The 2025 International Workshop on Human-Augmented Intelligence and Collaboration (HAIC 2025)

Description

For the past few decades, the development of traditional artificial intelligence (AI) has primarily focused on improving technical performance, efficiency, and process automation. As AI systems become increasingly complex and permeate every aspect of human society, our expectations of AI must also evolve. Collaborative AI for Humanity emphasizes that AI's core goal is to serve humanity and enhance its capabilities.

In an era where human and artificial intelligence converge, Human-Augmented Intelligence and Collaboration (HAIC) emphasizes not only technological breakthroughs but also how to integrate artificial intelligence with human values, creativity, and decision-making capabilities. Compared to traditional artificial intelligence, which focuses solely on automation and efficiency, HAIC emphasizes collaboration, explainability, and fairness, striving to enhance human capabilities. This seminar will focus on cutting-edge research and applications in human-machine collaboration, including the establishment of trustworthy collaborative models, context-aware adaptive systems, and iterative mechanisms for continuous improvement through user feedback. We sincerely invite scholars from all fields to submit papers exploring human-centered system design, explainable AI, bias mitigation, human-machine decision support, and cross-disciplinary application cases covering healthcare, education, finance, governance, and culture.

Topics

The list of topics includes, but is not limited to:

• User-Centered Design: How to incorporate user participation throughout the AI system lifecycle to ensure that technology aligns with real needs and preferences.
• Explainability & Accountability: Ensure that AI's decision-making processes are presented in a human-understandable manner and establish accountability mechanisms.
• Bias Mitigation & Fairness: How to identify and eliminate bias in AI systems to ensure fair and non-discriminatory outcomes.
• Context Awareness: Explore the adaptability of AI across different cultures, societies, and application scenarios.
• Iteration & Feedback Loops: Continuously collect and integrate user feedback to ensure that AI development meets human needs in the long term.
• Human-AI Collaboration: Case studies, methods, and tools demonstrate how AI can serve as a human partner to assist in decision-making and innovation.
• Other research issues about Human-Augmented Intelligence and Collaboration

Submission

Authors are invited to submit original unpublished research papers as well as industrial practice papers. Simultaneous submissions to other conferences are not permitted.

Papers should be written in English and submitted in PDF format. The length of a camera ready paper will be limited to ten pages, including the title of the paper, the name and affiliation of each author, an abstract, and up to 6 keywords. Shorter version papers (up to four pages) are also allowed.

Authors must follow the DSA conference proceedings format (PDF | Word DOCX | Latex) to prepare their papers. Each submission will be reviewed by at least three program committee members. Paper selection is based on originality, technical contribution, presentation quality, and relevance to the workshop.

At least one of the authors of each accepted paper is required to pay a full registration fee and present the paper at the workshop. Arrangements are being made to publish selected accepted papers in reputable journals.

General Chair

Tse-Chuan Hsu Taiwan

Soochow University

Program Chairs

Chih-Hung Chang Taiwan

Feng Chia University

Yao-Hong Tsai Taiwan

Hsuan Chuang University

Program Committee (Tentative)

Previous HAIC