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The 2nd international conference organised by COHUBICOL in collaboration with CRCL

General Co-Chairs:
Katie Atkinson, Mireille Hildebrandt, Frank Pasquale,
Laurence Diver

20 - 21 November 2023 in Brussels
Hybrid • attendance free of charge

Registration now open   Programme

Programme committee Format Call for abstracts Conference ethos Deadlines Reviewers

Programme committee

Conference format

Day 1: Symposium on The Future of Computational ‘Law’

Ten renowned scholars/scientists will present and discuss their invited position papers on

  • the current state of the domain of computational ‘law’, and
  • the direction that should be taken in view of adherence to the rule of law.

Accepted papers will be presented in a plenary format:

  • 10 minute provocation by the author
  • followed by a dedicated cross-disciplinary reply, and a response from the author
  • followed by a Q&A with the audience.

After the conference, revised papers will be submitted to CRCL.

In the afternoon we will convene a Round Table on The Future of Legal Method

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Call for abstracts

Before submitting, check out the Conference ethos below.

We invite computer scientists and lawyers, as well as scholars in the humanities or social sciences to submit an extended abstract by 15 April in one or more of these domains:

  • Computer Science
  • Artificial Intelligence
  • Law and legal theory
  • Philosophy of law
  • Philosophy of technology
  • Critical data studies
  • Critical algorithm studies
  • Critical code studies
  • Linguistics
  • Political economy of law
  • Political economy of legal technologies

We seek in-depth analyses that address both the potential and the challenges of computational ‘law’. We advise visiting the COHUBICOL and CRCL websites to check the scope of the domain. We are seeking internal critiques in both law and CS, to ensure a grounded conversation across disciplinary boundaries. In line with the ethos of the COHUBICOL project, we particularly welcome analyses that take a normative position as to adherence to key rule of law ‘requirements’, notably concerning (1) the checks and balances between the powers of the state, (2) practical and effective enjoyment of human rights and (3) resilience against instrumentalization against big players, whether public or private.

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Deadlines

  • 15 April: submission of extended abstracts (1,500 words)
  • 30 April: notification of invitation to submit a paper
  • 1 July: submission of full paper (6-8k words) for double-blind peer review
  • 1 July – 30 August: double blind peer review
  • 15 September: editorial decision on acceptance for presentation at the Conference
  • 15 September: invitation of repliers
  • October or November: conference

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Reviewers

All papers will undergo double blind peer review by reviewers from the disciplinary background of the author(s) (if co-authored based on different disciplinary backgrounds we will involve reviewers from the relevant disciplines).

Note we are looking for excellence in the author’s own discipline, though our understanding of excellence may differ from the usual metrics approach.

Papers should focus on rule of law, political economy of law, fundamental rights. This is about legal protection as well as instrumentality.

In-depth theoretical approaches are encouraged.

There will be three disciplinary domains, for:

  1. Peer Review in Law (legal theory, positive law)
  2. Peer Review in CS (computer science)
  3. Peer Review in SH (social science and humanities)

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Ethos

The future of computational law

Data-driven ‘law’: Legal practice and legal scholarship are confronted with (i) academic papers describing software systems that outperform lawyers in predicting legal judgments [1–[3], (ii) proprietary legal search engines that claim to replace cumbersome hands-on search with highly accurate advice on relevant case law and/or relevant statutory law [4], [5], (iii) a plethora of legal tech start-ups that offer legal advice or dispute resolution to laypersons, and (iv) with big law firms, justice authorities and the judiciary buying into advanced legal search, seeking both efficiency and improved legal decision-making. Major publishers of ‘legal content’ (formerly called legal text) offer various packages with different levels of ‘intelligence’, competing in a multibillion-euro market for ‘legal services’ often sold under the heading of ‘legal tech’ (https://www.statista.com/statistics/1155911/europe-legal-tech-revenue-by-market/). Finally, some have high hopes that Large Language Models (LLMs, a curious acronym for lawyers) will revolutionise any field of study and practice, including the law, for instance testing whether ChatGPT would pass the Bar Exam [6].

Code-driven ‘law’: legal practice and legal theory are also confronted with major investments in making legislation machine-consumable or even writing legislation in the form of dedicated software code [7], [8][9]. These efforts seek to provide improved access to applicable law, aiming to rewrite the relevant natural language text in ways that avoid both unintended ambiguities and contradictions with other applicable legal rules, thus paving the way for an improved ‘user experience’ for both lawyers and those subject to the law. Similar efforts pave the way for increased reliance on automated decision systems that translate legislation into ‘business rules’ to calculate, automate and thus scale individual decisions [10]. This has given rise to various types of reflection, taking the perspective of critical code studies [11] or science, technology and society (STS) studies [12], based on an in-depth engagement with the underlying technological infrastructure and the various abstract layers involved in the construction of constrained natural languages, dedicated programming languages, assemblers and compilers intended to produce a clean, unambiguous and relevant ‘legal computer code’ that is largely isomorphic with the related legal text.

Commercial providers tend to advocate a brand of legal solutionism, by claiming increased efficiency, accuracy and/or insight that will replace much of the allegedly boring or time-consuming search for relevant legal information [4], thanks to data-driven legal search and the advent of machine-consumable law. Some believe these legal technologies will finally democratise access to justice based on the scaling of legal services for marginalised communities, due to cheaper products or semi-automation of collective action [13], and seamless access to relevant legislation. Others express scepticism about the supposed added value, warning against a kind of technological solutionism that will play into the hands of those already well protected, or lead us into a form of digital legalism [14], [15]. Indeed, a proposal has been made to develop a dedicated digisprudence [16] to face the issues of computational law [17], [18].

