Citizen crowdsourcing: An investigation of opportunities and challenges of using collective intelligence in policy-making
The project is funded by Slagelse Municipality. The project is headed by Collective Intelligence Unit, Copenhagen Business School and Zealand Academy of Technologies and Business. The total project sum amounts to 4.65 million DKK, of which CIU will receive 2.5 million.
Aims of the project:
The research purpose of the project is to explore the benefits and limitations of the usage of collective intelligence and AI for policy-making, evaluating and comparing with other international participatory democracy platforms.
Dr. Billy Adamsen is Head of Talent Lab, Zealand Academy of Technologies & Business in Denmark. His research interests are management, knowledge and managerial decision-making and the use of crowdsourcing in decision-making.
Funded by Slagelse Municipality, Region Sjællend, Denmark.
A Study of Household Credits, Debts and Savings and Regional GDP: Advancing predictability of Fluctuations Integrating Big Data and Crowdsourcing of Predictions in the Financial Sector.
The project is funded by the research program Nordic Finance and the Good Society, Center for Corporate Governance, Copenhagen Business School. The project is headed by Assistant Professor Carina Antonia Hallin, Collective Intelligence Unit, and computer scientist, Dr. Oded Koren, Shenkar College of Engineering and Design, Israel.
Aims of the project:
To explore who are the smart crowds in the economy and study new approaches and data to forecast the use of credits, debts and savings at the regional level in Denmark, and to investigate links between forecasts of such financial variables and the Regional Gross Domestic Product.
Dr. Oded Koren is a full faculty member in the Department of Industrial Engineering and Management at Shenkar College of Engineering, Design and Art in Israel. His research interests are in the areas of open source development domains, Big Data, AI related aspects and mobile applications.
Dr. Nir Perel is a senior faculty member in the Department of Industrial Engineering and Management at Shenkar College of Engineering, Design and Art in Israel. His research interests include operations research modeling, queuing theory and statistical analysis. Lately his interests are focused on AI and open source development.
Sigbjørn Tveterås is a Professor in Applied Economics in the Department of Industrial Economics, Risk and Planning at the University of Stavanger, Norway. His main research field is Applied Microeconometrics. Most of his published research articles focus on applied issues related to modelling, prediction models, demand, pricing and market structures.
Koren, O., Hallin, C.A., Perel, N., & Bendet, D. (2019). Decision-Making Enhancement in a Big Data Environment: Application of the K-Means Algorithm to Mixed Data, Journal of Artificial Intelligence and Soft Computing Research, 9(4), 293-302. doi: https://doi.org/10.2478/jaiscr-2019-0010
Hallin, C. A., Jensen, J. J. U., Koren, O., Perel, N., & Tveterås, S. (2019). Testing Smart Crowds for the Economy. In A. Monroy-Hernández, & M. Valentine (Eds.), Proceedings of the ACM Collective Intelligence 2019 New York: Association for Computing Machinery.
Koren, O., Hallin, C.A., Perel, N., & Bendet, D. (2019). Enhancement of the K-Means Algorithm for Mixed Data in Big Data Platforms: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 1. doi: https://