Mark Kleiman was a policy analyst and teacher. His career was grounded in a paradox: he valued objective truth above all, but he applied his skills to the inherently subjective, messy task of designing policies in the public interest. He excelled in this pursuit, becoming an advisor to decision makers at all levels of government. He also taught countless students how to think in complex ways, with one foot grounded in rigorous science and the other in empathy to the idiosyncrasies of human existence.

Mark’s most lasting public contribution will likely be his book, When Brute Force Fails, which explained in plain terms how the criminal justice system can encourage people to make better decisions, without causing intolerable harm. Near the beginning of that volume he writes, “It is just as well that intellectual debts need only be acknowledged, rather than paid; else we would all die bankrupt.”

After his death in 2019, many of Mark’s colleagues, students, and friends felt the weight of our intellectual debts. To compensate, in part, for these arrears they approached the Committee on Law and Justice at the National Academies of Sciences, Engineering, and Medicine, of which Mark was a long-time member, to establish a fitting memorial to his legacy.

The Mark Kleiman Innovation for Public Policy Memorial Lecture will be awarded annually (for the period that sufficient funding remains available) to an early career investigator with a portfolio of research that informs criminal justice decision making and public policy, or other related field. It will be accompanied by a monetary prize and the opportunity to present at a meeting of the Committee on Law and Justice. Mark was fond of novel, counterintuitive, and contrarian ideas – the type of work in which early career professionals are rarely encouraged to engage. In this spirit, the award is intended to identify scholars with innovative ideas for public policy; a demonstrated record of successful peer reviewed publication is neither necessary or sufficient positive factor for selection.