AI Risk Management

As organizations increasingly rely on AI for critical decision-making and incorporate it into different areas of their businesses, effective AI risk management should be a top priority. Ensuring the safe and compliant deployment of ML systems is essential to establish trustworthiness in AI solutions. However, many organizations and individuals have very limited understanding of the risks associated with AI systems, often resulting in outcomes that may negatively impact organizations financially or legally. In this chapter, we will explore key AI risk scenarios, highlight the differences between AI risk management and traditional software risk management, and emphasize the importance of having a robust AI risk management practice. We will present a risk management framework that organizations can consider for managing AI risks. Finally, we will discuss how to manage risks at different stages of the ML lifecycle and design ML platforms that support risk management...