This paper traces the legislative process of the EU Artificial Intelligence Act (AI Act) to provide an empirical and critical account of the choices made in its formation. It specifically focuses on the dynamics that led to increasing or lowering fundamental rights protection in the final text and their implications for fundamental rights. Adopting process-tracing methods, the paper sheds light on the institutional differences and agreements behind this landmark legislation. It then analyses the implications of political compromise for fundamental rights protection. The core message it aims to convey is to read the AI Act with its institutional setting and political context in mind. As this paper shows, the different policy aims and mandates of the three EU institutions, compounded by the unprecedented level of redrafting and the short time needed to reach a political agreement, influenced the formulation of the AI Act. Looking forward, the paper points to the role of implementation, enforcement and judicial interpretation in enhancing the protection of fundamental rights in the age of AI.

The Paper aims to explore whether the current ecosystem of existing and still-to-be adopted rules on artificial intelligence (AI) systems in the European Union does fully and adequately address the liability for damages caused by Generative AI system. It maps first and primarily the distinctive features and functional characteristics of Generative AI likely to impact on regulatory and legal considerations and, in particular, on determining the specific regulatory regime governing Generative AI and on tracing and allocating liability along the value chain pursuant to the AI Act. On the basis of this mapping exercise, the Paper focuses on testing the liability rules as provided for the draft Artificial Intelligence Liability Directive and the Revised Product Liability Directive and assessing their sufficiency and effectiveness in the face of Generative AI. Beyond the assessment of the rules laid down in the above-referred texts, the Paper briefly describes other liability scenarios to be explored in future works.

The paper examines the legal regulation and governance of “generative artificial intelligence” (AI), “foundation AI,” “large language models” (LLMs), and the “general-purpose” AI models of the AI Act. Attention is drawn to two potential sorcerer’s apprentices, namely, in the spirit of J. W. Goethe’s poem, people who were unable to control a situation they created. Focus is on developers and producers of technologies, such as LLMs that bring about risks of discrimination and information hazards, malicious uses and environmental harms; furthermore, the analysis dwells on the normative attempt of European Union legislators to govern misuses and overuses of LLMs with the AI Act. Scholars, private companies, and organisations have stressed limits of such normative attempt. In addition to issues of competitiveness and legal certainty, bureaucratic burdens and standard development, the threat is the over-frequent revision of the law to tackle advancements of technology. The paper illustrates this threat since the inception of the AI Act and recommends some ways in which the law has not to be continuously amended to address the challenges of technological innovation.

In May 2024, the European Union adopted the Directive on violence against women and domestic violence, marking the first EU-wide binding legislation to address various forms of sexualized and gendered harm. This Article provides the first comprehensive analysis of the Directive’s provisions on image-based sexual abuse (“IBSA”), encompassing the non-consensual taking, creating, and sharing of intimate materials, as well as threats to distribute them. While acknowledging the aim to harmonize legislation at the Union level, the Article identifies a range of limitations and the failure to fully reflect the diverse experiences of victims. Additionally, the Article evaluates the complementary roles in combating IBSA of the Digital Services Act and the AI Act which impose obligations on online platforms, search engines, and AI developers. Overall, the current EU framework represents a promising but partial approach. If the EU is to comprehensively address IBSA and safeguard victims’ rights, implementation beyond the minimum will be required together with proactive, effective regulation.

The Artificial Intelligence Act (AI Act) of the European Union (EU) claims to be based on a risk-based approach to avoid over-regulation and to respect the principle of legislative proportionality. This paper argues that risk-based regulation is indeed the right approach to AI regulation. At the same time, however, the paper shows that important provisions of the AI Act do not follow a truly risk-based approach. Yet, this is nothing that cannot be fixed. The AI Act provides for sufficient tools to support future-proof legislation and to implement it in line with a genuine risk-based approach. Against this background, the paper analyses how the AI Act should be applied and implemented according to its original intention of a risk-based approach, and what lessons legislators around the world can learn from the AI Act in regulating AI.

