Much of the work of modern governance, including delivery of public services, adjudication of entitlement to public benefits, and enforcement of legal mandates, is performed by administrative agencies implementing statutes, regulations, and other authoritative legal sources expressed in complex, interconnected texts. Understanding and complying with these rules is challenging for agencies, citizens, rule-drafters, and attorneys alike. Recent advances in AI, Machine Learning, Human Language Technology, Network Science, and Human Factors analysis offer promising new approaches to improving the ability of all stakeholders, including agencies themselves, to operate within this complex regulatory environment. The scale of administrative states means that the benefits of automation have very high potential impact, both in improvements to government processes and in the delivery of services and benefits to citizens. At the same time, the black-box nature of many automated decision-making systems, particularly sub-symbolic AI components such as those generated by machine learning algorithms, can create considerable tension with the norms of transparency, accountability, and reason-giving that typically govern administrative action. Explainable, responsible, and trustworthy AI is vital for addressing these factors. The First Workshop on Artificial Intelligence and the Administrative State was held on 17 June 2019 in Montreal, Quebec, in conjunction with the Seventeenth International Conference on AI and Law. The Workshop received ten technical paper submissions. Following review by the Program Committee, the seven papers included in these proceedings were accepted for presentation at the Workshop. The Workshop program also included two invited addresses: “Government by Algorithm: A View from the US,” by David Engstrom (Stanford Law School); and “AI and Administration: A View from Europe,” by Tom van Engers (University of Amsterdam). The Workshop concluded with a panel on “Rules as Code” conducted by Jameson Dempsey (Stanford University) with panelists Genevieve Bastien (Transport Canada), Nick Van Beest (Data61), and Meng Weng Wong (Legalese Ltd). The AIAS Organizing Committee expresses its sincere gratitude to all authors for their submissions to the workshop, to the Program Committee for its diligent reviewing, to the invited speakers and panelists, and to the workshop attendees for their enthusiastic participation. It is our earnest hope that identification and development of administrative applications of AI will lead to rapid advances in this field and improved delivery of services to citizens worldwide.
Program Chairs Karl Branting, The MITRE Corporation Tom van Engers, University of Amsterdam