Khan, Arif Ali and Badshah, Sher and Liang, Peng and Waseem, Muhammad and Khan, Bilal and Ahmad, Aakash and Fahmideh, Mahdi and Niazi, Mahmood and Akbar, Muhammad Azeem (2022) Ethics of AI : A Systematic Literature Review of Principles and Challenges. In: Proceedings of the ACM International Conference on Evaluation and Assessment in Software Engineering, EASE 2022 :. ACM International Conference Proceeding Series . The Association for Computing Machinery, SWE, pp. 383-392. ISBN 9781450396134
Full text not available from this repository.Abstract
Ethics in AI becomes a global topic of interest for both policymakers and academic researchers. In the last few years, various research organizations, lawyers, think tankers, and regulatory bodies get involved in developing AI ethics guidelines and principles. However, there is still debate about the implications of these principles. We conducted a systematic literature review (SLR) study to investigate the agreement on the significance of AI principles and identify the challenging factors that could negatively impact the adoption of AI ethics principles. The results reveal that the global convergence set consists of 22 ethical principles and 15 challenges. Transparency, privacy, accountability and fairness are identified as the most common AI ethics principles. Similarly, lack of ethical knowledge and vague principles are reported as the significant challenges for considering ethics in AI. The findings of this study are the preliminary inputs for proposing a maturity model that assesses the ethical capabilities of AI systems and provides best practices for further improvements.