Vol. 2 No. 1 (2023): CRCL22: Computational 'Law' on Edge
Papers presented at the inaugural Conference on Cross-disciplinary Research in Computational Law (CRCL22) in Brussels, November 2022.
(Published on a rolling basis.)
Papers presented at the inaugural Conference on Cross-disciplinary Research in Computational Law (CRCL22) in Brussels, November 2022.
(Published on a rolling basis.)
The article questions the translation of a particular legal statement, a rule of calculation of social rights, into a computer program, able to activate the rights of the concerned citizens. It does not adopt a theoretical perspective on the logic of law and computing, rather a realistic stance on contemporary welfare states, by studying the case of the calculation of housing benefit in France. Lacking access to CRISTAL, the source code of the calculation, we simulated the code base from the letter of the law and met with the writers of the housing law in the ministries to conduct a critical investigation of the source code. Through these interdisciplinary methods, we identified three types of unnoticed micro-choices made by developers when translating the law: imprecision, simplification and invisibilization. These methods also uncover significant sociological understanding of the ordinary writing of law and code in the administration: the absence of a synoptic point of view on a particular domain of the law, the non-pathological character of errors in published texts, and the prevalence of a frontier of automation in the division of bureaucratic work. These results from the explicitation of programming choices, lead us to plead for a re-specification in the field of legal informatics and a reorientation of the investigations in the field of the philosophy and the sociology of law.
‘Rules as Code’ is a broad heuristic that encompasses different conceptual and practical aspects regarding the presentation of legal instruments as machine executable code, especially for use in automated business systems. The presentation of law as code was historically considered a largely isomorphic exercise that could be achieved through a literal translation of law into code. Contemporary research is questioning the value of a literal approach to legal coding and is adopting different interpretive strategies that seek enhanced alignment between law and code. In this article, we report on research findings involving the coding of an Australian Commonwealth statute – the Treasury Laws Amendment (Design and Distribution Obligations and Product Intervention Powers) Act 2019 (Cth) (the ‘DDO Act’), and the Act’s concomitant regulatory guidance – the Australian Securities and Investments Commission (ASIC) Regulatory Guide 274 (‘RG 274’). We adapt and apply Brownsword’s mindsets to develop different interpretive approaches that were necessary to resolve the coding issues encountered. The mindset strategies enabled us to outline and delineate distinct computational, legal and regulatory interpretive approaches that highlight the different cultural contexts and rationales which are embedded in legal instruments, like legislation and regulatory guidance. In conclusion, we contend that different types of mindset strategies better highlight the interpretive choices involved in the coding of legal and regulatory instruments.
This paper aims to investigate the possibility of using Artificial Intelligence (AI) to resolve the legal issues raised by the Covid-19 emergency about the fate of contracts with continuous, repeated or deferred performance, as well as, more generally, to deal with exceptional events and contingencies. We first study whether the Italian legal system allows for `maintenance' remedies to face contingencies and to avoid the termination of the (duration) contracts, while ensuring effective protection of the interests of both parties. We then give a complete and technical description of an AI-based predictive framework, aimed at assisting both the Magistrate (during the trial) and the parties themselves (in out-of-court proceedings) in the redetermination of the rent of commercial lease contracts. This framework, called A.I.A.Co. for Artificial Intelligence for contract law Against Covid-19, has been developed under the Italian public grant called Fondo Integrativo Speciale per la Ricerca and - even if the predictive system was initially intended to deal with the very specific problem connected to Covid-19 - the knowledge acquired, the model produced and the research outcomes can be easily transferred to other civil issues (such as, for example, those relating to the determination of the amount of the maintenance or divorce obligation in family law).
