Abstract: The exponential growth of born digital government records poses a looming public policy challenge: how can archival institutions and government agencies subject to freedom of information laws provide timely access to accumulating repositories of billions of government records, while respecting sensitivities in those records that may legitimately justify restricting access to portions thereof? This is a problem of international dimension, given that all freedom of information laws contain various types of exemptions that allow for restrictions on public access. Moreover, recent policy changes initiated by the US National Archives and Records Administration to ensure that US federal agencies transition completely to electronic recordkeeping by the end of 2022 only serves to highlight the access challenges that government agencies increasingly will face in the coming decade and beyond. However, recent research applying machine learning to find exempt material within the scope of the “deliberative process privilege” embodied in US freedom of information law offers a promising tool to assist human reviewers in meeting the challenge of providing timely access. This presentation will describe in greater detail the dimensions of the public policy problem, will describe the research conducted to date using White House email records, and will suggest next steps for utilizing machine learning for the purpose of providing greater citizen access to records of government agencies.

Bio: Rajiv Shakdher, B.Com.(Hons.), C.A., LL.B.Born on 19th October, 1962. Studied in St.Columba's School, Delhi. Graduated in B.Com. (Hons.) from Delhi University in 1984. Obtained LL.B. degree from Law Faculty, University of Delhi in 1987. Enrolled as an Advocate on 19th November, 1987. Completed Chartered Accountancy from Institute of Chartered Accountants of India in 1987. Admitted as an Associate Member with the Institute of Chartered Accountants of India on 29th January, 1988. Pursued Advanced Course of Law at Institute of Advanced Legal Studies from University of London in 1994. Was designated as Senior Advocate on 8th December, 2005. Practiced in the Supreme Court of India, High Court of Delhi and other High Courts of India, Tax Tribunals, DRT, BIFR, AAIFR, MRTP and Company Law Board. Has vast experience in civil litigation, constitutional law, with special emphasis on commercial litigation, corporate and taxation laws. Was appointed as a counsel for the Union of India on 13th March, 1995 by the Government of India with respect to its cases in the High Court of Delhi. Appointed on the Senior Panel of the Union of India in the Delhi High Court on 20th July, 2004 till 20th July, 2007. Appointed in 2005 to the Union of India Panel in the Supreme Court of India. Appointed as a counsel by the office of Comptroller and Auditor General to defend IA &AD matters before CAT from 1st August, 2002 to 31st July, 2003. Appointed as a Senior Standing Counsel by office of Comptroller and Auditor General of India, to defend IA & AD cases before Delhi High Court with effect from 1st August, 2006. Appointed as Additional Judge of Delhi High Court on 11.04.2008 and became permanent Judge on 17.10.2011. Transferred to Madras High Court w.e.f. 11.04.2016.

Abstract : With Legal AI gaining more interest from Government, Industry and Academia, and with the increase in population generating and consuming digital data and services in regional languages, it is imperative to look at the prospect of offering AI enabled legal solutions in multiple regional languages. A major challenge towards this is lack of annotated data for different tasks, and especially in languages other than English. One way to prepare ourselves for the design of scalable and accurate solutions for legal services in multiple regional languages will be to focus on algorithms or frameworks that can work with multiple languages in limited/no task-specific annotated data. In this presentation, we will discuss a few approaches that can help address this challenge, and hence could be one of the stepping stones for designing AI-enabled legal services in multiple languages.

Brief Bio: Dr. Maunendra Desarkar is an Associate Professor at the Computer Science and Engineering Department at IIT Hyderabad, India. Currently, he is also serving as the Head of the Department of the AI Department at IIT Hyderabad. He received his MTech degree in Computer Science in Engineering in 2006 from IIT Kanpur and PhD in 2014 from IIT Kharagpur. In the past, he has also worked for Sybase India Private Limited and Samsung Research Institute Bangalore. His research interests are in the areas of application of Machine Learning and Artificial Intelligence in the domains of Natural Language Processing, Information Retrieval, Recommendation Systems, etc. More details about his current research, publications etc. can be found at https://people.iith.ac.in/maunendra/.

