Robert Mahari

Robert Mahari

rmahari@mit.edu

Boston, Massachusetts

About me

I'm pursuing a joint JD-PhD degree at Harvard Law School and the MIT Media Lab. My work focuses on Computational Law: leveraging computation to analyze, improve, and extend the study and practice of law.

My research aims to bridge the gap between technology and law to surface new quantitative insights into jurisprudential systems and to identify computationally-enabled approaches to the practice of law. By formalizing research around computational law, I aim to deepen our understanding of legal processes, while building tools that improve legal practice, expand access to justice, and increase judicial efficacy.

I also study the technological transformation of the legal profession and its effect on how organizations manage legal services and risks. To this end, I collaborate with private and public entities around the world to prototype practice-oriented computational legal solutions, deploying and studying computational law in the real world.

Research

Analyze

Computational law leverages advanced computational techniques—like network science, natural language processing, and machine learning to help us better understand how legal systems function.

Uncovering the universal dynamics of citation systems

Universal citation dynamics across knowledge systems and a community-based citation model that better predicts future citation trajectories.

Quantifying Judicial Impartiality

We use judges' early career citations to capture their idiosyncracies and we find that a significant minority of judges appear to routinely rely on extreneous factors.

Ranking Law Firms

Widely used law firm rankings focus on reputation and we show they have little to do with trial outcomes. We present a data-driven ranking approach that captures law firm's actual performance.

Litigation Finance at Trial: Model and Data

Grounded in empirical data, we explore how litigation finance affects the way litgants and law firms behave.

Improve

Legal practice is deeply rooted in written language and so stands to benefit immensely from the thoughtful and responsible application of machine learning and NLP. Computational law brings a practice-oriented perspective to the development of these technologies in an effort to use technology to further access to justice and sustainably transform legal services.

The Law and NLP: Bridging Disciplinary Disconnects

The slow uptake of NLP in legal practice may be exacerbated by a disconnect between the needs of the legal community and the focus of NLP researchers.

LePaRD: A Large-Scale Dataset of Judges Citing Precedents

A massive collection of U.S. federal judicial citations to precedent in context that facilitates work on legal passage prediction, a challenging practice oriented legal retrieval and reasoning task.

AutoLaw: Augmented Legal Reasoning

Introducing Legal Precedent Prediction (LPP), the task of predicting relevant passages from precedential court decisions given the context of a legal argument.

LLMs for Learning Complex Legal Concepts

LLM generated can help individuals understand complex legal concepts by generating an illustrative story. This especially helps non-native English speakers in their understanding.

Extend

Computational law enables new approaches to regulation and provide valuable information to regulators and market participants. Computational approaches can be used to express regulations in new ways and provide insights that allow lawmakers to regulate new technologies like AI more effectively.

Art and Science of Generative AI

Exploring the role of human creativity in generative AI.

Data Provenance Project

A large-scale audit of AI training data including data licenses, sources, and provenance.

Preparing for Addictive Intelligence

Individuals are starting to form connections with AI companions. Although this can can harm users, this area is difficult to regulate. Regulation by Design and Legal Dynamism might offer solutions.

Legal Dynamism

Advances in computational law allow us to re-examine and update regulation in real time, recasting laws as dynamic systems rather than as static rules.

AML by Design

Designing central bank digital currencies to stifle money laundering.

Time for a New Antitrust Era

Responding to unique challenges of a data-driven marketplace by expanding monopoly power to include data ownership and enhancing premerger review with network science.

Speaking

The Future of Law: AI Powered Justice? | TEDxBoston

Inaugural Speech | University of Warsaw

AI, Democracy, and Humanity | Boston Global Forum

The Science of Breakthroughs | TEDxBoston

News

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