# High-Risk AI Systems and the Problem of Identity in the European AI Act

arXiv: https://arxiv.org/abs/2605.23922 · HTML: https://mlsanity.com/paper/2605.23922/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 40 references that are in the map.
- First posted on arXiv 17 Apr 2026.

## Builds on (most cited first, 12 of 12)

- [Role-Play with Large Language Models](https://mlsanity.com/paper/2305.16367/) (2023)
- [Trustworthy AI: From Principles to Practices](https://mlsanity.com/paper/2110.01167/) (2021)
- [Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI](https://mlsanity.com/paper/2010.07487/) (2020)
- [Auditing large language models: a three-layered approach](https://mlsanity.com/paper/2302.08500/) (2023)
- [Towards a Science of AI Agent Reliability](https://mlsanity.com/paper/2602.16666/) (2026)
- [Ethics-Based Auditing to Develop Trustworthy AI](https://mlsanity.com/paper/2105.00002/) (2021)
- [Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulation](https://mlsanity.com/paper/2111.05071/) (2021)
- [Robustness and Cybersecurity in the EU Artificial Intelligence Act](https://mlsanity.com/paper/2502.16184/) (2025)
- [A Trustworthiness-based Metaphysics of Artificial Intelligence Systems](https://mlsanity.com/paper/2506.03233/) (2025)
- [A Blueprint for Auditing Generative AI](https://mlsanity.com/paper/2407.05338/) (2024)
- [The E.U.'s Artificial Intelligence Act: An Ordoliberal Assessment](https://mlsanity.com/paper/2309.12336/) (2023)
- [A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents](https://mlsanity.com/paper/2601.09869/) (2026)

## Built on by (most cited first, 4 of 4)

- [A Category Theory Account of AI Identity](https://mlsanity.com/paper/2607.00220/) (2026)
- [Update Opacity: Epistemic Accessibility and Governance Under AI System Change](https://mlsanity.com/paper/2606.00037/) (2026)
- [A Methodology for Auditable Trustworthiness Levels in AI Lifecycle Governance](https://mlsanity.com/paper/2607.16130/) (2026)
- [Operational Identity: A Finite Audit of Declared and Implemented Rules of Sameness](https://mlsanity.com/paper/2607.20729/) (2026)

## Abstract (arXiv)

The EU Artificial Intelligence Act (AIA) establishes a lifecycle governance regime for high-risk AI systems built around ex-ante conformity assessment, post-market monitoring, and re-assessment upon "substantial modification." These obligations presuppose AI identity judgments: regulators and providers must decide when an updated system remains the same system over time. In this work, we show how this logic is clarified by the function+ framework of artifact identity, which individuates AI systems by their intended function together with context-sensitive criteria of appropriate functioning, captured as "AI trustworthiness." We further argue that the AIA does not provide an internal, auditable criterion for synchronic identity--when two AI systems at a given time should count as the same for regulatory purposes--and instead largely defers such sameness determinations to sectoral or harmonization instruments. function+ supplies a synchronic identity test anchored in intended function and trustworthiness profiles and levels, making synchronic identity decisions inspectable in governance settings such as procurement, liability, and market surveillance. Our contribution is a conceptual and auditing lens: we provide a correspondence map between AIA lifecycle obligations and function+ identity components, and we make the synchronic case operationally legible via a minimal decision flow for audit and dispute contexts. We conclude with two implementation-facing recommendations: (1) more precise, testable reporting of intended purpose, and (2) standardized, auditable trustworthiness reporting that supports comparability over time and across deployments.