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 many governments continue to try 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 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 are not accountable 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 realized on a large scale.

The focus of this minitrack will be on both current uses and potential uses of AI in government. We invite contributions on adoption and implementation of AI in public organizations, 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.
• 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

Minitrack papers should be submitted online via the HICSS submission system by June 15, 2023 (11:59 pm HST)

Minitrack Leaders

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.

Lemuria Carter is a Professor in the School of Information Systems and Technology Management at the University of New South Wales. Her research interests include technology adoption, digital government and privacy. 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 currently serves as the digital government track chair for the Americas Conference on Information Systems. Her research has been funded by the Institute for Homeland Security Solutions and the Southeastern Transportation Institute in the United States.

Mila Gasco-Hernandez holds an MBA and a Ph. D. in public policy evaluation. She is the Research Director at the Center for Technology in Government as well as an Associate Professor at the Rockefeller College of Public Affairs and Policy, both at the University at Albany – SUNY. Before joining SUNY, Dr. Gasco-Hernandez served as a senior researcher at the Institute of Governance and Public Management (currently known as ESADEgov - Center for Public Governance) and the Institute of Innovation and Knowledge Management, both at ESADE Business & Law School in Spain. The main general research question at the center of Dr. Gasco-Hernandez’s research agenda is: why and how does technology-driven innovation happen in the public sector? Most of her research in the last six years has focused on the topics of open government, public sector innovation, smart cities and communities, telework, and artificial intelligence in government. In these areas, she has published six books, more than 25 peer-reviewed articles, 16 peer-reviewed book chapters, and more than 40 peer-reviewed conference papers. She has been awarded more than 15 grants in external funding competitive calls and more than 25 consultancy/applied research projects.