AI governance and ethics framework for sustainable AI and sustainability

Abstract

This paper addresses the growing need for trustworthy artificial intelligence (AI) in research by integrating ethical AI principles with robust data governance practices. It introduces the Responsible Intelligence (RI) framework, which unifies key ethical AI factors such as fairness, transparency, accountability, safety, and inclusivity with critical data governance elements, including consent, privacy, data quality, equity, and responsible sharing. The framework spans the entire AI lifecycle, from data collection and processing to model development and deployment, offering a structured approach to ensure responsible AI use. By embedding these dual pillars, the RI framework fosters alignment with societal values and legal standards. It encourages interdisciplinary collaboration and institutional commitment, promoting systems that are not only efficient and innovative but also ethically grounded, reliable, and aligned with public trust in scientific research.