The Justice Technology Review is a peer-reviewed, open-access journal that publishes research grounded in evidence on technology and innovation in the justice system. The journal operates as an arXiv and SSRN overlay, meaning that papers are hosted on preprint servers while the journal provides rigorous peer review and a curated index of accepted work. There are no article processing charges, and all published work is freely available under a Creative Commons CC-BY 4.0 license.
The journal uses the ACM sigconf format familiar to the ICAIL and JURIX communities, and targets a turnaround of 45 to 60 days from submission to first editorial decision. Papers are published on a rolling basis and grouped into two issues per year.
The Justice Technology Review publishes research grounded in evidence on how technological interventions are designed, tested, deployed, and evaluated in the pursuit of access to justice. The journal covers AI tools, digital platforms, online dispute resolution systems, NLP applications, guided interviews, automated document assembly, and other innovations in courts and legal services.
We welcome work at every stage of the research and development lifecycle — from scoping studies and needs assessments to usability testing, pilot evaluations, and summative impact analyses. Evidence may be quantitative, qualitative, or mixed methods. What matters is that claims are grounded in systematically gathered observations from real-world justice contexts, not in theory or system descriptions alone.
The field of justice technology is generating interventions faster than it is studying them. Courts, legal aid organizations, and technologists are building tools at scale, but there is no dedicated venue for the careful, evidence-based work needed to understand what actually works, for whom, and under what conditions. The Justice Technology Review exists to fill that gap.
As an overlay journal, the Justice Technology Review does not host papers directly. Instead, arXiv and SSRN serve as the publication infrastructure, and the journal provides fast, rigorous peer review alongside a curated index of accepted work. The journal is pursuing listing in DOAJ and Scopus.
The journal maintains a formal pipeline from the ICAIL and JURIX workshop series. Each year, the editors identify the strongest workshop papers and invite their authors to submit expanded versions, providing a clear path from workshop presentation to full, citable, indexed publication.
There are no article processing charges. The journal is free to publish in and free to read, and it will remain that way.
Papers with minor revisions move from initial submission to final publication in approximately nine weeks.
The journal publishes two named issues per year, with individual papers appearing online as soon as they are accepted.
Margaret Hagan is the Executive Director of the Stanford Legal Design Lab at Stanford Law School, where she leads research and infrastructure-building at the intersection of legal design, access to justice, and AI. She is the author of Rituals for Work (Wiley) and directs work on legal help technology evaluation, court innovation, and justice system design.
Quinten Steenhuis is the co-director of Suffolk University Law School’s Legal Innovation and Technology Lab and founder and CEO of Lemma Legal Consulting. At Suffolk, he leads the Document Assembly Line project that builds and maintains CourtFormsOnline.org. His work focuses on closing the access to justice gap with technology, especially interactive tools that help people who cannot afford an attorney, including generative AI tools. He has expertise in testing and validating AI applications for safety and quality.
Hannes Westermann is Assistant Professor of Law and Artificial Intelligence at Maastricht University and the Maastricht Law and Tech Lab. His research explores whether and how artificial intelligence can perform legal reasoning, and how AI and generative AI can be used to improve access to justice. He obtained his PhD from the Université de Montréal and the Cyberjustice Laboratory, where he developed JusticeBot, an AI platform providing legal information to laypeople that has been used over 50,000 times. He was awarded the Best Paper Award at JURIX 2020 and 2023.
Interested in serving as a reviewer? Join the editorial board.
Editorial board members review 2–3 papers per year and help shape the journal's direction. Board members are drawn from across computer science, law, design, and practice.
Stanford Legal Design Lab, Stanford Law School
Human-centered legal design, access to justice innovation, legal technology, user-centered research and evaluation methods
DIKE Research Group, Vrije Universiteit Brussel & ALMA AI, University of Bologna
AI and law, justice technology, legal NLP, LLMs and access to justice, EU digital regulation, dispute resolution
Vrije Universiteit Brussel (VUB), Co-Director, DIKE Research Group on Digitalisation and Access to Justice
Online dispute resolution, digitalization and access to justice, EU legal technology
Additional board members are being confirmed and will be listed here as they join.
Two reviewers evaluate the paper using a structured review form, with a target of 45 to 60 days to the first decision.
The journal uses the ACM sigconf template, which is the same format used for ICAIL and JURIX proceedings. Authors familiar with those venues will not need to learn a new template.
\documentclass[sigconf]{acmart}. The template is available on Overleaf or as a direct download from ACM.Reviewers evaluate each submission on five dimensions:
The Justice Technology Review uses a single-blind peer review process. Authors are identified to reviewers, but reviewers remain anonymous to authors. Each submitted paper passes through the following stages:
Desk review (1–2 weeks): A handling editor reviews each submission for scope, minimum quality, and formatting compliance. Papers that are clearly out of scope, that lack any grounding in evidence from real-world justice contexts, or that contain unverified references are desk rejected at this stage without external review.
External peer review (4–6 weeks): Papers that pass desk review are assigned to two independent external reviewers with expertise in the paper's subject area. Reviewers are selected from the journal's editorial board and broader reviewer pool. Each reviewer completes a structured review form evaluating the paper on evidentiary rigor, practical relevance, clarity, reproducibility, and contribution. If the two reviewers reach substantially different conclusions, a third reviewer is assigned.
