Computer science

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  • Rules, Computation and Politics: Scrutinizing Unnoticed Programming Choices in French Housing Benefits

    Denis Merigoux, Marie Alauzen, Lilya Slimani

    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.

  • Technical Countermeasures against Adversarial Attacks on Computational Law

    Dario Henri Haux, Alfred Früh

    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.

  • Analogies and Disanalogies Between Machine-Driven and Human-Driven Legal Judgement

    Reuben Binns

    Are there certain desirable properties from text-driven law, which have parallels in data-driven law? As a preliminary exercise, this article explores a range of analogies and disanalogies between text-driven normativity and its data-driven counterparts. Ultimately, the conclusion is that the analogies are weaker than the disanalogies. But the hope is that, in the process of drawing them, we learn something more about the comparison between text and data-driven normativities and the (im?)possibility of data-driven law.

    Reply by Emily M. Bender, Professor of Computational Linguistics, University of Washington.