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Post-Project Output: The Special Issue on ‘THE FUTURE OF COMPUTATIONAL LAW’

 28 May 2024

For the second CRCL Conference (CRCL23) in Brussels we invited a small number of key authors in the domain of computational ‘law’ to present their position on the future of code- and data-driven legal technologies. Their salient papers provide a research agenda for further development and integration of these technologies, including keen attention to the education and training of lawyers and computer scientists, the impact on access to justice, Rule of Law checks and balances, the need for targeted instead of general ‘solutions’ and an analysis of what the integration of AI in legal practice can and cannot achieve. The papers, by thought leaders across the spectrum of both law and computer science, have now been published in the Journal of Cross-Disciplinary Research in Computational Law, in this special issue.

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Hildebrandt publishes chapter on ‘Grounding Computational Law’ in legal education and professional legal training

 18 Dec 2023

COHUBICOL’ s Mireille Hildebrandt has contributed a chapter in the recently published Research Handbook on Law and Technology (Edward Elgar Publishing, 2023). The chapter, entitled ‘Grounding computational ‘law’ in legal education and professional legal training’, discusses how we can devise learning objectives and teaching approaches that contribute to critical engagement with computational legal technologies and calls for effective scrutiny of such technology in legal research and practice.  

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Hildebrandt reviews Matsumi and Solove’s paper on The Prediction Society

 1 Dec 2023

Daniel J. Solove, Professor of Intellectual Property and Technology Law at the George Washington University Law School - and one of the global thought leaders on privacy matters - and Hideyuki Matsumi, a doctoral researcher of the Law, Science, Technology and Society Research Group at the Vrije Universiteit Brussel (LSTS), have co-authored the paper ‘The Prediction Society: Algorithms and the Problems of Forecasting the Future’.

In their paper they state that algorithmic predictions are types of inferences that current privacy and data protection laws fail to adequately address. They argue that the use of algorithmic predictions is a distinct issue warranting different treatment from other types of inference and they further examine the issues laws must consider when addressing the problems of algorithmic predictions.

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