ABSTRACT Reimagining State Aid argues that Article 107 TFEU no longer describes what State aid control does and proposes amendments to recalibrate and narrow the notion of aid, modernise the compatibility grounds and expressly ground Commission frameworks in Article 108. This comment shares the diagnosis but disputes its cause, and thus the cure. The Union has assumed industrial objectives without a consolidated competence or commensurate fiscal resources, and compatibility control has become the path of least political resistance as it attaches common conditions to national expenditure without resolving broader political or budgetary conflicts. That account changes the reform question. Articles 107(3), 108 and 109 TFEU already permit considerable adaptation and steering, whereas narrowing Article 107(1) would weaken the jurisdiction through which national spending is coordinated. Reform should instead strengthen framework‐level evidence and evaluation, make European additionality testable, connect common objectives to Union co‐financing and derisking and choose more deliberately among nonfiscal industrial policy instruments.
EU state aid law has shifted fundamentally from an originally purely repressive tool to a proactive steering mechanism for critical EU goals today. This paper argues that the current legal framework in Article 107 TFEU is gravely misaligned with this new function. The paper outlines the novel challenges and contrasts them with current state aid law, exposing anachronism and systemic friction. In response, the paper proposes a systemic reform agenda that redefines the Treaty's notion of state aid to further strengthen its steering role, avoid overenforcement and align the regime more closely with the strategic orientations of the Letta Report.
This introductory article sets competition law in the transformative context. It explains that competition law is not only something that is transformed, but that is transformative in its own right. A twofold argument is advanced: first, that competition law has an important role to play in ensuring that the wide range of transitions in play today (i.e. green, digital and industrial) are both just and enduring, and second that there are significant lessons to be learnt from economic transformations that have already taken place in Central and Eastern European (CEE) countries and countries from the Global South. To this end, the article explains that the manner in which CEE and selected Global South countries designed and enforced their competition laws allowed competition law to play a meaningful role not only as an instrument but also as an architect of their economic transformations. Against this background, the EU's openness to these transitional experiences is desirable not only because it would supplement the transitions within the EU but also because it will facilitate the pathway to similar transitions in other non-European jurisdictions that look to the EU for guidance. In terms of structure, first, the article examines the role that competition law can play in the course of transitions. Second, it examines the possibilities and limitations of the role competition law has already played in the transitions in CEE and Global South countries. It ends by inviting everyone to read the articles in the collection to gain a deeper insight into these issues.
We argue that generative AI can degrade research by eroding the very practices through which scholarly judgement is formed and academic trust is built. As constitutive conditions for the production and validation of knowledge, these practices cannot be reduced to the final outputs of research, which is what AI so effectively simulate. Accordingly, when researchers delegate central tasks of inquiry to systems like Large Language Models, they may stop enacting these practices and, with them, lose access to the formation they provide. An individual research output generated by AI may even appear improved but the researcher behind it fails to develop. Against this risk, merely keeping humans in the loop as prompters or quality checkers of AI outputs is insufficient to preserve research as a site of intellectual formation. What is needed instead is a renewed commitment to research as a lived practice in which judgement is formed gradually, often through frictions, and participation in a scholarly community. We defend it because it rests on four sources and warrants of research that cannot be automated: tacit knowledge, personal commitment, socialisation, and deep reading. This practice enacts what we call second scholarship, by which we understand the reappropriation of scholarly craft, chosen out of a critical experience of what generative AI can and cannot do. What cannot and should not be delegated becomes what research communities must value and answer for. This is what is left for us.
