This article provides an overview of how computational methods are affecting research across the varied landscape of legal scholarship, from the interpretation of legal texts to the quantitative estimation of causal factors that shape the law. Already, computational methods have facilitated important contributions in a diverse array of law-related research areas. As these tools continue to advance, and law scholars become more familiar with their potential applications, the impact of computational methods is likely to continue to grow.

How is Computational Law and Regulation (CARL) different from contiguous disciplines such as Empirical Legal Studies or Legal Tech? What may computer science add to the understanding of legal concepts? For instance, international law scholars have in the past drawn inspirations from economics, political science or sociology to enrich the study and our understanding of international law. The computational analysis of international law renders legal analysis scalable and empowers scholars to study international law in unprecedented depth and breadth. But what is it really new about CARL compared to existing techniques such as Empirical Legal Studies?....

In this scenario it could help finding best practices, discover effective norms, good patterns of linguistic formulations, detect inconsistent norms and definitions, reveal implicit modifications and repeals, underline some unused acts, cluster similar regulations, correlate different norms, detect unexpected relationships, support legislative offices to achieve better quality of legislation.

Secondly, we will focus on how in practice AI can make the law computable by-design (Law by-design), help checking compliance with norms and easing implementation (think e.g., to smart contracts). In both cases, we will discuss the opportunities and risks associated with the use of AI for making legislation by algorithm the new paradigm. In particular, we will remark the need to preserve transparency of the algorithmic process, using a solid legal-theory methodology, a robust explicability processing to avoid creating a new black box capable to obscuring democratic and due process principles.

Dark patterns have been with us for some time now. But “how effective are they?” That question is as unanswered as vital if we are to understand the magnitude of the problem and whether regulation is appropriate. The lack of published research and data about the successes and failures of the techniques seems to suggest that dark patterns work and generate profits for the many firms employing them....

...Strahilevitz presents the results of two unique large-scale experiments on census-weighted samples of many widely employed dark patterns, providing the first comparative evidence of how strikingly effective DP are in getting consumers to do what they would not do when confronted with more neutral user interfaces.

What is the difference with vivid images, colors, aggressive advertising and unfair commercial practice? Does "scale" of the digital environment make any difference? And if so, should regulation of DP be an option?

What are the main normative implications of behavioral economics for legal policymaking? More specifically, what goals should the law seek to achieve, and what means should it use to achieve its goals? These two normative questions will be discussed in the framework of disclosure duties, contrasting traditional economic with behavioral analysis.

Is regulation of information by disclosure duties well founded from a behavioral perspective? What empirical evidence is supporting such rulemaking strategy?

Future proofing science, design, architecture, and technology entails the creation of solutions that are forward-looking, sustainable, resilient, and can adapt to complex challenges. In the last years, lawmakers have also become intrigued by the question whether laws and policies could also be future-proof. This question has become particularly relevant considering the rapid changes that characterize the digital age. The implementation of a future-proof approach to legislation has nonetheless remained overlooked in the legal literature. Future proofing law is a challenging task for legislators but a cautious forward-looking approach could ensure that legislation becomes more adaptable and flexible to innovation. Drawing on the interdisciplinary literature on future proofing, we suggest the broader employment of experimental legislation and regulatory impact assessments.

FThe Internet is helping regular users make money in ways that did not exist 10 years ago, such as influencer marketing or ad revenue. These users (sometimes referred to as influencers or content creators) engage in cultural production, namely they create content on social media platforms. To monetize their activity, they often act as vehicles for hidden advertising. European law is lagging behind in terms of interpretations (e.g. of unfair commercial practices), of drawing lines between lawful and unlawful behavior relating to the failure of disclosing advertising.

How does the doctrine view the current European legal frameworks and interpretations, including proposed reforms in the Digital Services Act?
Can a digital (legal) ethnography view of how to do qualitative empirical research on social media monetization be provided?
What is the contribution of Natural Language Processing to the measuring and monitoring of social media disclosures?