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ICAIL 2027 – First Call For Papers
22nd International Conference on Artificial Intelligence and Law
(40th Anniversary Edition)

Vienna, Austria | 5 – 9 July 2027
https://icail-vienna-2027.org/
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Important dates:

* Workshop/Tutorial proposals: 11 December 2026
* Paper submission deadline: 28 January 2027
* Rebuttal period: 18 - 25 March 2027
* Notification of acceptance: 19 April 2027
* Camera-ready papers due: 26 April 2027


Organization
===============

Venue: University of Vienna
Program Chair: Giovanni Sileno (University of Amsterdam), g.sileno@uva.nl
Local Chairs: Stefan Eder (University of Vienna), Erich Schweighofer (University of Vienna), Agata Ciabattoni (TU Wien), Sabrina Kirrane (WU Wien)

International Association for Artificial Intelligence and Law (IAAIL)
President: Adam Wyner
Secretary/Treasurer: Michał Araszkiewicz

The mission of IAAIL and ICAIL is to foster, promote, and disseminate high quality academic research on Artificial Intelligence and Law. Further information at https://iaail.org/


About ICAIL
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Since 1987, the International Conference on Artificial Intelligence and Law (ICAIL) has been the foremost global conference addressing research at the intersection of artificial intelligence and law. It is organized under the auspices of the International Association for Artificial Intelligence and Law (IAAIL), https://iaail.org/. In 2025, the conference changed from a biennial to an annual schedule. The 22nd edition will coincide with the 40th anniversary of the ICAIL series and will take place in Vienna, Austria.


Call for Papers
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We invite submissions of original research papers on Artificial Intelligence and Law, covering foundations, concepts, methods, systems, tools, and applications. Topics of interest include, but are not limited to, the following:

1. Foundations, Knowledge Representation, and Computational Legal Theory

- Logic and argumentation: Deontic and potestative logics, defeasible reasoning, argumentation frameworks, and models of normative conflict.
- Normative modeling: Formal or conceptual modeling of fundamental legal aspects (e.g., normative positions, causation, responsibility, legal qualification, …).
- Rule- and case-based reasoning: Formal and computational models of rule-based, case-based, evidential and value-based reasoning.
- Agent systems and norm emergence: Normative reasoning by autonomous agents, normative multi-agent systems, computational social science in law, complex adaptive systems modeling of legal ecosystems.
- Neuro-symbolic integration: Approaches merging deep learning with symbolic legal knowledge representation and hybrid reasoning models, e.g. autoformalization of natural language legal texts into computable logic or DSLs.
- Ontologies and standards: Formal models of norms, legal ontologies, semantic web mark-up languages, open linked data, and legal data standards/interoperability schemas.

2. Legal Data Science, Information Retrieval, and Generative AI

- Legal NLP: Precedent-aware Named Entity Recognition, semantic role labeling, multilingual legal corpora, parsing of legal text, information extraction from text.
- Information retrieval, search, and network analysis: Legal information retrieval, semantic search, recommender systems, and structural network analysis of legal systems (e.g., statutory citation graphs, court precedent network topology, and topological data analysis of legal corpora).
- Argument mining: Argument mining on unstructured legal texts and automated information extraction from legal databases.
- Predictive analytics and other empirical methods: Predictive legal analytics, multi-modal legal data processing, and empirical machine learning methods applied to statutory and case law.
- Generative AI, evaluation and verification: LLM applications tailored for complex legal reasoning and synthesis, accompanied by rigorous evaluation pipelines, legal benchmarking, hallucination management, and verification methods.

3. Technical Governance, Legal Risk Analysis, and Normative Alignment

- Regulatory compliance engineering: Formal and technical compliance-checking systems, logic-based verification, and runtime compliance for dynamic digital and AI regulatory environments (e.g., automated adherence to legal frameworks, end-to-end compliance architectures).
- Algorithmic fairness and bias: Bias assessment, fairness metrics, and non-discrimination design embedded in legal, judicial, and administrative tools.
- Law-based AI safety, alignment and guardrails: risk mitigation, model guardrails, norm-aware reinforcement learning, and law-following agent architectures designed to operate within legal constraints.
- Legal risk assessment and audibility: Automated legal risk assessment, exposure modeling, liability allocation, and Explainable AI (XAI) for judicial/administrative accountability and audibility.
- Accountability operationalization: Operationalization strategies for meaningful human control or other accountability frameworks, integrating normative systems, legal accountability, and human oversight into high-stakes automated decisions.

