Co-creating computer supported collective intelligence in citizen science hubs

Abstract

A Collective Intelligence system is a knowledge network that emerges from human-machine mediated interaction between individuals with personal knowledge. Citizen Science aims to connect society and science by developing a Collective Intelligence ecosystem, which entails collaboration between all QH stakeholders: the public society, researchers and universities, NGOs, governments and funding agencies. The development of crowdsourcing platforms and networks enables volunteers to contribute to different research projects. In addition, artificial intelligence and machine learning technologies extend human intelligence capabilities in the ecosystem. The presented conceptual model was developed based on theoretical insights to understand the complexity of relationships at different levels of human-computer interaction in the Collective Intelligence ecosystem. Citizen Science Hubs are considered an ideal environment for collective intelligence to emerge and bridge the intellectual strengths of humans and machines to take advantage of enormous amounts of data advanced across disciplines.