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8 Regul. Rev. Depth 1 (2019)

handle is hein.journals/rgyrvidh8 and id is 1 raw text is: THE CHALLENGE OF EQUITABLE ALGORITHMIC CHANGE Ellen P. Goodmant Iconic yellow public school buses pass through streets all across the United States every day, performing a complex choreography of crisscrossing routes and school handoffs. It turns out that school districts have only very recently acquired the computational heft to optimally design bus traffic.1 Algorithms and big data have now made it possible to redo public school busing in ways that cut costs, improve the environment, and better serve students, teachers, and parents. Taking advantage of these tools, the Boston public school system proposed an overhaul of bus routes and school schedules for the 2018 to 2019 school year with the possibility of saving up to $15 million per year.2 What happened next should teach public officials everywhere especially in regulatory agencies-something about how algorithmically derived policy can go sideways even when it promises greater efficiency and equity. Algorithms are useful in solving any complex regulatory problem with a difficult computational component, such as a carbon tax, congestion pricing, pollution allowances, dynamic zoning codes. But there is a growing literature on the things we might worry about in the model that makes up the algorithm, including unfairness, opacity, and a lack of due process.3 These issues have been easiest to see where human life and liberty are on t Ellen P. Goodman is a professor of law at Rutgers Law School and the co-director and co-founder of the Rutgers Institute for Information Policy & Law. 1 David Scharfenberg, Computers Can Solve Your Problem. You May Not Like the Answer, BOSTON GLOBE, Sept. 21, 2018, https://apps.bostonglobe.com/ideas/graphics/ 2018/09/equity-machine/. 2 Dimitris Bertsimas et. al., From School Buses to Start Times: Driving Policy with Optimization, Jan. 2019, https://adelarue.github.io/files/school-buses-to-bell-times.pdf. 3 See Solon Barocas & Andrew D. Selbst, Big Data's Disparate Impact, 104 CAL L. REV. 671 (2016); FRANK PASQUALE, THE BLACK BOX SOCIETY: THE SECRET ALGORITHMS THAT CONTROL MONEY AND INFORMATION (2015); Danielle Keats Citron & Frank A. Pasquale, The Scored Society: Due Process for Automated Predictions, 89 WASH L. REV. 1(2014).

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