Risk, regulation, and governance: evaluating artificial intelligence across diverse application scenarios

Abstract Understanding the impact of Artificial intelligence (AI) systems, including general purpose AI (GPAI) systems, across varied risk profiles becomes imperative with their pervasive expansion. This study systematically examines AI implementations in environments categorised from minimal to high risk, emphasising the significance of tailored risk management strategies and ethical approaches. In our article we explore how different AI applications influence public health, safety, and security and outline the regulatory and ethical frameworks required to manage the impact effectively. Our analysis reveals distinct operational and ethical challenges AI systems face in high-risk scenarios, necessitating thorough oversight and strict regulatory compliance to mitigate potential adverse outcomes. Furthermore, AI applications in lower-risk contexts also require careful consideration of transparency and accountability to ensure ethical alignment and public trust. This paper adds to the current discussion about AI governance by providing a detailed overview of AI risk factors and mitigation strategies. It proposes a complex approach to AI regulation and attempts to serve as a valuable resource for policymakers, IT professionals, and stakeholders. The goal is to maximise the benefits of AI while protecting against its risks, thereby promoting the responsible development and lawful implementation of AI technologies.