Editorial decision (1 week): The handling editor considers the reviewer reports and makes a recommendation. The possible decisions are Accept, Minor Revisions, Major Revisions, or Reject. For split decisions, the co-editors discuss and reach a consensus.
Revision (2–6 weeks): Authors revise their paper on arXiv or SSRN and notify the editor. For minor revisions, the handling editor verifies the changes. For major revisions, the revised paper is returned to the original reviewers. The journal allows a maximum of one major revision cycle per submission.
Target timeline: The journal aims for a first editorial decision within 45 to 60 days of submission. The total time from submission to publication for a paper with minor revisions is approximately 8 to 10 weeks.
Ready to submit your paper?
Submit a Paper →The Justice Technology Review studies AI in justice systems, and the editors recognize that AI tools can genuinely improve the quality and accessibility of scholarly work. At the same time, the journal is committed to the integrity, accuracy, and authenticity of published research. The policy below is built on three principles.
Human authors are responsible for every claim, every data point, and every reference in a published paper. AI tools cannot be listed as authors because authorship requires accountability that only humans can provide.
Authors may use AI to assist with drafting, editing, coding, and analysis. They may not delegate intellectual responsibility to an AI system. Every AI-assisted output must be carefully reviewed, verified, and approved by the human authors before submission.
The journal requires disclosure of significant AI use, not because AI assistance is something to be ashamed of, but because transparency is a core value of open science. Readers deserve to know how a paper was produced.
The following uses are considered equivalent to standard software tools and do not need to be disclosed:
The following uses are permitted but must be described in the paper's AI Use Statement:
The following practices are prohibited:
Every submission must include an AI Use Statement immediately before the references section, regardless of whether AI was used in preparing the paper. The statement should identify which tools were used, describe how they were used, and explain what verification the authors performed. If no AI tools were used substantively, the statement should say so. The journal will provide example statements on its author guidelines page.
The Justice Technology Review is committed to maintaining the highest standards of publication ethics. The journal follows the guidelines established by the Committee on Publication Ethics (COPE) and adheres to the Principles of Transparency and Best Practice in Scholarly Publishing.
The Justice Technology Review is a fully open-access journal. All published content is immediately and freely available to anyone, anywhere in the world, without registration, subscription, or embargo. The journal does not charge article processing charges (APCs) or any other fees to authors. There are no charges to readers.
This policy is permanent and will not change.
All articles are published under the Creative Commons Attribution 4.0 International License (CC-BY 4.0). Authors retain full copyright of their work. Under this license, anyone may copy, distribute, and adapt the work for any purpose, including commercial use, provided that proper attribution is given to the original authors and the source is cited.
The journal does not require authors to transfer copyright or assign exclusive rights to the publisher.
All submissions are expected to be original work. The journal does not tolerate plagiarism, fabrication, or falsification of data. If plagiarism or data fabrication is suspected at any stage, the editors will investigate following COPE flowcharts for handling allegations of misconduct. Confirmed cases may result in rejection, retraction, and notification of the authors' institutions.
Authors must properly cite all prior work on which their submission builds, including their own previously published work. Self-plagiarism and duplicate submission are not permitted.
All authors must disclose any financial, institutional, or personal relationships that could be perceived as influencing their research. Editors and reviewers must recuse themselves from handling any paper where they have a conflict of interest, including papers by current collaborators, colleagues at the same institution, or former advisors and advisees.
The journal's editors will not handle papers in which they are authors. Such papers will be managed by a guest editor who is independent of the editorial team.
If significant errors are discovered in a published paper, the journal will issue a correction notice linked to the original paper. If the errors are sufficiently serious to undermine the paper's findings, or if ethical violations are confirmed, the paper may be retracted in accordance with COPE retraction guidelines. Retraction notices will clearly state the reason for retraction and will be permanently linked to the original record.
Authors who wish to appeal an editorial decision should submit a written appeal to the co-editors-in-chief within 30 days of the decision, explaining the grounds for appeal. Appeals are considered by a co-editor who was not involved in the original decision. The journal aims to resolve appeals within 30 days.
Complaints about any aspect of the journal's editorial or publication practices may be directed to legaldesignlab@law.stanford.edu. The editors will investigate and respond within 30 days.
As an overlay journal, the Justice Technology Review relies on arXiv and SSRN as its primary archiving infrastructure. Both repositories are established, long-term scholarly archives. arXiv is supported by Cornell University and the Simons Foundation. SSRN is operated by Elsevier.
The journal website maintains a complete index of all published papers with metadata and links to the archived versions.
To maintain editorial independence and credibility, the journal monitors the proportion of published papers in which an author is also an editor, editorial board member, or reviewer. This proportion will not exceed 25% of the articles published in any issue or calendar year, in accordance with DOAJ guidelines. All papers authored by editorial team members are handled by an independent guest editor and undergo the same peer review process as any other submission.
The journal is currently recruiting editorial board members, peer reviewers, and its first authors. If you work on justice technology from any discipline — computer science, law, design, public policy, or practice — we would welcome your involvement.
Questions? Email legaldesignlab@law.stanford.edu