The Norm
16 Research
Stanford Law publication introducing the concept of Legal Engineering as a new paradigm for converting legal workflows into AI systems.
SSRN paper on the intersection of corporate governance, AI governance, and the role of the board of directors.
Published in the Royal Society, this case study examines the emergence of legal reasoning capabilities in large language models through tax law.
Published in Science, this paper explores the intersection of artificial intelligence and interspecific law.
Stanford Law publication exploring how legal fiduciary standards can serve as a framework for robust AI-human communication.
Published in the Vanderbilt Law Review, this paper explores practical ways regulators can leverage AI to improve regulatory processes.
Research on using legal frameworks as information systems to align AI agent behavior with human values and societal norms.
Research investigating the ability of large language models to follow explicit rules and instructions in various contexts.
A collaboratively developed benchmark specifically designed to measure and evaluate legal reasoning capabilities in large language models.
A comprehensive assessment framework for evaluating the reliability of artificial intelligence systems across multiple dimensions.
A benchmark designed to evaluate advanced reasoning capabilities in large language models across diverse domains.
Research examining the potential for large language models to function as corporate lobbyists and the implications for policy.
Northwestern Journal of Technology and Intellectual Property publication on using legal informatics to align AI systems with human values.
SSRN paper applying natural language processing techniques to analyze presidential legal texts and executive orders.
Published in PLOS ONE, this paper presents AI methods for predicting legislative outcomes and law-making patterns.
Applying machine learning to create distributed representations of government institutions and their legal text for computational analysis.
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