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CFP
CRCL22: Computational 'law' on edge
Vrije Universiteit Brussel
Brussels, Belgium, November 3-4, 2022
Conference websitehttps://www.cohubicol.com/about/conference-crcl-2022/
Submission linkhttps://easychair.org/conferences/?conf=crcl22
Abstract registration deadlineApril 19, 2022
Submission deadlineJuly 1, 2022
Topics: legal search and prediction formalisation and rules as code ai in international law

Registration for the conference is now open

Limited space for in person attendance, remote participation will be facilitated

See the Conference Ethos regarding the Cross-Disciplinary Nature of the Conference

See also our data protection statement (PDF)

Conference 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 (CRCL), 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.

They 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.

More papers may be submitted for publication in the Journal, following the conference and any required revisions.

Conference Tracks

The Conference has three tracks:

  1. legal search and prediction
  2. formalisation and rules as code (RaC)
  3. AI in international law

Each track will be run by two Track Chairs, one for law and one for computer science

Papers will be reviewed by 2 reviewers of the own discipline of the author: law, computer science or social science/humanities (double blind peer review)

Accepted papers will be replied by a replier from the other discipline (the reply will be published with the article and followed by a response)

List of Topics

We invite computer scientists and lawyers, as well as social science and humanities scholars to submit an abstract by 19 April in one or more of the following 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.

Deadlines

  • 19 April: submission of an extended abstract (1500 words) 

  • 30 April: notification of the invitation to submit a full paper (6-8K)

  • 1 July: submission of full paper (6-8K words) for double blind 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 (1500 words) and the author response (750 words) will be solicited 

  • Publication March/April 2023

 

Program Committee

Reviewing will be supported by 3 Program Sub-Committees in: (i) Law, (ii) Computer Science (CS) and (iii) Social Sciences and Humanities (SH)

Publication

CRCL22 proceedings will be published in the Journal of Cross-disciplinary Research in Computational Law (CRCL)

Venue and Date

The conference will be held in Brussels on November 3-4.

Cross-disciplinary conference 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’ (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.

Legal solutionism or scepticism?

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: 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: 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: 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://edinburghuniversitypress.com/book-digisprudence-code-as-law-rebooted.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.

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