Are we preparing for a good AI society? A bibliometric review and research agenda

• Published in: Technological forecasting & social change Vol. 164; p. 120482
• Main Authors: Fosso Wamba, Samuel, Bawack, Ransome Epie, Guthrie, Cameron, Queiroz, Maciel M., Carillo, Kevin Daniel André
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.03.2021; Elsevier Science Ltd; Elsevier
• Subjects: Artificial intelligence; Bibliometrics; Economic crisis; Empowerment; Equality; Humanities and Social Sciences; Impact analysis; Incentives; Infrastructure; Knowledge structure; Social change; Social impact; Social innovation; Social security; Society; Verification; Bibliometrics; Artificial intelligence; Social innovation; Social change; Knowledge structure
• ISSN: 0040-1625; 1873-5509
• DOI: 10.1016/j.techfore.2020.120482

•Five themes characterize AI research today, none concern AI for social good.•Future AI research is predicted to be technical with a focus on image processing.•136 research questions are proposed to prepare for a “good” AI society. Artificial intelligence (AI) may be one of the most disruptive technologies of the 21st century, with the potential to transform every aspect of society. Preparing for a “good AI society” has become a hot topic, with growing public and scientific interest in the principles, policies, incentives, and ethical frameworks necessary for society to enjoy the benefits of AI while minimizing the risks associated with its use. However, despite the renewed interest in artificial intelligence, little is known of the direction in which AI scholarship is moving and whether the field is evolving towards the goal of building a “good AI society”. Based on a bibliometric analysis of 40147 documents retrieved from the Web of Science database, this study describes the intellectual, social, and conceptual structure of AI research. It provides 136 evidence-based research questions about how AI research can help understand the social changes brought about by AI and prepare for a “good AI society.” The research agenda is organized according to ten social impact domains identified from the literature, including crisis response, economic empowerment, educational challenges, environmental challenges, equality and inclusion, health and hunger, information verification and validation, infrastructure management, public and social sector management, security, and justice.