This conference aims to steer free of either techno-optimism or techno-pessimism, instead seeking to inquire into (i) the theoretical assumptions and affordances of NLP and computer code in both data- and code-driven ‘legal techs’, (ii) the complex socio-technical dynamics that will play out when integrating advanced legal search into legal practice, (iii) the implications of all this for legal doctrine, legal practice, legal scholarship and, finally, (iv) the kind of legal protection afforded by text-driven law.

  1. D. M. Katz, M. J. B. Ii, and J. Blackman, “A general approach for predicting the behavior of the Supreme Court of the United States,” PLOS ONE, vol. 12, no. 4, p. e0174698, Apr. 2017, doi: 10.1371/journal.pone.0174698.
  2. I. Chalkidis, I. Androutsopoulos, and N. Aletras, “Neural Legal Judgment Prediction in English,” ArXiv190602059 Cs, Jun. 2019, Accessed: Feb. 18, 2020.. Available at http://arxiv.org/abs/1906.02059
  3. M. Medvedeva, M. Vols, and M. Wieling, “Using machine learning to predict decisions of the European Court of Human Rights,” Artif. Intell. Law, vol. 28, no. 2, pp. 237–266, Jun. 2020, doi: 10.1007/s10506-019-09255-y.
  4. S. Steer, “Westlaw Edge UK: Three Traits that Make for an Unrivalled Lawyer,” Leg. Inf. Manag., vol. 21, no. 2, pp. 79–87, Jun. 2021, doi: 10.1017/S1472669621000177.
  5. T. Custis, F. Schilder, T. Vacek, G. McElvain, and H. M. Alonso, “Westlaw Edge AI Features Demo: KeyCite Overruling Risk, Litigation Analytics, and WestSearch Plus,” in Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law, New York, NY, USA, Jun. 2019, pp. 256–257. doi: 10.1145/3322640.3326739.
  6. M. Bommarito II and D. M. Katz, “GPT Takes the Bar Exam.” arXiv, Dec. 29, 2022. doi: 10.48550/arXiv.2212.14402.
  7. D. Merigoux, N. Chataing, and J. Protzenko, “Catala: a programming language for the law,” Proc. ACM Program. Lang., vol. 5, no. ICFP, p. 77:1-77:29, Aug. 2021, doi: 10.1145/3473582.
  8. J. Mohun and A. Roberts, “Cracking the code: Rulemaking for humans and machines,” Oct. 2020, doi: https://doi.org/10.1787/3afe6ba5-en.
  9. P. Casanovas, “Comments on Cracking the Code. A short note on the OECD Working Paper Draft on Rules as Code,” in Comments on Cracking The Code: Rulemaking For Humans And Machines (August 2020 draft) Comments on the draft OECD White Paper on Rules as Code, submitted on 27 August 2020 to the authors, Zenodo, 2020, pp. 13–24. doi: 10.5281/zenodo.4166115.
  10. M. Corsius, S. Hoppenbrouwers, M. Lokin, E. Baars, G. Sangers-Van Cappellen, and I. Wilmont, “RegelSpraak: a CNL for Executable Tax Rules Specification,” in Proceedings of the Seventh International Workshop on Controlled Natural Language (CNL 2020/21), Amsterdam, Netherlands, Sep. 2021. Accessed: Nov. 25, 2021. Available at https://aclanthology.org/2021.cnl-1.6
  11. M. C. Marino, Critical Code Studies. Cambridge, MA, USA: MIT Press, 2020.
  12. D. Allhutter, F. Cech, F. Fischer, G. Grill, and A. Mager, “Algorithmic Profiling of Job Seekers in Austria: How Austerity Politics Are Made Effective,” Front. Big Data, vol. 3, 2020, doi: 10.3389/fdata.2020.00005.
  13. P. Gowder, “Transformative legal technology and the rule of law,” Univ. Tor. Law J., vol. 68, no. 1, pp. 82–105, 2018, Accessed: Feb. 05, 2021. Available at https://muse.jhu.edu/article/688835
  14. F. Pasquale, New Laws of Robotics: Defending Human Expertise in the Age of AI. Cambridge, Massachusetts, 2020.
  15. L. Diver, “Digisprudence: the design of legitimate code,” (2021) 13(2) Law, Innovation and Technology 325.
  16. L. Diver, Digisprudence: Code as Law Rebooted. Edinburgh: Edinburgh University Press, 2022. Accessed: Feb. 02, 2022. Available at https://edinburghuniversitypress.com/pub/media/ebooks/9781474485340.pdf
  17. M. Hildebrandt, “Law as Information in the Era of Data‐Driven Agency,” Mod. Law Rev., vol. 79, no. 1, pp. 1–30, Jan. 2016, doi: 10.1111/1468-2230.12165.
  18. M. Hildebrandt, “Law as computation in the era of artificial legal intelligence: Speaking law to the power of statistics,” Univ. Tor. Law J., Mar. 2018, doi: 10.3138/utlj.2017-0044.

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Funding

This conference is fully funded by the Advanced Grant awarded by the European Research Council for the COHUBICOL project. See the footer of this website for details.

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