Aloni Cohen Named Sloan Research Fellow for Work Bridging Law and Computer Science
When a computer scientist spends as much time poring over legal documents as lines of code, something interesting is bound to happen. That is certainly the case for Aloni Cohen, Assistant Professor of Computer Science at the University of Chicago, who has just been awarded a 2026 Sloan Research Fellowship—a two-year, $75,000 award supporting fundamental research across science, mathematics, engineering, and more.
The Sloan Fellowship, bestowed annually on researchers whose creativity and accomplishments signal them as leaders of the next generation, recognizes those who break boundaries—and Cohen’s work embodies that spirit. His research stands out at the intersection of computer science and law, a meeting point where technical advances and societal challenges converge.
As Cohen explains, “Examining law through a computational lens can reveal new problems and lead to new insights,” underscoring how mathematical rigor can illuminate dimensions of legal questions rarely addressed by traditional legal analysis. For Cohen, the goal is to create what he calls “legal theorems”: mathematical results that have concrete legal consequences, offering both new ways of understanding and practical tools for navigating complex regulatory landscapes.
Rethinking the Foundations of Data Privacy
One of the central issues Cohen addresses is data anonymization—how to transform sensitive data so that individuals cannot be re-identified. A widely adopted technique known as k-anonymity has long shaped regulatory approaches in the United States and abroad. Cohen’s research, however, demonstrates that k-anonymity and its many variants do not provide sufficient privacy safeguards, a conclusion supported by both theoretical and practical analysis.
His findings have drawn the attention of key stakeholders, with citations in reports from the National Institute of Standards and Technology (NIST) and the National Academies of Sciences, Engineering, and Medicine. As privacy regulations continue to evolve—especially under frameworks like the European Union’s General Data Protection Regulation (GDPR)—such work plays an essential role in informing both policy and practice. If widely adopted by regulators, this perspective could lead to significant changes in how sensitive data is handled in sectors including health care, where privacy requirements are stringent and the risks of re-identification are substantial.
Building a Bridge Between Law and Computation
The novelty of Cohen’s work lies in what he calls “hybrid legal-technical” arguments”, rigorously translating legal concepts into computational problems. This approach enables legal questions—rooted in statute or case law—to be examined with the precision of mathematical analysis, creating a mutual interface for regulators, policymakers, and computer scientists.
“You start with some question of law, and you try to map it to a technical, mathematical, computational problem,” Cohen explains. “That mapping is the hard part. But if you succeed in translating the legal question into a technical question, then you can focus on analyzing it mathematically.”
This methodology has led to results with real-world impact, such as amicus briefs cited in federal court and influencing privacy practice at the systemic level. In domains as varied as criminal law and voting rights, it illustrates that rigorous computational work and informed legal analysis can make each discipline stronger and more useful for society.
Law and AI: Navigating a New Era
Cohen’s recent research tackles the next frontier: artificial intelligence. As generative models become commonplace, Cohen’s work raises urgent legal and ethical questions around copyright, data provenance, and privacy.
“There’s just an infinite number of challenges,” he notes. “AI is doing what search engines did 20 years ago; making discoverable information that was practically not so.”
He expects society will soon have to move beyond old frameworks for regulating data-driven systems.
“AI is going to be the catalyst that forces a shift away from intuitions that are built on thinking of data as static databases, and towards thinking about complex and constantly evolving computational systems.”
As these questions multiply, the clarity of Cohen’s computational approach will play a critical role in equipping lawmakers, technologists, and the broader community for challenges ahead.
Shaping the Digital Age
With AI transforming society and data privacy more important than ever, Cohen’s cross-disciplinary research exemplifies the innovative thinking the Sloan Research Fellowship seeks to foster. His work calls for a reassessment of the legacy frameworks guiding how we regulate, implement, and think about data and computation in the modern era.
By supporting foundational research through this fellowship, the Alfred P. Sloan Foundation is betting on researchers like Cohen—those capable of forging new connections between technology, law, and the public interest—to help guide society through the evolving digital landscape.
