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Accepted for/Published in: JMIR Human Factors

Date Submitted: Oct 9, 2024
Date Accepted: Mar 17, 2025

The final, peer-reviewed published version of this preprint can be found here:

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

Bevilacqua R, Bailoni T, Maranesi E, Amabili G, Barbarossa F, Ponzano M, Virgolesi M, Rea T, Illario M, Piras EM, Lenge M, Barbi E, Sakellariou G

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

JMIR Hum Factors 2025;12:e67350

DOI: 10.2196/67350

PMID: 40435517

PMCID: 12136509

Framing the Human-Centered Artificial Intelligence concepts and methods: a scoping review

  • 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

ABSTRACT

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 is 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 Design and User-centered design.

Methods:

Following the PRISMA Checklist Extension guidelines, we conducted a systematic review in PubMed, Sciencedirect and IEEE Xplore, including all study types, excluding scoping review 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 artificial intelligence applications. Human-centred design methodologies were adopted in 3 studies, personas in 2 studies, while the remaining methodologies were adopted in individual studies.

Conclusions:

Human-Centered Artificial Intelligence (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 healthcare, but notes that there is a lack of standardized HCAI methodologies and limited practical applications adhering to these principles. Clinical Trial: N/A


 Citation

Please cite as:

Bevilacqua R, Bailoni T, Maranesi E, Amabili G, Barbarossa F, Ponzano M, Virgolesi M, Rea T, Illario M, Piras EM, Lenge M, Barbi E, Sakellariou G

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

JMIR Hum Factors 2025;12:e67350

DOI: 10.2196/67350

PMID: 40435517

PMCID: 12136509

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