Assessing AI Algorithms

As AI increasingly shapes decision-making across industries, assessing the algorithms that power these systems are essential for ensuring transparency, fairness, accountability, and ethical compliance. This chapter explores a comprehensive methodology for evaluating AI algorithms, aligning with international standards such as the IEEE CertifAIEd Certification Framework. Drawing on real-world applications, assessor experiences, and organizational case studies, it addresses the critical components of ethical AI assessment—including algorithmic bias detection, transparency mechanisms, explainability, governance policies, and Red Teaming practices. The chapter outlines the best practices, practical frameworks, and implementation steps for organizations seeking certification or developing internal AI oversight. It emphasizes the role of assessors and the necessary skills to evaluate the trustworthiness and societal impact of intelligent systems in diverse domains such as healthcare, finance, and public services.