Information Ethics in Light of Bibliometric Analyses: Discovering a Shift to Ethics of Artificial Intelligence
Information Ethics in Light of Bibliometric Analyses: Discovering a Shift to Ethics of Artificial Intelligence

Summary/Abstract: The objectives of this study are to analyse the content of publications focused on the area of information ethics and discover patterns, knowledge and thematic trends. The main research question is: What is the intellectual and topical structure of the field of information ethics? We apply bibliometric analytical methods, including co-citation analysis (41 most cited authors out of 9947), co-word analysis (127 keywords), visualizations (maps) and analysis of time periods in strategic diagrams. These methods are interpreted with the use of previous content analyses and results of a Delphi study. The dataset covers publications between 1988 and 2023 collected from Web of Science using the search term “information ethics” in titles, keywords and abstracts (469 records). The study presents the research background and objectives, related research review, research methods and findings. Results are visualized in maps of topics and trends. We investigate the intellectual and thematic structure of information ethics, including numbers of publications, main disciplines, the intellectual structure (authors, topics, trends) and identify four time periods (1988-2005, 2006-2012, 2013-2019, 2020-2023) visualized by strategic diagrams. The study reveals the multidimensionality and multidisciplinary dynamic evolution of information ethics. The main trends are the topics of ethics of artificial intelligence and algorithms, data ethics, ethics of information literacy, informational privacy and dis/misinformation. We find that information ethics studies are embedded in wider contexts of the information crisis and design of public digital services. We propose education and information literacy courses related to ethical sensitivity, data ethics and the use of AI tools. The study contributes to bridging the gap between information ethics studies and human information interactions. Our results confirm the increasing interest in ethics of artificial intelligence.

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