Challenges in Collective Intelligence: A Survey
Proceedings of MIPRO 2023 — 46th ICT and Electronics Convention
Abstract
Collective Intelligence (CI) has been gaining significant attention as an effective method for decision-making and forecasting. Prediction Markets (PMs), as a subset of CI, aim to aggregate participants' diverse opinions and knowledge to produce more accurate predictions than any individual could make alone. The unique market-based mechanism of PMs incentivizes participants to reveal their information truthfully, leading to a collectively superior prediction. However, CI and PMs have challenges, including manipulation, fallacies, and group polarization. This paper provides an overview of the challenges facing CI and PMs as tools for collective knowledge aggregation and examines the role of machine learning (ML) models as tools for amplification and hybridization in the future development of CI. Furthermore, the importance of continued research in this field is emphasized.
Notes
Published in MIPRO 2023 proceedings (doi:10.23919/mipro57284.2023.10159767). A survey of open challenges in collective intelligence and prediction markets — manipulation, fallacies, group polarization — and the role of ML for amplification and human–machine hybridization.
How to cite
@inproceedings{brcic2023brcic,
author = {Kristijan Poje and Mario Brcic and Mihael Kovac and Dalibor Krleza},
title = {Challenges in Collective Intelligence: A Survey},
booktitle = {Proceedings of MIPRO 2023 — 46th ICT and Electronics Convention},
year = {2023},
doi = {10.23919/mipro57284.2023.10159767},
}Topics: