Uncovering AI Governance Themes in EU Policies using BERTopic and Thematic Analysis

2025-09-16

AI Summary

The European Union’s AI governance faces fragmentation across policy instruments, with tensions in scope, regulatory stringency, and priority setting. This study employs a mixed-methods approach—integrating qualitative thematic analysis with BERTopic-based unsupervised topic modeling—to systematically examine key post-2018 policy documents, including the AI Act and the High-Level Expert Group’s (HLEG) Ethics Guidelines. Methodologically, it advances interpretability by coupling explainable quantitative topic modeling with rigorous policy hermeneutics, expanding textual coverage and deepening semantic insight. Results reveal a clear diachronic shift from principle-based ethics toward risk-based regulation: foundational HLEG values—such as transparency and human oversight—are institutionalized in the AI Act, yet the emphasis pivots to enforceability and high-risk AI system oversight. The study thus offers both a methodological framework and empirical evidence for assessing policy coherence, diagnosing regulatory gaps, and strengthening transnational AI governance coordination.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Humans and AI: Learning Human Values and Preferences
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• Responsible Web: Technology governance, policy, and regulations
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

The upsurge of policies and guidelines that aim to ensure Artificial Intelligence (AI) systems are safe and trustworthy has led to a fragmented landscape of AI governance. The European Union (EU) is a key actor in the development of such policies and guidelines. Its High-Level Expert Group (HLEG) issued an influential set of guidelines for trustworthy AI, followed in 2024 by the adoption of the EU AI Act. While the EU policies and guidelines are expected to be aligned, they may differ in their scope, areas of emphasis, degrees of normativity, and priorities in relation to AI. To gain a broad understanding of AI governance from the EU perspective, we leverage qualitative thematic analysis approaches to uncover prevalent themes in key EU documents, including the AI Act and the HLEG Ethics Guidelines. We further employ quantitative topic modelling approaches, specifically through the use of the BERTopic model, to enhance the results and increase the document sample to include EU AI policy documents published post-2018. We present a novel perspective on EU policies, tracking the evolution of its approach to addressing AI governance.

Problem

• Identifying AI governance themes in EU policies
• Analyzing alignment and differences in EU AI guidelines
• Tracking evolution of EU's AI governance approach

Innovation

• BERTopic model for topic modeling
• Thematic analysis of EU documents
• Combining qualitative and quantitative approaches