Abstract Postconviction review is an increasingly salient issue, especially during transitions between presidential administrations. Despite statements that he would not do so, President Joe Biden pardoned his son, Hunter Biden, for firearms and tax-related offenses. Weeks later, President Donald Trump pardoned individuals who were convicted of crimes associated with the January 6, 2021, events on Capitol Hill. Each administration’s postconviction relief decisions were critiqued on similar grounds, namely, that they were unprincipled, self-interested, or partisan. These examples highlight the importance of fairness, justice, and coherence associated with postconviction review and postconviction relief. Interestingly, the recent transition between the Biden and Trump administrations occurred during a unique period that was characterized by two other major developments: the rise of artificial intelligence and a renewed emphasis on government efficiency. These two developments may catalyze significant reforms to the postconviction review process to counteract a specific type of government waste and abuse: excessive prison sentences. Drawing on the insights of public administration scholarship, this article argues that artificial intelligence may help improve postconviction review and postconviction relief in certain respects. It argues that artificial intelligence can be used to identify eligible persons for second-look resentencing and clemency, facilitate applications for postconviction review, and streamline the evaluation of postconviction review claims. It demonstrates how artificially intelligent clemency may improve efficiency, fairness, and access to justice. It also highlights important barriers that limit AI’s potential and effectiveness in postconviction review contexts.
Terry Skolnik (Thu,) studied this question.