Publications

Scholars have identified various regulatory barriers hampering responses to the COVID-19 pandemic. For example, the regulatory approval required for drugs and medical devices has created “bottlenecks” for expanding the capacity of virus testing, ambiguous and often changing regulations “have served as hindrances” to the increasing use of telehealth, and patients have limited access to mobile narcotic treatment due to regulatory bans. Do these criticisms reflect the public’s opinion toward regulation, and how did average public sentiment evolve with the spread of COVID-19? This article explores these questions by presenting a text-based sentiment analysis of news articles related to COVID-19 and regulation. The analysis shows that the expression about regulation in the COVID-related news was negative in most days during the beginning of the virus outbreak, but it started to improve in mid-March. The improvement may suggest increased public confidence in regulatory responses to the pandemic, as the government started to take the virus more seriously and regulatory agencies started to issue temporary relaxations of regulations. However, the level of uncertainty expressed in the news shows no signs of diminishing, indicating persistent uncertainty surrounding regulation in the time of COVID-19. Further topic modeling of news articles suggests that sentiment and uncertainty vary across different regulatory issues. News covering quarantine and reopening, legislation (other than the stimulus bill), and testing and treatment revealed the most negative sentiment, and uncertainty was relatively high regarding testing and treatment, workplace safety, banking and lending, and oil prices.

This study focuses on presenting the technological, impact and regulatory state of play in the EU, as compared to key competitor countries. This study also highlights industrial areas in which AI will bring significant socioeconomic benefits, before presenting a methodology for scrutinising the fitness of the EU policy and regulatory framework in the context of AI. This document was provided by the Policy Department for Economic, Scientific and Quality of Life Policies at the request of the committee on Industry, Research and Energy (ITRE committee).

Ex-ante impact assessment and ex-post evaluation are regulatory policy tools that help inform the policy-making process with evidence-based analysis. Both tools are geared towards raising the quality of policies and legislation. While Better Regulation is widely deemed a prerogative of the executive branch, increasingly, parliaments are also emerging as actors. This study sheds light on the parliamentary dimension of Better Regulation. Based on a survey, it maps the capacities and experiences of the national parliaments of all 27 European Union (EU) Member States and of 11 further Council of Europe countries in the field of ex-ante impact assessment and ex-post evaluation. The study reveals that roughly half of the surveyed parliaments engage in regulatory policy beyond classical parliamentary scrutiny mechanisms. Overall, these parliaments show a very diverse pattern in terms of drivers, types and depth of engagement. There is no 'one size fits all' approach.

As algorithmic systems become more critical to decision making across many parts of society, there is increasing interest in how they can be scrutinised and assessed for societal impact, and regulatory and normative compliance. This report is primarily aimed at policymakers, to inform more accurate and focused policy conversations. It may also be helpful to anyone who creates, commissions or interacts with an algorithmic system and wants to know what methods or approaches exist to assess and evaluate that system.