Deciphering Ethics and Privacy in Artificial Intelligence Through Bibliometric

Abstract

This study offers a bibliometric review of AI ethics and privacy research, with a focus on trends, topics, and deficiencies. Employing citation, co-citation, and keyword analysis, it reveals significant topics like algorithmic bias, transparency, and data privacy. These issues received moderate concern from 71 participants, and the results showed the correlations between transparency, data protection, and ethical guidelines are significant. Thus, ANOVA results reveal the significance of these predictors for privacy perceptions. The study also points out that the field of AI ethics research is dynamic and identifies potential trajectories for research.