Abstract : AI (Artificial Intelligence) has the potential to transform the administration of justice in a variety of ways. Here are some of the ways AI is already being used in the administration of justice:
Predictive Policing: AI algorithms can analyze crime data and patterns to identify areas with higher crime rates, predict where crimes are likely to occur and help law enforcement to allocate resources to these areas.
Case Management: AI-powered case management tools can help judges and lawyers to manage and process cases more efficiently. This can include automating routine tasks, identifying relevant legal precedents, and providing data-driven insights into legal cases.
Legal Research: AI algorithms can be used to search and analyze legal documents, including case law and statutes, to help lawyers and judges make more informed decisions. This can save time and effort and reduce the likelihood of errors.
Sentencing and Parole Decisions: Some jurisdictions are using AI to help inform sentencing and parole decisions. By analyzing factors such as criminal history, demographic data, and other relevant information, AI algorithms can help judges make more consistent and unbiased decisions.
Access to Justice: AI-powered legal chatbots and virtual assistants can provide information and guidance to people who cannot afford a lawyer. These tools can help individuals navigate the legal system, complete legal forms, and understand their legal rights.
While AI has the potential to improve the administration of justice in many ways, there are also concerns about the ethical and legal implications of AI. For example, there are concerns about bias in AI algorithms, the potential for automation to replace human decision-making, and the need to protect individual privacy and data. As AI continues to evolve, it will be important to address these concerns and ensure that AI is used in ways that are fair, transparent, and accountable.

Brief Bio : Dr. K.V.K. Santhy is been teaching Criminal Law since 17 years, did Doctoral Thesis on “Penal Reforms in India” at Osmania University. She is the Proctor of the University and takes care of discipline on campus. She has been associated with many projects such as “Study of the Indian Penal Code from Gender Perspective” commissioned by NCW, “Law on Grievance Redressal in the Public offices in A P” by Centre for Good Governance, as Coordinator for the project to draft the Amendment Act for “Transplantation of Human Organs Act, 1994,” with National Deceased Donor Transplantation Network, Mumbai and submitted to Ministry of Health and Family Welfare coordinator of the Project “Defective Investigation leading to acquittals” commissioned by Bureau of Police Research Development, New Delhi and a UGC Major Research Project on “Sentencing perspectives in the State of Andhra Pradesh”. Delivered guest lectures on Criminal Law at NADT, Nagpur and on International Humanitarian Law - Women at ICRC, New Delhi and ASCII, Hyderabad. She is been the Co-Investigator for GIGA ( Global Internet Governance and Advocacy) an initiative of Dept of Information and technology since three years. Coordinated a three day National Workshop on “Advanced Training to teachers in the South Asian Region on International Humanitarian Law and International Criminal Law” with ICRC.

She visited Max Planck Research Institute for International Criminal Law, Germany as a part of Post Doctoral Research programme on “Punishment and Sentencing”.  Submitted report on “Counterfeit Drugs in India” to Max Planck under the Guidance of  Professor  Dr. Hans-Georg Koch. Publications: Book on “Sentencing: the use and misuse of Discretion”, “Police Torture: Legal Issues and Remedies”, “The significance of Fair Trial under Human Rights Law in matters of criminal justice: a case study of the trial of Former Iraqi Leader, Mr. Saddam Hussein”, ‘Issues in Human Rights’ Edited by Azizur Rahman, Bangladesh, “A critique of the Transplantation of Human organs Act in India”, Practical Lawyer. Participated in National and International Seminars on issues like, Community Sentence, Law on Sea Piracy, Restorative Justice in Europe, Forensic Law and Cyber Laws.

Delivered lectures in NISA, Hyderabad, NADT Nagpur, CFSL, Hyderabad, National Police Academy, Telagana Police Academy, Women and Child Welfare Department, Andhra Pradesh on issues such as cyber laws, criminal law, sentencing issues in India, Sexual harassment at work place etc

Abstract : In this talk, I will present some key findings in legal reasoning and vocabulary definition. I will start by discussing in a comparative way the main state-of-the-art legal vocabularies, and then I will show how we can make use of these vocabularies in legal technologies. To do so, I will present a low cost information extraction approach to populate legal ontologies. I will conclude my talk by arguing about the open challenges in knowledge representation and semantically enriched information extraction to achieve actually interoperable legal technologies.

Brief Bio : Serena Villata is a research director in computer science at the CNRS and she pursues her research at the I3S laboratory in Sophia Antipolis (France). Her research area is Artificial Intelligence (AI), and her current work focuses on artificial argumentation, with a specific focus on legal and medical texts, political debates and social network harmful content (abusive language, disinformation). Her work conjugates argument-based reasoning frameworks with natural language arguments extracted from text. She is the author of more than 150 scientific publications in AI. Since July 2019, she has been awarded with a Chair in Artificial Intelligence at the Interdisciplinary Institute for Artificial Intelligence 3IA Cote d’Azur on “Artificial Argumentation for Humans”. She became the Deputy Scientific Director of the 3IA Côte d'Azur Institute in January 2021. Since December 2019, she is a member of the National Committee for Digital Ethics (CNPEN).

