Research

Intellectual property adjudication begins with perception. Before courts can determine whether copying has occurred, whether consumers are confused, or whether designs are ornamental, decision makers must perceive and compare stimuli (works, marks, products) and evaluate their similarity, distinctiveness, and aesthetic character. Copyright's "substantial similarity" standard is a perceptual judgment. Trademark's "likelihood of confusion" is a prediction about consumer perception. The "ordinary observer" standard in design patent is an appeal to perceptual consensus.

I study the cognitive and neural mechanisms underlying these processes: psychophysical and computational models of similarity judgment, including geometric, feature-based, exemplar, and Bayesian approaches; neural substrates of categorization and aesthetic evaluation; representational similarity analysis; and the effects of attention, context, and expertise on how people perceive resemblance between complex creative works. This work extends to musical cognition, where questions about similarity perception, structural representation, and analogical mapping bear on copyright disputes involving melodic and harmonic similarity.

Perception alone does not determine legal outcomes. Observers must categorize perceived similarities, deciding whether a secondary work is derivative or transformative, whether a mark is descriptive or suggestive, whether features are functional or ornamental. They reason analogically from precedent, mapping prior cases onto new disputes. They apply normative standards about fairness, intent, and desert. And they increasingly evaluate creativity in contexts where the "author" is an algorithm rather than a human.

This level of my research examines how these reasoning processes operate across multiple areas of law. In intellectual property, I study categorization processes underlying the derivative-transformative distinction in fair use, analogical reasoning in case-based decision making, normative cognition in assessments of ownership and fairness, and how people evaluate machine-generated creativity against implicit effort heuristics and essentialist beliefs about human authorship. In constitutional law, I apply computational and psycholinguistic methods to questions of legal interpretation, including Bayesian models and the rational speech act framework as alternatives to serial textualism, and empirical investigations of how people parse the syntactic structure of constitutional provisions like the Second Amendment. In criminal law and tort, I study intentionality attribution, the decay of counterfactual reasoning in moral and legal judgment, the cognitive dimensions of reasonableness, and the justifications of punishment.

Across these domains, a recurring finding is that the hypothetical cognitive agents invoked by legal standards (the "ordinary observer," the "reasonable person," the "person having ordinary skill in the art") are cognitive fictions whose assumed capacities can be empirically investigated and often diverge from actual human cognition in systematic ways.

Individual cognition does not simply aggregate into collective outcomes through summation. The emergence of legal norms follows complex dynamics that cannot be predicted from individual-level psychology alone. Informal intellectual property regimes in creative communities (attribution norms, sharing conventions, expectations about permissible borrowing) arise through evolutionary and cultural processes that interact with, and sometimes substitute for, formal law. Understanding how these informal systems develop and operate is essential for predicting how changes in legal rules will affect actual creative practice.

I study these dynamics using computational cognitive modeling, agent-based simulation, and multi-agent reinforcement learning. I examine how cognitively realistic agents, endowed with the perceptual and reasoning processes studied at the first two levels, generate system-level patterns of innovation, imitation, and enforcement under different legal regimes. I also study how cognitive constraints like bounded rationality, hindsight bias, and intent attribution heuristics shape institutional frameworks for secondary liability and contributory infringement. At this level I am also interested in using computational methods to formalize and test theories of jurisprudence, examining how formal models can clarify competing accounts of the nature of law and the relationship between individual legal reasoning and institutional structure.