Publications

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Critics raise alarm bells about governmental use of digital algorithms, charging that they are too complex, inscrutable, and prone to bias. A realistic assessment of digital algorithms, though, must acknowledge that government is already driven by algorithms of arguably greater complexity and potential for abuse: the algorithms implicit in human decision-making. The human brain operates algorithmically through complex neural networks. And when humans make collective decisions, they operate via algorithms too—those reflected in legislative, judicial, and administrative processes. Yet these human algorithms undeniably fail and are far from transparent. On an individual level, human decision-making suffers from memory limitations, fatigue, cognitive biases, and racial prejudices, among other problems. On an organizational level, humans succumb to groupthink and free-riding, along with other collective dysfunctionalities. As a result, human decisions will in some cases prove far more problematic than their digital counterparts. Digital algorithms, such as machine learning, can improve governmental performance by facilitating outcomes that are more accurate, timely, and consistent. Still, when deciding whether to deploy digital algorithms to perform tasks currently completed by humans, public officials should proceed with care on a case-by-case basis. They should consider both whether a particular use would satisfy the basic preconditions for successful machine learning and whether it would in fact lead to demonstrable improvements over the status quo. The question about the future of public administration is not whether digital algorithms are perfect. Rather, it is a question about what will work better: human algorithms or digital ones.

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A growing body of literature discusses the impact of machine-learning algorithms on regulatory processes. This paper contributes to the predomi-nantly legal and technological literature by using a sociological-institutional perspective to identify nine organisational challenges for using algorithms in regulatory practice. Firstly, this paper identifies three forms of algorithms and regulation: regulation of algorithms, regulation through algorithms, and regulation of algorithms through algorithms. Secondly, we identify nine organisational challenges for regulation of and through algorithms based on literature analysis and empirical examples from Dutch regulatory agencies. Finally, we indicate what kind of institutional work regulatory agencies need to carry out to overcome the challenges and to develop an algorithmic regu-latory practice, which calls for future empirical research.

Better regulation is an agenda aiming at managing legislation across the different stages of the policy cycle. At the EU level, this agenda for reform has been handled as soft law with communications, reports, principles, and toolboxes. The ambiguity of the concept has created a policy arena where the EU institutions jockey for positions on the control of the lawmaking process. We then turn to the Member States. For their better regulation policies, they have chosen a combination of soft and hard instruments and different degrees of formalization. Tellingly, this variation shows the different views and assumptions on the efficiency of soft law as well as of the role played by legal and administrative traditions.

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A cura di Gabriele Mazzantini e Laura Tafani

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The objective of the foresight process was to look at Open Strategic Autonomy in a systematic and systemic way, encompassing different dimensions and look at them in a holistic manner. This report is part of the 2021 European Commission Strategic Foresight Agenda. Desk research, including literature review and policy analysis, synthetises existing knowledge on the current state and future possibilities in 2040 and beyond. The report presents an overview of Europe’s existing capacities, dependencies and vulnerabilities. It also describes trends and emerging issues, looking forward at how they could evolve over time, and looking at the opportunities and risks they entail. The report highlights ways the EU can start to seize the benefits from positive developments and ways to transform risks into potential for positive transformation.This report presents foresight scenarios on the global standing of the EU in 2040, in relation to Open Strategic Autonomy. They point to ways for the EU to build preparedness through anticipation. A Delphi enquiry enabled the engagement of experts who assessed and ranked the identified 'forward-looking issues' in terms of their relevance for shaping and securing the EU’s Open Strategic Autonomy towards 2040.Finally, we outline implications for leveraging the EU’s capacity to implement an Open Strategic Autonomy by 2040 and beyond. We highlight the ways in which the EU can use its existing strengths and develop further capacities, both by itself and through alliances. We address current weaknesses and upcoming challenges, point to ways of seizing underlying opportunities, and implementing identified priorities required to shape and guarantee Open Strategic Autonomy. The implications outlined should be considered as a set, as in this way they can ensure establishing a coherent policy framework.