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Opportunities for a Collaborative Approach with GenAI Agents in Public Sector Foresight Projects

Type
conference contribution
Date Issued
2025
Author(s)
Lukas Zumbrunn  
;
Davies, Nathan
Abstract
This paper explores the potential integration of Artificial Intelligence (AI) into public sector foresight projects as proxies for citizen participation. Despite motivations to increase participatory approaches, foresight projects have remained constrained by challenges pertaining to scale and confidentiality. Recent advancements in AI technology, particularly in agentic Large Language Models (LLMs), provide new opportunities to simulate diverse public perspectives while managing sensitive strategic information. Through a theory-building approach, we will investigate how AI can enhance openness in foresight without compromising confidentiality. Our conceptual framework integrates insights from foresight, deliberative democracy, and technological affordances literature, emphasizing task-technology-user fit. Preliminary findings indicate significant theoretical and practical opportunities, including enhanced efficiency and inclusivity, alongside challenges such as ethical considerations, data authenticity, and public trust. By analysing expert perspectives across foresight and deliberative democracy fields, the paper contributes to the digital public-citizen innovation discourse and proposes directions for future research on the collaborative potential of human-AI interactions in strategic public administration.
Language
English (United States)
Refereed
Yes
Event Title
IRSPM Annual Conference 2025
Event Location
Bologna
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/122555
File(s)
Thumbnail Image

open.access

Name

IRSPM_Zumbrunn_Davies.pdf

Size

595.06 KB

Format

Adobe PDF

Checksum (MD5)

54c3466548ef89a3172133ab7f9e94b7

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