TY - JOUR
T1 - Democratizing Artificial Intelligence for Social Good: A Bibliometric–Systematic Review Through a Social Science Lens
AU - Chan, Chitat
AU - Nurrosyidah, Afifah
N1 - This research and the APC was funded by an internal grant from Hong Kong Baptist University; project number RC-FNRA-IG/23-24/SOSC/02.
Publisher Copyright:
© 2025 by the authors.
PY - 2025/1/10
Y1 - 2025/1/10
N2 - This study provides a comprehensive analysis of the opportunities for democratizing artificial intelligence (AI) for social good using a bibliometric–systematic literature review method. It combines the quantitative analysis of bibliometric methods with the qualitative synthesis of systematic reviews. This approach helps identify patterns, trends, and gaps in the literature, advancing theoretical insights and mapping future research directions. Design/methodology/approach: Scopus, PubMed, and Web of Science, as prominent scientific databases, were utilized to examine publications between 2014 and 2024. The article selection followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The bibliometric analysis was conducted using CiteSpace software. Findings: The bibliometric analysis identified the most influential articles, journals, countries, authors, and key themes. The systematic thematic analysis identified established modes of using AI for social good. Moreover, future research directions are suggested and discussed in this article. Practical implications: The findings give future research directions and guidance to academics, practitioners, and policymakers for real-world applications.
AB - This study provides a comprehensive analysis of the opportunities for democratizing artificial intelligence (AI) for social good using a bibliometric–systematic literature review method. It combines the quantitative analysis of bibliometric methods with the qualitative synthesis of systematic reviews. This approach helps identify patterns, trends, and gaps in the literature, advancing theoretical insights and mapping future research directions. Design/methodology/approach: Scopus, PubMed, and Web of Science, as prominent scientific databases, were utilized to examine publications between 2014 and 2024. The article selection followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The bibliometric analysis was conducted using CiteSpace software. Findings: The bibliometric analysis identified the most influential articles, journals, countries, authors, and key themes. The systematic thematic analysis identified established modes of using AI for social good. Moreover, future research directions are suggested and discussed in this article. Practical implications: The findings give future research directions and guidance to academics, practitioners, and policymakers for real-world applications.
KW - AI
KW - social good
KW - democratization
KW - bibliometric analysis
KW - systematic review
UR - https://www.mdpi.com/2076-0760/14/1/30
U2 - 10.3390/socsci14010030
DO - 10.3390/socsci14010030
M3 - Review article
SN - 2076-0760
VL - 14
JO - Social Sciences
JF - Social Sciences
IS - 1
M1 - 30
ER -