4. Legal Technologies

- Hybrid intelligence workflows: Human-in-the-loop, human-on-the-loop, and other relevant legal workflow systems for judges, attorneys, legal practitioners, and other relevant stakeholders.
- Access to Justice (A2J) and public interest tech: AI-driven A2J tools, public interest legal technologies, and participatory data infrastructures.
- Rules as Code and E-Government: Automation of the state, computational governance ("Rules as Code"), and e-justice/e-democracy platforms.
- Dispute resolution and negotiation: Computer-assisted and online dispute resolution (ODR), computational negotiation methods, and automated contract formation.
- Smart contracts and distributed ledgers: Formal, computational, and jurisprudential challenges of smart contracts, DAOs, and decentralized dispute resolution.
- Legal process, forensics and education: Legal process mining, digital forensics, evidence evaluation technology, and intelligent legal tutoring systems.


Paper Submission
=================

Paper Length:

- Long papers: up to 10 pages, including references.
- Short papers: up to 5 pages, including references.
- Demonstrations (Extended abstracts): up to 2 pages, including references.

Scope
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Submissions must present contributions on relevant topics for AI & Law as those enlisted above. To maintain ICAIL’s characterization within the broader, rapidly moving field at the intersection of Law and Artificial Intelligence, we will NOT accept submissions focused exclusively on the regulation of technology, policy, or legal doctrine. However, we welcome papers engaging in scholarly elaborations on legal concepts, reasoning or processes when framed within a computation-oriented or technical context. We will also NOT accept papers merely applying off-the-shelf LLMs to hand-picked simplistic cases, lacking systematic, rigorous methodology, scalable benchmarking, and legal-domain analytical depth.

Guidelines
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Authors must include a clear statement detailing the novel scientific contribution of the work. The relationship to prior work (including in AI & Law venues such as ICAIL, JURIX, and the Artificial Intelligence and Law journal) must be thoroughly developed. Papers should feature an adequate discussion comparing their findings to prior work.

Depending on the type of paper, additional guidelines apply:

- Formal or computational models: Papers should include concrete examples (e.g., a sound use case, a realistic legal conflict or a genuine statutory nuance) or reproducible simulations. Authors should provide clear syntax, semantics, and, where applicable, proof sketches or theoretical evaluations of relevant properties.

- Data mining, Machine Learning, & Generative AI: Papers must go beyond merely reporting metrics. They should include discussions on relevant (legal) background, data, methodology, results, and analysis. Evaluations should use authentic, uncurated, or multi-jurisdictional legal data (e.g., actual case law, messy contracts, administrative filings) rather than purely synthetic or overly sanitized benchmark subsets.

- Applications: Papers must clearly describe motivations, techniques, implementation, and evaluation (user-centred, technical, or other).

- Human evaluations: When human evaluation is involved, annotations must be performed or validated by qualified legal professionals, and inter-annotator agreement (e.g., Cohen's or Fleiss' Kappa) must be reported.

Reproducibility
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Authors are highly recommended to publish on open repositories their code, data (including schemas), and (non-confidential) prompting templates alongside their submissions. Studies utilizing proprietary, closed-source LLMs (e.g., commercial APIs) should benchmark their performance against at least one open-weights, publicly available model of comparable scale under identical evaluation conditions. Program committee members are instructed to take reproducibility into account during their reviews, besides the previous guidelines.

Double-Anonymized Review Process
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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). Prior to submission, authors must first register the paper on the conference support system to receive an ID number. The paper must then be revised so that the paper ID replaces the names and affiliations of the authors. References should include relevant published literature (including previous works by the authors), ensuring the writing style preserves anonymity. References to code and data intended for publication must also be phrased to maintain anonymity (e.g. using anonymous GitHub services or OSF links).

Format and submission
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Papers must be formatted using the ACM sigconf template (for LaTeX) or the interim template layout.docx (for Word), both at https://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 (including page limitations or the anonymity requirements) may be rejected without review. Submissions should be uploaded to the conference support system by the submission deadline; see the conference website for further information. Submitted papers may not be published as open access preprints before acceptance notifications have been sent.

