AI in Government

Description

The use of artificial intelligence (AI) in government reflects the growth in the use of AI in the economy and in society generally. It is being driven, on the one side, by technical advances in a number of areas such as machine learning, neural nets, and deep learning and, on the other, by economic forces as governments strive to provide more services with fewer resources. AI offers enormous potential to boost efficiency and improve decision-making by processing large amounts of data and information that can help to, for example, identify welfare beneficiaries, combat fraud, and not only deliver better public services but also reduce the cost of delivering personalized and customized services to citizens. However, along with benefits, AI may pose risks to individuals, organizations, and society as a whole. For example, machines lack accountability, and there are opaque and proprietary software tools working outside the scope of meaningful scrutiny and accountability (the so-called “black boxes”) already being used to make decisions that can have fundamental effects on the lives of ordinary citizens. While many government agencies identify AI as a priority, the successful diffusion of this innovation has not been fully realized on a large scale.

The focus of this minitrack will be on both the current uses and potential uses of AI in government. We invite contributions on the adoption and implementation of AI in public organizations, its benefits and risks, as well as on the control, regulation, and governance of this technology. While we envisage papers in this minitrack being on the use of AI primarily in public administration, we will also welcome papers in areas and on topics within the wider public sector, including policing and health (although we will not consider papers related to AI in national security and the military). We welcome submissions with diverse views and methodologies. The goal of this minitrack is to promote critical discussion on the current status and future trajectory AI in government.

Among the dimensions of AI in government that might be addressed are:

• The implementation of AI as a public management task
• The ethics and risk governance of AI and algorithms in public management implementation
• Linking AI implementation, evaluation and the political agenda
• The behavioral impacts of AI – e.g. on motivation, trust, etc.
• The impact of AI on policy development and strategic planning
• Comparative studies across different public service fields
• The role of organizational and/or institutional factors in the implementation of AI
• Ensuring the legitimacy of AI implementation
• Transparency and accountability of algorithm use
• The tensions between the legitimacy of algorithmic decisions used in frontline service delivery and the discretion of street-level bureaucrats when employing, assessing or overriding automated decisions
• Governance of AI
• Determinants of AI adoption
• Challenges of AI implementation
• AI and digital government design
• The integration of AI with existing information systems in the public sector
• AI and sustainable public management
• AI and public value
• Interoperability of AI systems within and across government agencies

Minitrack Leaders

Lemuria Carter is a professor in the business school at the University of Sydney. Her research interests include technology adoption, e-government and cyber security. She has published in several top-tier journals including the Journal of the Association for Information Systems, European Journal of Information Systems, Journal of Strategic Information Systems, Information Systems Journal and Decision Support Systems. She has served as the e-government track and mini-track chair for the Americas Conference on Information Systems and the Hawaii International Conference on System Sciences, respectively. Her research has been funded by the Institute for Homeland Security Solutions and the Southeastern Transportation Institute in the United States.

Laura Hand is an associate professor holding an interdisciplinary joint appointment with the Political Science & Public Administration department in the Nistler College of Business and Public Administration, and the Public Health program in the School of Medicine and Health Sciences. She is currently a visiting scholar at the Center for Technology in Government at the University at Albany – SUNY. Her research examines the ways in which employees of public agencies interact with the people they serve, and what is accomplished through those encounters. She is especially interested in the way AI and other technologies may modify those encounters and alter the relationship between citizens (broadly defined) and the state. She has published in peer-reviewed journals including Government Information Quarterly, Perspectives on Public Management and Governance, and Public Policy and Administration. 

Dapeng Liu is an assistant professor at the Information Systems and Business Analytics Department of Baylor University. He has published in peer reviewed journals including the Journal of the Association for Information Systems, European Journal of Information Systems, International Journal of Information Management, and Decision Support Systems. His research interests include e-government adoption, information security and privacy, AI divide, AI bias, and knowledge modeling and management. His research has been funded by Microsoft Azure. He currently serves on the Editorial Board of the International Journal of Information Management and other journals.