CRCL2022 conference banner

An international conference organised by COHUBICOL in collaboration with CRCL

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

3-4 November 2022 in Brussels
In person / Online / Hybrid (COVID permitting)

Registration now open at EasyChair

Keynotes and tracks Call for abstracts Deadlines Conference ethos


Keynotes and tracks

Keynotes

  • ‘How to build language processing applications that work—and expose those that don’t’ – Emily M. Bender
  • ‘A responsible and relational conceptualisation for computational law’ – Virginia Dignum
  • ‘Positional Services: Avoiding a Legal Technology Arms Race’ – Frank Pasquale
  • Title TBA – Antoinette Rouvroy

Conference tracks

Each track will be led by track chairs who coordinate the paper review process

  1. Legal search and prediction (Harry Surden, Sofia Olhede)
  2. Formalisation and Rules as Code (Lyria Bennett Moses, Denis Merigoux)
  3. AI in international law (Fleur Johns, Jatinder Singh)

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Call for abstracts

Before submitting, check out the Conference Ethos below.

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

  • Computer Science
  • Artificial Intelligence
  • Law
  • Legal theory
  • Philosophy of law
  • Philosophy of technology
  • Critical data studies
  • Critical algorithm studies
  • Critical code studies
  • Linguistics
  • Political Economy of law

We seek in-depth analysis addressing both the potential and the challenges of computational ‘law’. We welcome internal critiques in both law and CS, to ensure a grounded conversation that crosses disciplinary boundaries.

For more on the scope of the conference, see the COHUBICOL and CRCL websites.

Presentation format

Papers that are accepted for presentation at the conference will be published as preprints before the event. Following the conference, we expect to publish final versions of the papers in the Journal of Cross-disciplinary Research in Computational Law, along with the reply and response as described below. In line with the CRCL submission policy, papers must not be submitted to or under the consideration of any other journal.

A selection of papers will be presented in plenary format:

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

The reply and response will be added to the paper and submitted to CRCL.

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Deadlines

  • 19 April: submission of extended abstracts (1,500 words)
  • 30 April: notification of invitation to submit
  • 1 July: submission of full paper (6-8k words) to CRCL for peer review
  • 1 July - 15 August: double blind peer review
  • 13 September: editorial decision on acceptance for presentation at the Conference, with minor or major revisions required for the Journal
  • 14 September: invitation of repliers
  • 30 October: papers accepted for the Conference will be shared with registered participants
  • 3-4 November: conference
  • 30 November: submission to the Journal with minor or major revisions
  • After papers are accepted by the Journal, the cross-disciplinary reply (1,500 words) and the author response (750 words) will be solicited
  • March/April 2023: publication final papers

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Ethos

The future or the end of law?

Data-driven ‘law’: Legal practice and legal scholarship are confronted with academic papers describing software systems that outperform lawyers in predicting legal judgments [1][3], with 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], with a plethora of legal tech start-ups that offer legal advice or dispute resolution to laypersons and 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/>).

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 [6], [7][8]. These efforts aim to provide improved access to applicable law, aiming to rewrite the relevant natural language text in a way that avoids both unintended ambiguities and contradictions with other applicable legal rules, thus supposedly 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 [9]. This has given rise to various types of reflection, taking the perspective of critical code studies [10] or science, technology and society (STS) studies [11], 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 insights 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 cheaper products or semi-automation of collective action [12], 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 [13], [14]. Indeed, a proposal has been made to develop a dedicated digisprudence [15] to face the issues of computational law [16], [17].

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. [Online]. 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]: 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.

[7]: J. Mohun and A. Roberts, “Cracking the code: Rulemaking for humans and machines,” Oct. 2020, doi: <https://doi.org/10.1787/3afe6ba5-en>.

[8]: 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.

[9]: M. Corsius, S. Hoppenbrouwers, M. Lokin, E. Baars, G. Sangers-Van Cappellen, and I. Wilmont, “RegelSpraak: a CNL for Executable Tax Rules Specification,” presented at the CNL 2021, Amsterdam, Netherlands, Sep. 2021. Accessed: Nov. 25, 2021. [Online]. Available at <https://aclanthology.org/2021.cnl-1.6>

[10]: M. C. Marino, Critical Code Studies. Cambridge, MA, USA: MIT Press, 2020.

[11]: 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.

[12]: 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. [Online]. Available at <https://muse.jhu.edu/article/688835>

[13]: F. Pasquale, New Laws of Robotics: Defending Human Expertise in the Age of AI. Cambridge, Massachusetts, 2020.

[14]: L. Diver, “Digisprudence: the design of legitimate code,” LawArXiv, preprint, Jul. 2020. doi: 10.31228/osf.io/nechu.

[15]: L. Diver, Digisprudence: Code as Law Rebooted. Edinburgh: Edinburgh University Press, 2022. Available OA at <https://www.degruyter.com/document/doi/10.1515/9781474485340/html>.

[16]: 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.

[17]: 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.

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.