Publications

This paper explores how EU competition law enforcement might be affected by the COVID-19 pandemic. Each section of this paper reviews how various components of EU competition law are impacted. The paper evaluates the state of play and, where relevant, it makes policy proposals for how competition law might develop. It suggests that the Commission’s state aid policy is unprecedentedly lax but more tightening up might be welcomed to ensure state funds are not misspent. In the field of antitrust it recommends that competition authorities should be watchful of excessive prices and price discrimination, using interim measures more boldly. Collusion should remain an enforcement priority but a procedural pathway to review agreements that may be in the public interest is proposed, drawing on practices developed in the US in the aftermath of major natural disasters. In merger control, the Commission’s strict interpretation of the failing firm defense is appropriate but, in general, a more skeptical attitude towards mergers may be warranted during this period. Advocacy plays a key role: competition agencies can both point to existing regulations that limit competition and monitor proposed emergency legislation that would harm competition for no good reason.

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COVID-19 represents not only one of the greatest natural and economic disasters in human history, but also a rich case study of government’s emergency response. As such, it is a test bed for risk research and regulatory theories in a world increasingly shaped by transboundary, uncertain manufactured and natural risks. While it is obviously too early to come to definitive conclusions, the contributions collected – in record-time – in this special issue of the European Journal of Risk Regulation attempt at providing an initial analysis of the surprisingly uncoordinated, at times unscientific, response to an essentially foreseeable event like a novel coronavirus (nCoV) in a geopolitically shattered world.

Complex machine learning models derived from personal data are increasingly used in making decisions important to peoples’ lives. These automated decision tools are controversial, in part because their operation is difficult for humans to grasp or explain. While scholars and policymakers have begun grappling with these explainability concerns, the debate has focused on explanations to decision subjects. This Essay argues that explainability has equally important normative and practical ramifications for decision-system design. Automated decision tools are particularly attractive when decisionmaking responsibility is delegated and distributed across multiple actors to handle large numbers of cases. Such decision systems depend on explanatory flows among those responsible for setting goals, developing decision criteria, and applying those criteria to particular cases. Inscrutable automated decision tools can disrupt all of these flows. This Essay focuses on explanation’s role in decision-criteria development, which it analogizes to rulemaking. It analyzes whether, and how, decision tool inscrutability undermines the traditional functions of explanation in rulemaking. It concludes that providing information about the many aspects of decision tool design, function, and use that can be explained can perform many of those traditional functions. Nonetheless, the technical inscrutability of machine learning models has significant ramifications for some decision contexts. Decision tool inscrutability makes it harder, for example, to assess whether decision criteria will generalize to unusual cases or new situations and heightens communication and coordination barriers between data scientists and subject matter experts. The Essay concludes with some suggested approaches for facilitating explanatory flows for decision-system design.

The Committee on Standards in Public Life has recently published (February 2020) a review on ‘Artificial Intelligence and Public Standards’. Chaired by Lord Evans of Weardale KCB DL, the report takes a thorough look at the use of AI in public service through the framework of the Nolan Principles (Selflessness, Integrity, Objectivity, Accountability, Openness, Honestly, and Leadership). This paper briefly comments upon and analyses selections form the publication by surveying the recommendations.

The EU Commission regularly consults with external actors when preparing policy proposals. This paper investigates possible bias in the voices the Commission listens to across all policy areas and consultation instruments. We map the full range of consultation instruments used by the Commission and analyse variation in group representation across types of consultations and policy areas. Our analysis draws on a dataset of more than 350 major Commission proposals between 2011 and 2016. We find that the Commission has established a consultation regime with the widespread use of standard consultation instruments, including open online consultations, stakeholder conferences and consultation in closed fora. The range of consulted actors depends on both consultation instruments and policy types. Open online-consultations are most inclusive. Our findings indicate that the Commission may be able to counteract the influence of business by selecting the most appropriate format for consultation.

Behavioural insights (BI) has become widely used by public bodies around the world, mostly towards improving the way policies are implemented and influencing individual behaviour. As the field of BI evolves to tackle more complex policy issues, there is widespread perception that BI can and should go beyond the study of individual-level decision processes for higher impact. This report presents research on applying BI to changing the behaviour of organisations, with a focus on fostering elements of a safety culture in the energy sector. It presents comparative findings from experiments with energy regulators in Canada, Ireland, Mexico and Oman, as well as guidance for applying BI to safety culture going forward.

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