@inproceedings{0b9c0e0ae7904725b9cf84999f0100c4,
title = "Human-Centric AI: From Explainability and Trustworthiness to Actionable Ethics",
abstract = "To address the potential risks of AI while supporting innovation and ensuring responsible adoption, there is an urgent need for clear governance frameworks grounded in human-centric values. It is imperative that AI systems operate in ways that are transparent, trustworthy, and ethically sound. Developing truly human-centric AI goes beyond technical innovation. It requires interdisciplinary collaboration and diverse perspectives. This workshop will explore key challenges and emerging solutions in the development of human-centric AI, with a focus on explainability, trustworthiness, fairness, and privacy. We welcome both theoretical contributions and practical case studies that demonstrate how human-centered principles are realized in real-world AI systems. The official workshop webpage is available at https://xai.kaist.ac.kr/Workshop/hcai2025/, which provides comprehensive information about the program.",
keywords = "ai ethics, explainability, explainable ai, fairness, human-ai interaction, human-centered ai, human-centric ai, privacy, trustworthiness, trustworthy ai",
author = "Jaesik Choi and Bohyung Han and Koo, \{Myoung Wan\} and Kyungman Bae and Yoo, \{Chang D.\} and Woo, \{Simon S.\} and Wojciech Samek",
note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s).; 34th ACM International Conference on Information and Knowledge Management, CIKM 2025 ; Conference date: 10-11-2025 Through 14-11-2025",
year = "2025",
month = nov,
day = "10",
doi = "10.1145/3746252.3761599",
language = "English",
series = "CIKM 2025 - Proceedings of the 34th ACM International Conference on Information and Knowledge Management",
publisher = "Association for Computing Machinery, Inc",
pages = "6898--6900",
booktitle = "CIKM 2025 - Proceedings of the 34th ACM International Conference on Information and Knowledge Management",
}