Abstract : One branch of legal technology that holds particular promise is access to justice (“A2J”) through the use of online dispute resolution (“ODR”). This is because ODR uses technology to enable online claim diagnosis, negotiation, and mediation without the time, money, and stress of traditional court processes. Indeed, courts are now moving traffic ticket, landlord-tenant, personal injury, debt collection, and even divorce claims online.

The hope is that legal technology such as online triage and dispute resolution systems will provide means for obtaining remedies for self-represented litigants (“SRLs”) and those who cannot otherwise afford traditional litigation. Meanwhile, the COVID-19 pandemic has accelerated the growth of online processes, including court and administrative processes that traditionally occurred in person. Nonetheless, these online processes seem focused mainly on case management and communication, neglecting the need for more imaginative and innovative uses of technology.

We propose a six-module system for ODR programs and identifies gaps in development where new technologies are needed to advance A2J.

Brief Bio : Professor John Zeleznikow is a Professor of Law and Technology at  La Trobe University Law School in Bundoora, Australia.  Prior to this position he was a Professor of Information Systems at the Victoria University Business School and Director of the Joseph Bell Centre for Forensic Statistics and Legal Reasoning at the University of Edinburgh Law School.  

He has conducted research for 50 years, in Australia, USA, France, Netherlands, Israel, Scotland, Spain, Poland and Estonia.  He has received over $A8,000,000 in research grants: from the Australian Research Council, European Union, Scottish Higher Education Funding Authority, French Scientific Council and Dutch Scientific Council.  Twenty of his PHD students have graduated.

He has published four research monographs (including Cambridge University Press) and one hundred refereed journal articles (including Harvard Negotiation Law Review) as well as over two hundred refereed conference articles and book chapters.  He has performed pioneering research on using machine learning and game theory to support legal decision making.

In 1996, his Spit-Up system, which used machine learning to predict the distribution of marital property following divorce, received international recognition when it was applied to the Divorce of Prince Charles and Lady Di.  The London Daily Telegraph, in a front page article on July 4 1996, had as its headline Aussie Computer kind to Lady Di.    - see   ‘Computer Divorce’ (Youtube, 26 April 2020) <https://youtu.be/u7A3H4lUjzM>

In November 2005, his Family-Winner software, which assisted separating parents to negotiate their property disputes through the use of trade-offs won its heat of the ABC TV New Inventors program. – see https://www.youtube.com/watch?v=YOZczuvrou4

Abstract : Legal Prompt Engineering (LPE) or Legal Prompting is a process to guide and assist a large language model (LLM) with performing a natural legal language processing (NLLP) skill. Our goal is to use LPE with LLMs over long legal documents for the Legal Judgement Prediction (LJP) task. We investigate the performance of zero-shot LPE for given facts in case-texts from the European Court of Human Rights (in English) and the Federal Supreme Court of Switzerland (in German, French and Italian). Our results show that zero-shot LPE is better compared to the baselines, but it still falls short compared to current state of the art supervised approaches. Nevertheless, the results are important, since there was 1) no explicit domain-specific data used — so we show that the transfer to the legal domain is possible for general-purpose LLMs, and 2) the LLMs where directly applied without any further training or fine-tuning — which in turn saves immensely in terms of additional computational costs.

Brief Bio :  Mohit is a Manager, Applied AI Research at TR labs. He has over 9 years’ experience in Machine Learning, Deep Learning and Natural Language Processing. Prior to that, he completed his Masters in Quantitative Economics from the Indian Statistical Institute in 2013.
His experience spans across multiple domains - Finance, Investment, Banking, Legal & Taxation. His primary expertise is in NLP with a focus on delivering projects involving - Named Entity Recognition, Summarization, Text Classification, Q&A, Topic Modeling, Translation & Transduction. At TR, his focus has been on solving long-text, long tailed, multilabel text modeling tasks & contributing towards research in the same direction. Prior to his current stint with TR, he has worked with MSCI where his work involved building Q&A models for interaction with clients, NER models to extract corporate event data from news articles and ML based Thematic Indices. Before MSCI, he worked at American Express where he was responsible for building, deploying and managing ML models for predicting Fraud and Credit Default. He has extensive experience in technical evaluation, hiring, building and managing data-science teams across organisations.

