Keynote Talk #1 (Morning): 

Dr. Kristian J. Hammond, Professor at Northwestern University

Dr. Kristian J. Hammond is the Bill and Cathy Osborn Professor of Computer Science at Northwestern University and the co-founder of the Artificial Intelligence company Narrative Science. He has spent most of his career focused on the problem of making machines smarter. Since the fall of 2016, he has been the faculty lead of Northwestern’s CS + X initiative, exploring how computational thinking can be used to transform fields such as the law, medicine, and education. Most recently, he has taken on the role of directing Northwestern’s Master of Science in Artificial Intelligence. Kris’s primary research is at the inter- section of data analytics and human/machine communication. He works on computational methods for interpreting user needs, translating those needs into machine executable queries and analysis, and then mapping the results into natural language. His vision is to automate the relationship between business goals and data science in an effort to scale the link between the data that serves us and the language we need to understand it. Kris believes in humanizing computers with the aim of stopping the process of mechanizing people.

Title: Law, Language, and AI: Integrating Fluency and Truth


 Artificial intelligence (AI) is reshaping numerous industries, and one of the most impactful developments in this landscape has been the rise of generative AI systems such as ChatGPT. Powered by a unique blend of machine learning and natural language processing capabilities, ChatGPT has emerged as a transformative technology that has redefined the realm of human-computer interaction. 

The impact of this technology is far reaching and differs from what we have seen before in the it is grounded in language. As a result, it is impacting areas that have been somewhat resistant to technological change in the past.  Fields that are themselves grounded in the language, such as the Law, are now trying to find ways to adapt to the technology. 

In the face of these transformations, it is crucial that we understand what these technologies really are and how they can and should be used. We need to distinguish between skill in how to say things and the knowledge of what to say.


In this talk, Dr. Hammond will outline an approach that leverages the power of these models and their near miraculous fluency to create systems that are both expressive and truthful. Using a synthesis of data, analytics, and language models, these systems are able provide access to knowledge and the inference it supports to provide access to information that is well beyond the reach of language models while leveraging the fluency that is at their core.


Keynote Talk #2 (Afternoon):  

Dr. Frank Schilder, Senior Director with Thomson Reuters Labs

Dr. Frank Schilder  is a Senior Research Director at Thomson Reuters with TR Labs, leading a team of researchers to explore new machine learning and artificial intelligence techniques in order to create smart products for legal NLP problems. His research interests include summarization, question answering and information extraction, and natural language generation. Frank received the master’s degree in computer science (Diplom-Informatik) from the University of Hamburg and the Ph.D. degree in cognitive science from the University of Edinburgh, Scotland.  Before joining Thomson Reuters, he was an Assistant Professor at the Department for Informatics, University of Hamburg, Germany. 

Title: Legal Expertise Meets Artificial Intelligence: A Critical Analysis of Large Language Models as Intelligent Assistance Technology


This talk investigates an intelligent assistance (IA) approach to utilizing Large Language Models (LLMs) in the legal domain by addressing the risks associated with unchecked artificial intelligence (AI) applications. We emphasize the importance of understanding the distinctions between AI and IA, with the latter involving human-in-the-loop decision-making processes, which can help mitigate risks and ensure responsible use of this rapidly developing technology.

Using ChatGPT and GPT-4 as a prime example, we demonstrate its dual role as both an AI and IA application, showcasing its versatility in a variety of legal tasks. We look at recently reported explorations in particular in using very LLMs in addressing tasks such as multiple-choice question answering, legal reasoning, case outcome prediction, and summarization. We argue that to fully achieve "augmented intelligence," a reasoning and knowledge base component is required, allowing IA systems to effectively support human users in decision-making processes.