第19届国际人工智能与法律会议论文征稿

法研在线 2023-03-25

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Universidade do Minho, Braga, Portugal
Universidade do Minho Law School with JUSGOV – Research Center for Justice and Governance, Centro Algoritmi and LASI – Laboratório Associado de Sistemas Inteligentes
Conference Website: https://icail2023.di.uminho.pt

Since 1987, the International Conference on Artificial Intelligence and Law (ICAIL) has been the foremost international conference addressing research in Artificial Intelligence and Law. It is organized biennially under the auspices of the International Association for Artificial Intelligence and Law (IAAIL), and in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI). The conference proceedings are published by ACM.
We invite submissions of papers along a regular and three special tracks, technology demonstrations, as well as proposals for workshops and tutorials.

Topics

We invite submission of original papers on Artificial Intelligence & Law, covering foundations, methods, tools, systems and applications. Topics may include, but are not limited to, the following:

Argument mining on legal texts
Classification and automatic summarization of legal text
Computational methods for negotiation and contract formation
Computer-assisted dispute resolution
Computable representations of legal rules and domain specific languages for the law
Decision support systems in the legal domain
Deep learning on data and text from the legal domain
Dialog systems in the legal domain
e-discovery and e-disclosure
e-government, e-democracy and e-justice
Ethical, legal, fairness, accountability, and transparency subjects arising from the use of AI systems in legal practice, access to justice, compliance, and public administration
Explainable AI for legal practice, data, and text analytics
Formal and computational models of legal reasoning (e.g., argumentation, case-based reasoning), including deontic logics
Formal and computational models of evidential reasoning
Formal models of norms and norm-governed systems
Information extraction from legal databases and texts
Information retrieval, question answering, and literature recommendation in the legal domain
Intelligent legal tutoring systems
Intelligent support systems for forensics
Interdisciplinary applications of legal informatics methods and systems
Knowledge acquisition techniques for the legal domain, including related applications of natural language processing, argument, and data mining
Knowledge representation, knowledge engineering, and ontologies in the legal domain
Legal design involving AI techniques
Machine learning and data analytics applied to the legal domain
Natural language processing of legal text, including law-specific standard NLP tasks (e.g., Named Entity Recognition, Semantic Role Labeling, Translation, etc.)
Normative reasoning by autonomous agents
Open and linked data in the legal domain
Smart contracts and application of blockchain in the legal domain
Visualization techniques for legal information and data

ICAIL is keen to broaden its scope to include topics of growing importance and to establish links to neighboring disciplines. In addition to the regular paper track, ICAIL 2023 will feature the following special tracks:
(1) a new special cross-disciplinary outreach track on Artificial Intelligence for Empirical Legal Studies. Legal systems have seen an increasing need to leverage data analysis to inform stakeholders, decision makers, and policy actors. This potential comes with a mandate for credible empirical research, as well as constructive communication, across communities at the intersection of law and data-driven disciplines. The empirical legal studies and AI&Law communities stand to benefit from an exchange of ideas and collaborations around concrete legal use cases, technical approaches, and commitment to using data-driven technology for policy and social good. For this track we invite short and long submissions of original papers on topics including, but not limited to:

Use of machine learning and/or knowledge representation techniques as part of statistical analyses of data from the legal domain
Use of AI methods (e.g, natural language processing) on legal data to extract information to be used as part of statistical analysis
Explainability and robustness of complex machine learning models towards specific legal analytic and policy objectives
Unstructured legal corpora and problems for data mining and discovery
Visualization-based exploration of legal data relevant for empirical research
Tools and best practices for data collection, curation, and statistical experimentation in the legal domain

(2) Innovative applications in AI and Law – Applications that fall within any of the core AI & Law topics. Papers in this track will be subject to the same rigorous reviewing process as regular papers, but the emphasis is less on novel scientific contributions, formal frameworks, or results and more on the innovative and novel application of techniques from AI & Law to real world problems and use cases.

(3) Legal, ethical, fairness, accountability, and transparency aspects of AI applications in legal practice, access to justice, compliance, and public administration – ICAIL is committed to not only further the state of the art in using AI technology in legal practice, but also about the legal and ethical ramifications of such applications. This track is intended to facilitate this discourse through the inclusion of case studies, reports on regulations efforts, lessons learned from experiments, technical contributions about monitoring and facilitating ethical use of AI in relevant areas, and other topical contributions. Papers in this track will be subject to the same rigorous reviewing process as regular papers.

