@proceedings{17699,
  author = {Leif Knutsen and Jo Hannay and Michael Riegler},
  title = {Artificial Intelligence in the Public Sector -- An Agenda for Responsible Innovation through Learning},
  abstract = {The optimism about the benefits of using artificial intelligence to innovate public services is tempered by concerns about its risks, limitations, and disbenefits. Given the rapid changes in the technology itself, the opportunities and needs for cross-sectional solutions, and the nascency of the field of AI-based innovation, we contend that policy, strategy, and implementation must include feedback loops that enable institutional learning for the entire public sector. The scope of challenges creates and imperative to facilitate learning must transcend functional, organizational, geographic, and national boundaries. We propose a learning agenda that includes 1) alignment of strategy and policy; 2) initial understanding of goals, benefits, disbenefits, limitations, and risks; 3) data sharing across jurisdictions; 4) technical robustness and societal alignment in governmental oversight; 5) convergence of architecture for AI support; and 6) a portfolio approach to selecting and learning from enabling service innovation with AI.},
  year = {2024},
  journal = {International Workshop on Software-intensive Business},
  month = {04/2024},
}