Registration and Participation
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At least one author of an accepted paper must register for the conference to be included in presentation and publication in proceedings. ICAIL 2027 is an in-presence event; remote participation is accepted only under exceptional circumstances. At least one author of an accepted paper must present the work at the conference in person.

Open Access Publication
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ICAIL proceedings have traditionally been published by ACM in their conference proceedings series. As of 2026, all conference papers published by ACM are subject to mandatory Open Access requirements.

Important note on Open Access fees: The Open Access fee is not included in the conference registration fee, nor is it sponsored by the IAAIL. However, most universities have agreements in place with ACM for waiving the Open Access fee (see the ACM Open participants list). If none of the paper's authors are affiliated with an institution that has an ACM Open agreement, they will be responsible for covering the fee. (Temporary ACM subsidies or hardship waivers may sometimes apply depending on your region; please check directly with ACM if you think this applies to you, see e.g. https://www.acm.org/publications/policies/policy-on-open-access-apc-waivers-and-discounts)


Ethics and policies
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Use of Generative AI tools to draft papers: For ICAIL 2027, we adhere to the principles and guidelines included in the ACM Policy on Authorship specifically about “Criteria for Authorship” regarding the use of Generative AI technologies for authoring papers: “Generative AI tools and technologies, such as ChatGPT, may not be listed as authors of an ACM published Work. The use of generative AI tools and technologies to create content is permitted but must be fully disclosed in the Work. For example, the authors could include the following statement in the Acknowledgements section of the Work: ChatGPT was utilized to generate sections of this Work, including text, tables, graphs, code, data, citations, etc.. If you are uncertain about the need to disclose the use of a particular tool, err on the side of caution, and include a disclosure in the acknowledgements section of the Work. (…) Basic word processing systems that recommend and insert replacement text, perform spelling or grammar checks and corrections, or systems that do language translations are to be considered exceptions to this disclosure requirement and are generally permitted and need not be disclosed in the Work. As the line between Generative AI tools and basic word processing systems like MS-Word or Grammarly becomes blurred, this Policy will be updated.”

Authorship
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All individuals, and only those, who have made significant contributions to a paper should be listed as authors in the submission system. We will NOT permit adding or removing authors to a paper after the submission deadline. Please also ensure that the order of authors is correct at submission time. Disputes about authorship and misconduct should be negotiated and resolved by the parties to the dispute. IAAIL and ICAIL do not accept responsibility to adjudicate or resolve any such disputes.

Ethics & Compliance
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Research reported at ICAIL must adhere to high standards of academic integrity, honesty, and trustworthiness, including the prevention of harm, data falsification, and plagiarism, while respecting privacy, fairness, and intellectual property. Submissions are subject to all applicable ACM Publications Policies and Code of Ethics. Submitting a work to the conference implies acceptance of all conditions outlined in this call for papers.

Paper Assessment
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Decisions regarding the acceptance or rejection of a paper fall under the exclusive responsibility of the Program Chair, who has the final say. No disputes will be admitted.


Doctoral consortium
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The Trevor Bench-Capon Doctoral Consortium aims 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. Since 2025, the Doctoral Consortium bears the name of Trevor Bench-Capon, one of the pillars of the AI and Law community, who was one of the greatest supporters of the DC initiative.


Karl Branting Industry meeting
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The Karl Branting Industry Meeting is a dedicated industry session at ICAIL aimed at bridging the gap between academic research and commercial applications in legal technology. The session serves as a platform for industry leaders, corporate researchers, and legal-tech providers to share practical insights, deployment challenges, and enterprise-level innovations within an academic and research-centred setting. It typically features short presentations, panel discussions, and updates from major legal tech organizations, alongside open discussions with academic researchers. If you are interested in participating, please contact the organizers.


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

Donald H. Berman Award for Best Student Paper
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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 2028. 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
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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
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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.


Relevant dates
=================

Workshop and Tutorial proposals submission: 11 December 2026
Paper submission deadline: 28 January 2027
Rebuttal period: 18 - 25 March 2027
Notification of acceptance: 19 April 2027
ACM metadata reporting deadline: 23 April 2027
Camera ready papers due: 26 April 2027
Conference: 5 – 9 July 2027