Developing a conceptual framework for identifying the ethical repercussions of artificial intelligence: A mixed method analysis

Abstract

Given that the topic of artificial intelligence (AI) ethics is novel, and many studies are emerging to uncover AI’s ethical challenges, the current study aims to analyse and visualise the research patterns and influential elements in this field. This paper analyses 1,646 Scopus-indexed publications using bibliometric analysis and cluster content analysis. To classify the most prominent elements and delineate the intellectual framework as well as the emerging patterns and gaps, we utilised keyword co-occurrence analysis and bibliographic coupling analysis and network visualisation of authors, countries, sources, documents and institutions. In particular, we detected nine major applications of AI in which ethics of AI is highly discussed, 24 ethical categories and 66 ethical concerns. Using the VOSviewer software, we also identified the general ethical concerns with the greatest total link strength regardless of their cluster associations. Then, focusing on the most recent articles (2020–21), we performed a cluster content analysis of the identified topic clusters and ethical concerns. This analysis guided us in detecting literature gaps and prospective topics and in developing a conceptual framework to illustrate a comprehensive image of ethical AI research trends. This study will assist policymakers, regulators, developers, engineers and researchers in better understanding AI’s ethical challenges and identifying the most pressing concerns that need to be tackled.