2023/11/16 【Nov. 17】Legal Professionals' Attitudes Towards Algorithmic and Human Decision-Making
Prof. Ryan Kennedy, University of Houston 
Date: Friday, November 17 - 10:00AM~13:00PM (Taiwan Time, GMT+8); Thursday, November 16 - 21:00PM~00:00AM (US Central Time, GMT-6).
Topic: Legal Professionals' Attitudes Towards Algorithmic and Human Decision-Making Note on speaker: Dr. Kennedy is one of the authors who published the
highly cited article on
Science, pointing out the flaws of Google Flu Trend in predictions. We will open a dialogue and invite him to reflect on that article and directions of big data and AI research.
Abstract: Decisions in criminal cases are influenced by the advice received from a multitude of legal experts and increasingly from algorithms or AI. While scholars and practitioners have raised concerns about the bias of algorithms in the criminal justice field affecting hundreds of thousands of defendants a year, few studies focus on how the legal community itself views advice from algorithms as compared to humans. Such a lacunae in the literature is problematic as it assumes that trained legal professionals, poised to influence algorithm development and use, have the same trust or distrust in algorithms as the general public. To address this, we conducted three survey experiments from a unique national sample of legal professionals comparing trust in advice received from algorithms to that from humans. Paradoxically, our results suggest that trained legal professionals or experts do not experience the “algorithms aversion” suggested in much of the social science literature on algorithm trust, despite general concerns of the justness and fairness of using algorithms in criminal cases. The methods used in this paper include multi-level models, parallel regression for estimating moderator effects, and traditional regression. The use of covariate balanced propensity scores and causal forests are demonstrated.
Bio: Dr. Kennedy is one of the authors who published the highly cited
article on Science, pointing out the flaws of Google Flu Trend in predictions. We will open a dialogue and invite him to reflect on that article and directions of big data and AI research.
Ryan Kennedy (Ph.D., The Ohio State University, 2008) is a professor in the department of political science at the University of Houston (UH), principal investigator for the NSF-funded Community Responsive Algorithms for Social Accountability (CRASA) project, director of the Machine-Assisted Human Decision-making (MAHD) Lab (UH), founding associate director of analytics for the Initiative for Sustainable Energy Policy, editor of Research & Politics, and a research associate at the Hobby Center for Public Policy.
Learn more about Prof. Ryan Kennedy at his website.