The rapid development of generative artificial intelligence (GenAI) is widely expected to transform professional practices across multiple sectors, including the legal profession. This article critically examines the growing integration of GenAI tools into legal work and the implications this development carries for professional competence, ethical responsibility, and the broader institutional structure of legal practice. While AI promises substantial gains in efficiency by automating tasks such as legal research, document drafting, information retrieval, and data analysis, their adoption also raises significant concerns regarding reliability, transparency, confidentiality, and professional accountability. While prevailing narratives surrounding AI adoption in law often frame technological integration as both inevitable and normatively desirable, emphasising efficiency and competitive advantage while downplaying potential risks and value conflicts, the increasing delegation of professional tasks to algorithmic systems challenges traditional understandings of legal expertise, particularly in relation to judgement, reasoning, and professional autonomy. Moreover, unequal access to advanced AI tools and proprietary datasets may reinforce structural inequalities within the legal market, benefitting larger firms while disadvantaging smaller practices. This article argues for a balanced approach that combines technological literacy with strong ethical frameworks and institutional safeguards. Ultimately, responsible integration of GenAI requires sustained human oversight and collective professional engagement to ensure that technological innovation supports, rather than undermines, the core values of legal practice.
The advent of AI in EU regulatory science is a litmus test for transparency. This article examines how EFSA and EMA are responding. It is argued that both agencies are subject to stringent safeguards for AI transparency. However, these lie in the guarantees developed around their scientific assessments (i.e., the logic of Regulatory Science Transparency), rather than in the AI Act. From the vantage point of Regulatory Science Transparency, expert accountability and legitimacy, EFSA’s and EMA’s emerging approaches to AI transparency yield mixed results: only EFSA’s response holds out the prospect for robust democratic governance in the age of AI.
This article examines whether the European Union (EU) should consider menopause as a workplace issue, drawing lessons from the United Kingdom (UK). It finds that existing UK equality laws provide fragmented protection, requiring menopause-related claims to be framed through sex, age or disability discrimination, often with significant difficulties. Although the recently introduced UK’s Equality (Menopause) Action Plans significantly raise the profile of menopause in the workplace, requiring employers to take actions to support those who experience menopause, they confer no individual rights and risk inconsistent application. The article concludes that menopause is a workplace gender equality issue requiring coordinated EU action, including data collection, employer guidance, awareness-raising and the exchange of best practice.
Considering the biodiversity and climate crises, an upscaling of ecosystem restoration has come to the forefront of international and European policies. Although restoration obligations are present in existing EU law, such as the Birds and Habitats Directives, a more concrete and detailed legal framework was necessary. The Nature Restoration Regulation (NRR) adopted in 2024 provides such a framework and is a pioneer law for pro-active positive restoration obligations. The NRR does not replace existing legislation, but complements it, including through, among others, providing definitions, concrete targets and deadlines, restoration obligations outside Natura 2000 and the implementation through national restoration plans.
The article examines the relationship between the European Union’s Artificial Intelligence Act (AI Act) and the General Data Protection Regulation (GDPR), focusing in particular on the role of regulatory sandboxes as instruments for fostering innovation while safeguarding fundamental rights. The data-intensive nature of contemporary AI systems creates inherent tensions with core GDPR principles, such as purpose limitation, data minimisation, and the protection of data subject rights. Against this background, the article addresses three key questions: how the sandbox provisions of the AI Act should be reconciled with the GDPR; whether these provisions operate as lex specialis or rather as a contextual clarification of existing rules; and whether regulatory sandboxes can achieve a meaningful balance between innovation and data protection. The analysis shows that, if properly designed, sandboxes can support trustworthy AI through a cooperative and proportionate regulatory approach.
