An HCAI Methodological Framework: Putting it Into Action to Enable Human-Centered AI

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Authors: Wei Xu, Zaifeng Gao, Marvin J. Dainoff
Cited by: 13
References: 114

Abstract

Human-centered artificial intelligence (HCAI) is a design philosophy that prioritizes humans in the design, development, deployment, and use of AI systems, aiming to maximize AI’s benefits while mitigating its negative impacts. Despite its growing prominence in literature, the lack of methodological guidance for its implementation poses challenges to HCAI practice. To address this gap, this article proposes a comprehensive HCAI methodological framework (HCAI-MF) comprising five key components: HCAI requirement hierarchy, approach and method taxonomy, process, interdisciplinary collaboration approach, and multilevel design paradigms. A case study demonstrates HCAI-MF’s practical implications, while the article also analyzes implementation challenges. Actionable recommendations and a “three-layer” HCAI implementation strategy are provided to address these challenges and guide future evolution of HCAI-MF. HCAI-MF is presented as a systematic and executable methodology capable of overcoming current gaps, enabling effective design, development, deployment, and use of AI systems, and advancing HCAI practice.

Fields of Study & Subjects

Ethics and Social Impacts of AI Explainable Artificial Intelligence (XAI) Persona Design and Applications

Publication details

Journal / source
IEEE Transactions on Human-Machine Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
56
Issue
1
Pages
78–94
Publication date
1 January 2026