This paper provides one of the first fieldwork-based research accounts of China's Social Credit Systems (SCS). It focuses on the issue of automated law enforcement. Evidence is drawn from semi-structured interviews with Shanghai-based local government officials, judges and corporate employees, conducted in April 2021. These are actors who supervise, manage, and/or operate Shanghai’s SCS at the level of daily practice. The paper examines the use of blacklists and joint sanctions within the wider framework of the SCS. The interview evidence, combined with online archival research, uncovers a more complete understanding than previously available of the detailed workings of these systems and of their perceived impacts, both positive and negative, in the field. Automation is observed to have achieved efficient scaling, but also to have negative consequences, including rigidity at the level of code, and perverse or counter-productive incentives at the level of human behaviour, leading to ‘institutional overload’. Proposing an original institutional theory of computational law which identifies the role of governance in ‘scaling and layering’, the paper argues that automated enforcement can only achieve scale effects if human judgement is combined with automation. Human agency is needed to continuously realign and re-fit code-based systems to text-driven laws and social norms in specific spatio-temporal environments. In the final analysis, code operates in a path-dependent and complementary way to these other forms of governance. From social norms to laws, to data and to code, governance is layered via formalisation sustained by human work and societal feedback.
This paper is an inquiry into the informational nature of legal systems to arrive at a new understanding of law-society interactions. Katharina Pistor in her book Code of Capital reveals how the legal ‘coding’ of ‘capital’ has deepened wealth inequality but does not offer an in-depth exploration or definition of ‘legal coding’. In her critical response to ‘legal singularity’ as a proposed solution for making law more inclusive and accessible, Jennifer Cobbe calls for a closer look at the structural role law plays in society and how it has come to exclude, marginalise and reinforce power gaps. The paper aims to link Pistor’s project with Cobbe’s critical questions by exploring ‘law as code’ and modelling juridical communication and information flows in a legal system. For this purpose, I use two external frames — Claude Shannon’s information theory and Niklas Luhmann’s systems theory — to explore ways in which the legal system is exclusive, reflexive, and adaptive in the ways it interacts with society. An attempt to model information flows within (using Shannon) and beyond (using Luhmann) the boundaries of law reveals the influence of experts, their identities, and their lived experiences on both the translation and transmission of legal information. The paper is hopefully a starting point for more cross-disciplinary conversations aimed at addressing the structural issues with the way law shifts and reinforces power.
Reply by Jannis Kallinikos, LUISS Guido Carli University.
Adversarial Attacks, commonly described as deliberately induced perturbations, can lead to incorrect outputs such as misclassifications or false predictions in systems based on forms of artificial intelligence. While these changes are often difficult to detect for a human observer, they can cause false results and have impacts on physical as well as intangible objects. In that way, they represent a key challenge in diverse areas, including — among others — legal fields such as the judicial system, law enforcement and legal tech. While computer science is addressing several approaches to mitigate these risks caused by Adversarial Attacks, the issue has not received much attention in legal scholarship so far. This paper aims to fill this gap, tries to assess the risks of and technical defenses against Adversarial Attacks on AI Systems and provides a first assessment of possible legal countermeasures.
This paper aims to offer a nomic (legal-spatial-political) concept of platform at the interface between modern legal theory and contemporary speculative philosophy. I argue that the ‘code as law’ debate has been dominated by ‘legal correlationism’, a theoretical framework based on the is/ought distinction in which ‘code’ appears as a technological fact to be regulated by legal norms. I propose an alternative approach via speculative legal theory in order to take code as law in a literal sense. I rework Carl Schmitt’s notion of ‘nomos’ to produce a legal concept of platform that avoids correlationism. I frame both modern law and computational platforms as nomic platforms, though based on different conceptions/experiences of technics, and map out their respective operations. I discern three types of norms active in nomic platforms: coded, interfacial and environmental norms, the first two of which have been often confused, while the third remain largely unknown to legal theory. Finally, I seek to offer a set of concepts meant to render cloud platforms intelligible in nomic terms, especially those of device, application, interface and user, introducing the notion of the transdividual user as the correlate of algorithmic governance. I close by emphasising that, though it is vital to criticise platform nomics and protect the affordances of law-as-we-know-it, those efforts should be supplemented by theoretico-practical speculation about what law may become.
Reply by Cecilia Rikap, University College London.
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CRCL is Platinum Open Access under the Creative Commons BY-NC license.
ISSN 2736-4321.