HCI International 2024 – Late Breaking Papers 26th International Conference on Human-Computer Interaction, HCII 2024, Washington, DC, USA, June 29 – July 4, 2024, Proceedings, Part IX

This nine-volume set LNCS 15473-15482 constitutes the proceedings of the 26th International Conference, HCI International 2023, in Washington, DC, USA, in June/July 2024.
For the HCCII 2024 proceedings, a total of 1271 papers and 309 posters was carefully reviewed and selected from 5108 submissions. Additionally, 222 papers and 104 posters are included in the volumes of the proceedings published after the conference, as “Late Breaking Work”.
These papers were organized in the following topical sections: HCI Theories, Methods and Tools; Multimodal Interaction; Interacting with Chatbots and Generative AI; Interacting in Social Media; Fintech, Consumer Behavior and the Business Environment; Design for Health and Wellbeing; Ergonomics and Digital Human Modelling; Virtual Experiences in XR and the Metaverse; Playing Experiences; Design for Learning; New Cultural and Tourism Experiences; Accessibility and Design for All; Design for Older Adults; User Experience Design and Evaluation: Novel Approaches and Case Studies; Safety, Security and Privacy; HCI in Automated Vehicles and Automotive; HCI in Aviation, Transport and Safety; Human-Centered AI; AI for Decision Making and Sentiment Analysis.

Human-Centered AI: Multimodal Referring Expression Generation for Human-Computer Interaction.- thics in the Use of Artificial Intelligence in the Media.- Are Fair Machine Learning Models More Useful?.- A Human-Centered Algorithmic Management Framework: A Literature Review.- Public Perception of AI: A Review.- Towards a Simplified AI Adoption Framework: Success Factors for the Implementation of Artificial Intelligence Information Systems.- Realizing the Promise of AI Governance Involving Humans-In-The-Loop.- Integrating HCI Datasets in Project-Based Machine Learning Courses: A College-Level Review and Case Study.- Human Centered Approaches and Taxonomies for Explainable Artificial Intelligence.- Enhancing Explainability in Medical AI: Developing Human-Centered Participatory Design Cards. AI for Decision Making and Sentiment Analysis: SenticNet 8: Fusing Emotion AI and Commonsense AI for Interpretable, Trustworthy, and Explainable Affective Computing.- Text Characteristics Vector: Rethinking Human-Centered Sentiment Analysis with Emotion-Related Text Characteristics.- Unbiased Recommender Learning for Enhanced Relevance and Coverage.- AI Web Service Solution for Real-Time Forest Fire Prevention.- Adaptive Planning: Comparing Human and Generative AI Responses in Premortem Planning.- Neurosymbolic AI for Personalized Sentiment Analysis.- An Exploratory Study of Conventional Machine Learning and Large Language Models for Sentiment Analysis.