The analysis of liability aspects facing Artificial Intelligence (‘AI’)-generated outputs under copyright and related rights has been overlooked compared to other issues connected to the development and use of AI. This study fills this gap by exploring pertinent questions under international, EU and UK law. Specifically, the study tackles actionable reproduction, allocation of liability, and availability of defences. The analysis ultimately shows that, while it is clear that each case will need to be decided on its own merits, the generative AI output phase raises several profiles of liability under copyright law. If the goal of policymakers and relevant stakeholders is to ensure the balanced and sustainable development of AI, then the issues related to the generation and dissemination of AI outputs need to be given ample attention and a greater role in the debate than what has been the case so far, whether it is in the context of risk assessment and compliance, licensing initiatives, or in contentious scenarios.

Regulation is nothing without enforcement. This particularly holds for the dynamic field of emerging technologies. Hence, this article has two ambitions. First, it explains how the EU’s new Artificial Intelligence Act (AIA) may be implemented and enforced by various institutional bodies, thus clarifying the governance framework of the AIA. Second, it proposes a normative governance model, providing recommendations to ensure uniform and coordinated execution of the AIA and the fulfillment of the legislation. The article explores how the AIA may be implemented by national and EU institutional bodies, encompassing longstanding bodies, such as the European Commission, and those newly established under the AIA, such as the AI Office. It investigates their roles across supranational and national levels, emphasising how EU regulations influence institutional structures and operations. These regulations may not only directly dictate the structural design of institutions but also indirectly request administrative capacities needed to enforce the AIA.

This Article explores the implications of Artificial Intelligence (AI)-driven innovation across sectors, highlighting the resulting legal uncertainties. Despite the transformative influence of AI in healthcare, retail, finance and more, regulatory responses to these developments are often contradictory, contributing to the opacity of the legal underpinnings of AI business. Our Article notes the common trend of commercializing AI tools amidst legal uncertainty, using innovative contractual solutions to secure claims. Over time, these innovations trigger overlooked legal conflicts, sometimes leading to outright bans on AI products due to negative impacts on some fundamental rights and democratic Governance. The core argument of our Article is that an over-reliance on co-regulatory strategies, such as those proposed by the European AI Act, exacerbates legal instability in emerging technological markets. This panorama creates an ’extended legal present’ when alternative legal expectations coexist, thus causing economic and political uncertainty that may elicit legal instability in the future. The concept of ’competing legal futures’ is introduced to illustrate how economic actors must bet on a legal future in the absence of guarantees that this future will materialize. To help analyze this complex narrative, we propose a theoretical framework for understanding legal, technological, and economic dynamics, highlighting anomalies in market exchanges within the co-regulatory model. Despite the focus on European developments, the practical and theoretical implications extend beyond the EU, making the Article relevant to a broader understanding of the legal-economic challenges posed by AI and digital innovation. We conclude by arguing for a course correction, proposing institutional diversification for resilient governance of legal innovation under uncertainty.

This Article addresses the pressing issues surrounding the use of automated systems in public decision-making, specifically focusing on migration, asylum, and mobility. Drawing on empirical data, this Article examines the potential and limitations of the General Data Protection Regulation and the Artificial Intelligence Act in effectively addressing the challenges posed by automated decision-making (ADM). The Article argues that the current legal definitions and categorizations of ADM fail to capture the complexity and diversity of real-life applications where automated systems assist human decision-makers rather than replace them entirely. To bridge the gap between ADM in law and practice, this Article proposes to move beyond the concept of “automated decisions” and complement the legal protection in the GDPR and AI Act with a taxonomy that can inform a fundamental rights analysis. This taxonomy enhances our understanding of ADM and allows to identify the fundamental rights at stake and the sector-specific legislation applicable to ADM. The Article calls for empirical observations and input from experts in other areas of public law to enrich and refine the proposed taxonomy, thus ensuring clearer conceptual frameworks to safeguard individuals in our increasingly algorithmic society.