The workshop will provide a venue for these issues in the form of a number of accepted ideation, application, and research papers, as well as an industry panel, and two keynote speakers (one from the perspective of AI, the other from the perspective of IA (Intelligent Assistance). Many of the artifacts of the workshop are contained in this volume published by CEUR-WS (see below for additional publication information).
13:00 – 14:00 Lunch
14:00 – Afternoon Keynote: Introduction: Dan Linna
“Legal Expertise Meets Artificial Intelligence: A Critical Analysis of Large Language Models as Intelligent Assistance Technology” 14:50 – Q&A Session led by Dan Linna 15:00 – Using ChatGPT for the FOIA Exemption 5 Deliberative Process Privilege
Jason R. Baron, Nathaniel W. Rollings, Douglas W. Oard 15:30 – 16:00 Coffee Break 16:00 – Strengthening the AI Operating Environment: Distributed Competence as a Means to Risk Mitigation
Bruce Hedin, Samuel Curtis 16:20 – Some Practical Analyses of the Judgment Documents of Labor Litigations for Social Conflicts and Similar Cases
Chao-Lin Liu, Yi-Fan Liu
16:45 – 17:30 – Panel Topic: The Future of AI & Law and the Impact of Generative AI
• Jack Conrad (Thomson Reuters)
• Pablo Arredondo (Casetext) • Uwais Iqbal (Simplexico) • Megan Ma (Stanford Law & CodeX) • Laura Skylaki (Thomson Reuters)
Topics: See below 18:00 – END _______________________________________________ 19:00 – Conference Welcome Reception
• University of Minho Rectory Garden, Largo do Paço, 4704-553 Braga Additional details on the program:
• Hype about Generative AI and Intelligence Augmentation shows no sign of slowing. Abundant examples illustrate how these technologies are transforming industries. What about the legal industry? While Generative AI is revolutionizing the field, will this capability transform other aspects of legal services? This panel brings together industry experts to discuss how legal services organizations are making the most of data analytics, Artificial Intelligence, and Intelligent Assistance. Our panelists will discuss bridging the gap between strategy and implementing these technologies, the need for interdisciplinary teams, high-impact tools today, the challenges, and where they see these state-of-the-art technologies having the greatest impact in the near-term and in the long-term. • Session Description: This panel discussion will be 45 minutes long, followed by 15 minutes of Q&A. This panel session begins with the moderator introducing the speakers followed by each of our four speakers giving a 2-minute overview of their current perspective into seminal areas of the Legal AI and IA field (10 minutes). Following these introductions, the panel moderator will pose to the various members, depending on their specializations, a series of formative questions which they will be given the opportunity to answer (35 minutes). We conclude the panel session with questions from audience (15 minutes).
Illustrative Questions 1. Given the rapid advancements in AI and its potential to automate certain legal tasks, what are the implications for the future of legal employment? How can we ensure a smooth transition for legal professionals while harnessing the benefits of AI? 2. In light of the biases and limitations present in training data, how can we mitigate the risks of algorithmic bias in legal decision-making processes when using LLMs? What steps can be taken to ensure fairness and equity? 3. How can LLMs contribute to the development of predictive analytics in legal contexts, such as case outcome prediction or legal risk assessment? What are the potential challenges and limitations in this area? 4. What are the privacy and data protection concerns associated with the use of LLMs in legal practice? How can we strike a balance between the need for data access and protection of individuals' privacy rights? 5. How can LLMs be used to enhance access to justice and bridge the justice gap? Are there any specific legal domains or regions where the impact of LLMs can be particularly significant? 6. How can we ensure the explainability and interpretability of LLM-based legal systems to gain stakeholders' trust and enable effective decision-making? What methods and techniques can be employed to make LLMs more transparent?
What are the potential regulatory and policy considerations surrounding the use of LLMs in the legal domain? How can policymakers and legal practitioners collaborate to establish appropriate guidelines and frameworks? How can collaboration between legal professionals and AI experts be fostered to maximize the benefits of LLMs in the field of law? What are the best practices for interdisciplinary collaboration between the two domains? The organizing committee would like to sincerely thank all authors for their submissions and participation in the workshop, the program committee for its all-important task of reviewing, the keynote speakers and panelists for their time and preparation, and the workshop attendees for their active participation.
Jack G. Conrad, Thomson Reuters (co-chair) Daniel W. Linna, Jr., Northwestern University (co-chair) Jason R. Baron, University of Maryland, College Park Hans Henseler, University of Applied Sciences Leiden and Netherlands Forensics Institute Paheli Bhattacharya, IIT – Kharagpur Aileen Nielsen, ETH - Zurich Jyothi Vinjumur, CBRE Jeremy Pickens, Redgrave Data Amanda Jones, Lighthouse
Apoorv Agarwal, Relativity Evangelos Kanoulas, Informatics Institute, University of Amsterdam David Lewis, Redgrave Data Douglas W. Oard, University of Maryland, College Park Fabrizio Sebastiani, Italian National Research Council Antigone Peyton, Ridgeline International Amy Sellers, Cardinal Health Gineke Wiggers, Leiden University Adam Roegiest, Zuma Eugene Yang, Johns Hopkins (post-doc) These proceedings are published online by the LegalAIIA Organizing Committee as CEUR Workshop Proceedings http://ceur-ws.org Copyright © 2023 for the individual papers by the papers' authors.
Copyright © 2023 for the volume as a collection by its editors.
This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).
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