotions and AI can improve user experiences, leading to more engaging, personalized, and satisfying interactions in various domains;
• These sub-topics encompass the main areas of research and discussion within the field of emotions and AI, as outlined in the given context.
The Research Topic collection would provide a platform for networking, collaboration, and knowledge sharing among participants from academia, industry, and government.
Keywords: Emotions, Artificial Intelligence, Human-Machine Interaction, Ethics, emotional regulation, emotional processing, emotion perception
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
