David Lehr

Papers

Total Citations

233

H-Index

About

David Lehr is a leading scholar at the intersection of law, technology, and public administration, best known for his groundbreaking work on algorithmic governance and administrative law. His most-cited paper, "Regulating by Robot: Administrative Decision Making in the Machine-Learning Era" (2017), with over 230 citations, fundamentally reshaped how legal scholars and policymakers understand the use of machine-learning algorithms in government. In this seminal work, Lehr dissected the tension between the opaque, data-driven logic of AI systems and the transparency, accountability, and due process required by administrative law. He identified critical risks—such as algorithmic bias, lack of explainability, and the erosion of human discretion—while also proposing a framework for "technological due process." Beyond this flagship paper, Lehr’s research explores how emerging technologies challenge existing regulatory structures, making him a vital voice in debates on AI ethics and governance. His work has been widely cited in legal scholarship, policy reports, and judicial opinions, cementing his influence as a thinker who bridges technical complexity with democratic accountability. For students and researchers, Lehr offers a rigorous, cautionary, yet constructive lens on the future of automated decision-making.