Miami Law & AI (MiLA): Events & Initiatives

Join the Miami Law & AI (MiLA) Lab for a unique event that brings together UM’s first-ever AI and law conference and legal prompt engineering competition.

Conference on AI Lawyering
Discover the groundbreaking ways AI is reshaping the legal field with discussions and cutting-edge insights from experts on the challenges and opportunities of AI lawyering.
 
Student Competition: Prompt Engineering in Legal Tasks
Law students will compete to solve real-world legal challenges using AI tools. Competitors will showcase their skills, with awards for top performers.

Register

This project aims to develop an LLM-based tool that automates the process of creating Bluebook-compliant legal citations. The main mission of the AI Bluebook project is to create an accurate and efficient LLM-based tool that automates Bluebook citations, reducing errors and saving time for legal professionals and scholars. The tool will utilize an agentic flow environment, where multiple AI agents with specialized roles work together to handle different aspects of the citation process. This approach will allow for a “divide-and-conquer” strategy, breaking down the complex task of Bluebook citing into manageable subtasks. Key features of the AI driven Bluebook Citation tool include Multiple AI agents with specialized roles, integration of system prompts and Retrieval-Augmented Generation (RAG), and collaboration between UM law and computer science students.

Development of an online video library focused on AI literacy, skills, and applications
in the legal domain, designed for future law students.

ClassInsight is an innovative AI-powered tool developed by the MiLA Lab that transforms
classroom engagement and assessment.
ClassInsight uses real-time analysis of data collected during class to provide two main outputs:
(1) Classroom-Wide Visualization: Anonymized, collective visual insights for the professor
regarding class-wide comprehension.
(2) Personalized Student Feedback: Tailored feedback for each student regarding their
performance and level of understanding.
ClassInsight's output is generated and available in real-time, allowing professors to adapt and
adjust the class based on the insights.
Also, the tool enables students to recognize misunderstandings on the spot and explore them
further during class.
Faculty interested in early access to the tool are welcome to contact us.

Enhancing the online presence and media outreach of Miami Law’s AI
initiatives through a MiLA Newsletter and Journal Contributions

The AI & Law Research Award is an annual initiative led by the Miami Law & AI Lab to support cutting-edge research at the intersection of AI and law. Each year, promising scholars and practitioners are selected to receive funding and computational resources for their pioneering projects.

The Miami Law & AI Lab is funding six pioneering projects through the AI & Law Research Award program, advancing innovation at the intersection of AI, law, and government:

Human Trials of Anti-Genrative AI Biases in Patent Law
Mike Schuster - University of Georgia, US
Joseph Avery - University of Miami, US

Large Language Models and the Jurisprudence of Vibes
Ben Sobel - Cornell Tech, US

Bias as a Signal: Harnessing Foundation Models' Data-Driven Bias to Inform Contractual Legal Standards
Uri Hacohen - Tel Aviv University, IL

Navigating Decentralized Approaches to AI: Challenges in US State-Level Regulation Without Federal Oversight
Elijah Boykoff - University of Colorado Boulder, US

Imposters: Unregulated Medical Advice from AI Chatbots in the US and EU
Mindy Duffourc - Maastricht University, NL
Roni Kennedy, Riya Goel - University of Miami, US

Graph-Based RAG System for Automated Detection and Legal Validation of Abusive Clauses in Financial Contracts
Makdihel Laudino Santillán, Philippe Prince Tritto, Hiram Ponce, and Karina Ruby Perez-Daniel - National Commission for the Protection and Defense of Users of Financial Services & Universidad Panamericana, MX