TY - GEN
T1 - A Typology for AI-enhanced Online Ideation
T2 - 57th Annual Hawaii International Conference on System Sciences, HICSS 2024
AU - Bono Rossello, Nicolas
AU - Simonofski, Anthony
AU - Clarinval, Antoine
AU - Castiaux, Annick
N1 - Publisher Copyright:
© 2024 IEEE Computer Society. All rights reserved.
PY - 2024
Y1 - 2024
N2 - Digital Participation Platforms (DPP) can enable a massive online participation of citizens in policy-making. However, this digital channel brings new challenges for citizens in the form of information overload and asynchronous dialogues. Various disciplines of online ideation provide different AI-based approaches to tackle these challenges, but the literature remains fragmented. In consequence, this paper develops a typology for online ideation consisting of six types of AI-enhanced solutions. The application of this typology to DPP shows a prominence of automated tasks, with few AI-human loop approaches, and a current lack of applications at the collective level. This general typology also allows us to compare current DPP solutions to other fields, such as open innovation or recommender systems, and to use these fields as inspiration for future solutions. Overall, this paper suggests a theoretical foundation to analyze AI-enhanced online ideation under the form of a typology. Its application to DPP enables identifying future research opportunities and serves as a basis to develop complex architectures for the use of AI in DPP.
AB - Digital Participation Platforms (DPP) can enable a massive online participation of citizens in policy-making. However, this digital channel brings new challenges for citizens in the form of information overload and asynchronous dialogues. Various disciplines of online ideation provide different AI-based approaches to tackle these challenges, but the literature remains fragmented. In consequence, this paper develops a typology for online ideation consisting of six types of AI-enhanced solutions. The application of this typology to DPP shows a prominence of automated tasks, with few AI-human loop approaches, and a current lack of applications at the collective level. This general typology also allows us to compare current DPP solutions to other fields, such as open innovation or recommender systems, and to use these fields as inspiration for future solutions. Overall, this paper suggests a theoretical foundation to analyze AI-enhanced online ideation under the form of a typology. Its application to DPP enables identifying future research opportunities and serves as a basis to develop complex architectures for the use of AI in DPP.
KW - Artificial intelligence
KW - Collective intelligence
KW - Digital participation platforms
KW - E-participation
KW - Idea generation
UR - http://www.scopus.com/inward/record.url?scp=85195616275&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85195616275
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 1850
EP - 1859
BT - Proceedings of the 57th Annual Hawaii International Conference on System Sciences, HICSS 2024
A2 - Bui, Tung X.
PB - IEEE Computer Society
Y2 - 3 January 2024 through 6 January 2024
ER -