Fairness, Accuracy, Knowability, and Transparency in Artificial Intelligence: A Conceptual Quadrant

This chapter introduces this edited volume exploring the critical intersection of fairness, accuracy, knowability, and transparency in Artificial Intelligence (AI) regulation. It posits that technical AI deployment has outpaced legal frameworks meant to ensure safety, fundamental rights protection, and accountability. At the heart of this challenge is a conceptual quadrant that bridges the traditional divide between ethics (fairness and transparency) and epistemology (accuracy and knowability). This chapter outlines the three-part structure of this volume. Part I establishes the conceptual groundwork, reframing fairness as contingent upon the epistemic quality of decision-making procedures. Part II examines how these values are operationalized within frameworks like the EU’s AI Act (AIA), highlighting regulatory loopholes in remote biometric identification and transparency exceptions. Part III focuses on individual entitlements, exploring inter alia rights to explanation, and the protection of vulnerable groups in digital justice systems. Ultimately, this chapter argues that formal compliance with AI regulation is insufficient to safeguard fundamental rights. Ultimately, this chapter, and the edited volume it introduces, advocates for a structural governance framework capable of correcting power imbalances and protecting citizens, particularly the most vulnerable, from algorithmic opacity.