Abstract : Artificial Intelligence (AI) is a hot topic, also within policing. Many police forces are implementing predictive policing systems, where crime in certain neighbourhoods is predicted so that the police can divide their resources more efficiently. However, the use of AI in the context of law enforcement is also a contentious topic, with especially predictive policing coming under fire due to its association with biased and discriminatory police practices. Furthermore, the technically simple predictive policing systems in current use do not realise AI’s full potential. At the Netherlands National Police Lab AI, we research, develop and evaluate state-of-the-art AI systems for the Netherlands police with a team of researchers from different backgrounds. In this talk I will discuss some of these systems – e.g. for combating online web fraud, for searching through large datasets, and for gaining insights in criminal markets – in detail, and demonstrate how only the combination of insights from different disciplines can lead to responsible AI

Bio : Floris Bex is Associate Professor of AI at Utrecht University, and full Professor of Data Science and the Judiciary at Tilburg University. At Utrecht University, Floris leads the National Police Lab AI. He has a PhD in AI & Law, and his research focuses on AI techniques (mainly argumentation and NLP) for law enforcement and the legal field, as well as on legal and societal aspects of such AI systems.

Abstract : TBD

Brief Bio : Daniel W. Linna Jr. has a joint appointment at Northwestern Pritzker School of Law and McCormick School of Engineering as a Senior Lecturer and the Director of Law and Technology Initiatives. Dan’s teaching and research focus on innovation and technology, including computational law, artificial intelligence, data analytics, leadership, operations, and innovation frameworks. Dan is also an affiliated faculty member at CodeX — The Stanford Center for Legal Informatics. Dan received his BA from the University of Michigan, received a second BA and an MA in public policy and administration from Michigan State University, and graduated magna cum laude, Order of the Coif from the University of Michigan Law School. Dan began his legal career with a one-year judicial clerkship for U.S. Court of Appeals Judge James L. Ryan. After his clerkship, he joined Honigman Miller Schwartz and Cohn, where he was elected equity partner in 2013. Before law school, Dan was an information technology manager, developer, and consultant.

Abstract : Time is the essence for a good justice delivery system and demands appropriate planning and strategy for the access to the judiciary. The pendency of cases, at all levels, has jeopardized the rights of access to justice. The huge pendency of the cases results from insufficien infrastructure, inadequate manpower and inefficient court management system. The realization of the right warrants all-pronged strategy and should not wait for incremental improvement of the system. Technology-led innovation has been projected a promising tool to reduce the pendency. The initiatives like e-filing and e-notice have introduced the interface between technology and judicial process. It has further got up-scaled with the conduct of proceedings through video-conferencing during pandemic which has now resulted into the demand of regular live streaming of the judicial hearings.
The innovation in technology in the form of Artificial Intelligence presents opportunities to smoothen the judicial functioning and ease the burden of judiciary. Artificial Intelligence (AI) techniques, like machine learning, natural language processing, expert systems, and predictive analytics, holds the potential to restructure the justice delivery process and improve the administration & governance of law in the society. Integrating AI into judicial system requires digitalisation of Courts and online repository of courts documentation. AI technologies promises to facilitate court-processes, improve judge-case ratio, assist lawyers in giving their clients AI based prediction of case outcomes, and speedy disposal of cases, and much more. The author will discuss the potential of the artificial intelligence in making the judicial system effective and efficient and advancing the cause of access to justice for individual. Further, it will also examine the efficacy of non-human driven judicial process. Finally, it will build an argument of transforming e-courts to e-justice system for the fulfillment the goal of access to justice for all.

Brief Bio : Prof. Uday Shankar is Registrar & Professor of Law at Hidayatullah National Law University, Raipur. He has been teaching and researching in law for more than 20 years. He has served as guest professor under Magdalene Schoch Fellowship awarded by the Faculty of Law, University of Hamburg in the year 2016 and recipient of the prestigious fellowship from the Max-Planck Institute of Comparative Public Law and International Law, Heidelberg in the year 2008. He is a Member of International Association of Constitutional Law. He is a Life Member of Indian Law Institute, Delhi. More than 50 of his academic writings are published in journals and edited books. He has presented papers and delivered invited talks in more than 80 conferences in India and abroad. His research work on interface between technology and judicial system has been published in the prestigious journals namely Journal of Indian Law Institute, World Constitution Study and Legal Knowledge and Information Systems. His course on Introduction to Law on Electricity is offered under the scheme of National Programme on Technology Enhanced Learning (NPTEL), project funded by the Ministry of Education, Government of India. He has organized GIAN Course on Energy Law and Policy and Short Term Courses on Labour Law and Make in India/Skill India. He sits on the editorial boards or advisory boards of journals published by the National Law Universities/Law Colleges in India. He is a Director (Asia) of the Global Network of Human Rights and the Environment. He is also leading the Ambassdor’s Programme of Max Planck Alumni Association.

Abstract : The legal industry is moving towards standardizing terminology to simplify and improve the delivery of legal services by providing greater transparency and increasing the effectiveness of budgeting and resourcing. Providing a common language for the legal industry in India serves as the catalyst for better outcomes and value for helping new entities using AI/ML tools that aligns with a vision for a future of data-driven law and legal solutions.