Artificial Intelligence in HCI 6th International Conference, AI-HCI 2025, Held as Part of the 27th HCI International Conference, HCII 2025, Gothenburg, Sweden, June 22–27, 2025, Proceedings, Part II

The four-volume set LNAI 15819–15822 constitutes the thoroughly refereed proceedings of the 6th International Conference on Artificial Intelligence in HCI, AI-HCI 2025, held as part of the 27th International Conference, HCI International 2025, which took place in Gothenburg, Sweden, June 22-17, 2025.

The total of 1430 papers and 355 posters included in the HCII 2025 proceedings was carefully reviewed and selected from 7972 submissions.

The papers have been organized in topical sections as follows:

Part I: Trust and Explainability in Human-AI Interaction; User Perceptions, Acceptance, and Engagement with AI; UX and Socio-Technical Considerations in AI

Part II: Bias Mitigation and Ethics in AI Systems; Human-AI Collaboration and Teaming; Chatbots and AI-Driven Conversational Agents; AI in Language Processing and Communication.

Part III: Generative AI in HCI; Human-LLM Interactions and UX Considerations; Everyday AI: Enhancing Culture, Well-Being, and Urban Living.

Part IV: AI-Driven Creativity: Applications and Challenges; AI in Industry, Automation, and Robotics; Human-Centered AI and Machine Learning Technologies.

.- Bias Mitigation and Ethics in AI Systems.

.- Research Ethics for Data Collection from Human Participants – Case Study and Recommendations.

.- A Synthesis of Reflections, Attitudes and Suggestions Towards Mindful Implementation of LLMs in Digital First Pathways.

.- Mechanistic Exploration of the Architectural Impact of DPO Fine-Tuning on Ethical Alignment in LLMs.

.- Prompting Fairness: How End Users Can Mitigate Bias in AI Systems.

.- Bias in AI Recommender Systems: Examining Gender Disparities in STEM and Non-STEM Career Recommendations for Professional Development.

.- Mapping Moral Reasoning Circuits: A Mechanistic Analysis of Ethical Decision-Making in Large Language Model.

.- Evaluating Fairness and Bias in Large Language Models for Tabular Data.

.- Human-AI Collaboration and Teaming.

.- Exploring the Application of AI to Qualitative Data Analysis: A Comparative Study in the Field of Industrial Design Education.