AI Ethics: Frameworks, Principles, and Future Directions

As artificial intelligence (AI) is increasingly becoming a part of our everyday lives, the discussion of AI ethics has become a pressing global concern. AI ethics is a multidisciplinary field that establishes a set of guiding principles and frameworks to ensure the responsible development, deployment, and use of AI technology. It seeks to optimize the beneficial impacts of AI while actively reducing risks and adverse outcomes. As AI systems become more integrated into our daily lives, influencing everything from healthcare and finance to criminal justice and social media, the importance of these ethical considerations requires serious attention to mitigating risks, building trust, ensuring societal wellbeing, and shaping the future, among others. Based on a review of the literature, we have identified ten AI ethics frameworks, with each framework building around a set of core principles. The frameworks are data responsibility, accountability, data privacy, fairness, explainability, transparency, robustness, moral agency, value alignment, and technology misuse. We will discuss these frameworks with their core principles and set an agenda for future research and direction.