Bevilacqua Roberta, Bailoni Tania, Maranesi Elvira, Amabili Giulio, Barbarossa Federico, Ponzano Marta, Virgolesi Michele, Rea Teresa, Illario Maddalena, Piras Enrico Maria, Lenge Matteo, Barbi Elisa, Sakellariou Garifallia
Scientific Direction, IRCCS INRCA, Via Santa Margherita 5, Ancona, Italy, 39 0718004767.
Intelligent Digital Agents (IDA) Research Group, Fondazione Bruno Kessler (FBK), Trento, Italy.
JMIR Hum Factors. 2025 May 28;12:e67350. doi: 10.2196/67350.
With the rapid expansion of artificial intelligence (AI) applications, researchers have begun focusing on the concept of human-centered artificial intelligence (HCAI). This field is dedicated to designing AI systems that augment and improve human abilities, rather than substituting them.
The objective of the paper was to review the information on design principles, techniques, applications, methods, and outcomes adopted in the field of HCAI, in order to provide some insights on the discipline, in relation with the broader concepts of human-centered and user-centered design.
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist guidelines, we conducted a scoping review in PubMed, ScienceDirect, and IEEE Xplore, including all study types, excluding narrative reviews and editorials.
Out of the 1035 studies retrieved, 14 studies conducted between 2018 and 2023 met the inclusion criteria. The main fields of application were the health sector and AI applications. Human-centered design methodologies were adopted in 3 studies, personas in 2 studies, while the remaining methodologies were adopted in individual studies.
HCAI emphasizes designing AI systems that prioritize human needs, satisfaction, and trustworthiness, but current principles and guidelines are often vague and difficult to implement. The review highlights the importance of involving users early in the development process to enhance trust, especially in fields like health care, but notes that there is a lack of standardized HCAI methodologies and limited practical applications adhering to these principles.
随着人工智能（AI）应用的迅速扩展，研究人员已开始关注以人为本的人工智能（HCAI）概念。该领域致力于设计增强和改善人类能力而非替代人类能力的人工智能系统。
本文的目的是回顾HCAI领域所采用的设计原则、技术、应用、方法和成果方面的信息，以便结合以人为本和以用户为中心设计的更广泛概念，对该学科提供一些见解。
按照系统评价和Meta分析扩展版的范围综述优先报告条目（PRISMA-ScR）清单指南，我们在PubMed、ScienceDirect和IEEE Xplore中进行了范围综述，纳入所有研究类型，排除叙述性综述和社论。
在检索到的1035项研究中，2018年至2023年间进行的14项研究符合纳入标准。主要应用领域是卫生部门和人工智能应用。3项研究采用了以人为本的设计方法，2项研究采用了人物角色方法，其余方法则在个别研究中采用。
HCAI强调设计优先考虑人类需求、满意度和可信度的人工智能系统，但当前的原则和指南往往模糊且难以实施。该综述强调了在开发过程早期让用户参与以增强信任的重要性，尤其是在医疗保健等领域，但指出缺乏标准化的HCAI方法，且遵循这些原则的实际应用有限。