Paper submission

Papers (up to 10 pages including references for long papers, up to 5 pages including references for short papers) should present contributions from relevant topics. To maintain ICAIL’s relevance in the larger rapidly-moving field at the intersection of law and artificial intelligence, all papers must make clear their relation to legal information, reasoning, or processes as well as relation to prior work and novel scientific contribution, as well as contain a satisfying amount of discussion of their findings.
Papers on machine learning or data mining should include discussions of the data, methodology, results, and analysis in sufficient depth beyond merely reporting metrics. Submissions focusing on the reproduction, validation, constructive scrutinization, and extension of previously published works, datasets, and benchmarks are strongly encouraged.
Papers proposing formal or computational models should provide examples and/or reproducible simulations. Papers on applications should describe the motivations, techniques, implementation, and evaluation.
It is highly recommended for all submissions that code and data be published alongside the papers to facilitate reproducibility. Program committee members will be instructed to take data and code sharing into account in their reviews.
Paper must formatted using the ACM sigconf template (for LaTeX) or the interim template layout.docx (for Word), both at
http://www.acm.org/publications/proceedings-template
All papers should be converted to PDF prior to electronic submission. Papers that do not adhere to these conditions will be rejected without review.

Submissions should be uploaded in the conference support system Conftool [link forthcoming] by the submission deadline. For each submission, it should be indicated whether it belongs in the regular track or one of the special tracks (AI&Law for Empirical Legal Studies or Innovative Applications or Ethical and Legal Issues for AI in Legal Practice) using the facility provided by the submission system.
Reviewing will be double blind. Papers submitted for review must not include names and affiliations of the authors and not include an acknowledgments section. Any identifying text in the body of the paper (e.g. citing “our work”) should be removed or rephrased to be non-identifying. These aspects can be added at the camera-ready stage. Therefore, prior to submission of the paper, the authors should first register the paper on the conference support system in order to receive an ID number for the paper. Then, in order to submit the paper, the paper should be revised so that the ID number of the paper replaces the names and affiliations of the authors. The references should include published literature relevant to the paper, including previous works of the authors, though care should be taken in the style of writing in order to preserve anonymity. References to code and data intended to be published alongside the papers are to be phrased such that anonymity is preserved.
Submitted papers may not be published as open access preprints before acceptance notifications have been sent. Papers that have already been published as preprints at the time of submission for review must be flagged as such in the review system and must not reference the preprint in the paper.
Papers submitted not adhering to the page limitation or the anonymity requirements may be rejected without review.

Demonstrations

A session will be organized for the demonstration of creative, robust, and practical working applications and tools. Where a demonstration is not connected to a submitted paper, a two-page extended abstract about the system should be submitted for review, via the conference support system and following the instructions on paper submission. Accepted extended abstracts will be published in the conference proceedings. For those demonstrations that are connected to a paper in the main track, no separate statement about the demonstration need be submitted, but the author(s) should send an email to the Program Chair by the demo submission deadline to register their interest in demonstrating their work at this session.

Workshops & Tutorials

ICAIL 2023 will include workshops and tutorials on Monday, June 19 and Friday, June 23. Tutorials should cover a broad topic of relevance to the AI and Law community and should have one or more designated organizers/speakers. Workshops are intended for informal discussion and should have one or more designated organizers as well as an organizing and programming committee. Proposals must contain enough information to permit evaluation on the basis of importance, quality, and community interest. Proposals should be 2 to 4 pages and include at least the following information:
The workshop or tutorial topic and goals, their significance, and their appropriateness for ICAIL 2023
The intended audience, including the research areas from which participants may come, the likely number of participants (with some of their names, if known), and plans for publicizing the workshop
Organization of the workshop or tutorial, including the intended format (such as invited talks, presentations, panel discussions, or other methods for ensuring an interactive atmosphere) and the expected length (full day or half day)
Organizers’ details: a description of the main organizers’ background in the proposed topic; and complete addresses including web pages of all organizers and committee members (if applicable)

Proposals for workshops and tutorials can be sent by email to the program chair, Matthias Grabmair (matthias.grabmair@tum.de) by the submission deadline.

Doctoral Consortium

ICAIL 2023 will feature a Doctoral Consortium aiming to promote the exchange of ideas from PhD researchers in the area of Artificial Intelligence and Law and to provide them with an opportunity to interact and receive feedback from leading scholars and experts in the field. Details about the consortium’s program and timeline will be published separately from this call for papers.

Awards

IAAIL has established three different awards, to be presented at the conference banquet.

Donald H. Berman Award for Best Student Paper
The best student paper award is in memory of Donald H. Berman, a professor of law at Northeastern University, who was a co-founder of the Artificial Intelligence and Law journal. The award consists of a cash gift and free attendance at ICAIL 2023. For a paper to be considered for the award, the student author(s) should be clearly designated as such when the paper is submitted using the facility provided by the submission system, and any non-student co-authors should provide a statement by email to the Program Chair that affirms that the paper is primarily student work.

Carole Hafner Award for Best Paper
The best paper award is given in memory of Carole Hafner, an associate professor of computer science at Northeastern University. She was one of the founders of the ICAIL conference and a co-founding editor of the journal Artificial Intelligence and Law.

Peter Jackson Award for Best Innovative Application Paper
The best innovative application paper award is dedicated to the memory of Peter Jackson, Thomson Reuters’ Chief Research Scientist, who was a strong supporter of the ICAIL conferences and a significant contributor to the development of advanced technologies in AI and Law.