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Computer Science > Artificial Intelligence

arXiv:2311.06703 (cs)
[Submitted on 12 Nov 2023 (v1), last revised 14 Nov 2023 (this version, v2)]

Title:Enabling Human-Centered AI: A Methodological Perspective

Authors:Wei Xu, Zaifeng Gao
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Abstract:Human-centered AI (HCAI) is a design philosophy that advocates prioritizing humans in designing, developing, and deploying intelligent systems, aiming to maximize the benefits of AI to humans and avoid potential adverse impacts. While HCAI continues to influence, the lack of guidance on methodology in practice makes its adoption challenging. This paper proposes a comprehensive HCAI framework based on our previous work with integrated components, including design goals, design principles, implementation approaches, interdisciplinary teams, HCAI methods, and HCAI processes. This paper also presents a "three-layer" approach to facilitate the implementation of the framework. We believe this systematic and executable framework can overcome the weaknesses in current HCAI frameworks and the challenges currently faced in practice, putting it into action to enable HCAI further.
Subjects: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Software Engineering (cs.SE)
Cite as: arXiv:2311.06703 [cs.AI]
  (or arXiv:2311.06703v2 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2311.06703

Submission history

From: Wei Xu [view email]
[v1] Sun, 12 Nov 2023 01:31:34 UTC (568 KB)
[v2] Tue, 14 Nov 2023 17:32:07 UTC (569 KB)
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