Framing the Human-Centered Artificial Intelligence Concepts and Methods: Scoping Review.

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

© Roberta Bevilacqua, Tania Bailoni, Elvira Maranesi, Giulio Amabili, Federico Barbarossa, Marta Ponzano, Michele Virgolesi, Teresa Rea, Maddalena Illario, Enrico Maria Piras, Matteo Lenge, Elisa Barbi, Garifallia Sakellariou. Originally published in JMIR Human Factors (https://humanfactors.jmir.org).