Artificial intelligence governance: Ethical considerations and implications for social responsibility

Abstract A number of articles are increasingly raising awareness on the different uses of artificial intelligence (AI) technologies for customers and businesses. Many authors discuss about their benefits and possible challenges. However, for the time being, there is still limited research focused on AI principles and regulatory guidelines for the developers of expert systems like machine learning (ML) and/or deep learning (DL) technologies. This research addresses this knowledge gap in the academic literature. The objectives of this contribution are threefold: (i) It describes AI governance frameworks that were put forward by technology conglomerates, policy makers and by intergovernmental organizations, (ii) It sheds light on the extant literature on ‘AI governance’ as well as on the intersection of ‘AI’ and ‘corporate social responsibility’ (CSR), (iii) It identifies key dimensions of AI governance, and elaborates about the promotion of accountability and transparency; explainability, interpretability and reproducibility; fairness and inclusiveness; privacy and safety of end users, as well as on the prevention of risks and of cyber security issues from AI systems. This research implies that all those who are involved in the research, development and maintenance of AI systems, have social and ethical responsibilities to bear toward their consumers as well as to other stakeholders in society.