Decision Problems for Regulatees under the EU AI Act: Contested Values, Uncertain Evidence, and the Limits of Standardisation

Abstract

Based on the New Legislative Framework (NLF) approach, the AI Act relies on harmonised standards to provide technical specifications for the implementation of its essential requirements for high-risk AI systems. This paper argues that these requirements pose fundamental “decision problems” for regulatees, requiring value judgments and evidence assessment under uncertainty for their implementation. Unlike mature NLF fields with established methodologies and value consensus, the AI domain is characterised by contested values and uncertain evidence, significantly limiting the ability of traditional standardisation to provide clear, universally applicable solutions. This creates uncertainty for regulatees, complicates conformity assessment and enforcement, and risks undermining the overall regulatory effectiveness of the AI Act. In response to these challenges, this paper proposes supplementing standardisation with a procedural approach, such as documented “AI Act Compliance Cases,” to compel transparent articulation and justification of regulatees’ decisions. This enhances auditability and manageability, bolstering the Act’s capacity to achieve its health, safety and fundamental rights objectives despite inherent complexities.