2020 Vision of Crowd Science
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ItemCitizen Science in Information Systems Research: Evidence From a Systematic Literature Review( 2020-01-07)Citizen science refers to partnerships between scientists and the public in scientiﬁc research. Citizen science is considered as an emerging approach for conducting research in the field of information systems (IS). However, there is a fragmented understanding of citizen science in the IS community. As a result, we conducted a systematic literature review on citizen science in IS field aiming at understanding what and how IS scholars view and conduct their research related to citizen science. We searched papers from the database of the basket of eight senior journals, 47 SIG recommended journals by the Association for Information Systems, and the proceedings of five major conferences in IS including ICIS, ECIS, HICSS, PACIS, and AMCIS. Our findings provide the current status of citizen science research in IS field, such as how scholars view about citizen science, how to set up a citizen science project, or how citizen science is adopted in IS community. This research also contributes to the field by laying out suggestions for the future research of citizen science.
ItemTheoretical Underpinnings and Practical Challenges of Crowdsourcing as a Mechanism for Academic Study( 2020-01-07)Researchers in a variety of fields are increasingly adopting crowdsourcing as a reliable instrument for performing tasks that are either complex for humans and computer algorithms. As a result, new forms of collective intelligence have emerged from the study of massive crowd-machine interactions in scientific work settings as a field for which there is no known theory or model able to explain how it really works. Such type of crowd work uses an open participation model that keeps the scientific activity (including datasets, methods, guidelines, and analysis results) widely available and mostly independent from institutions, which distinguishes crowd science from other crowd-assisted types of participation. In this paper, we build on the practical challenges of crowd-AI supported research and propose a conceptual framework for addressing the socio-technical aspects of crowd science from a CSCW viewpoint. Our study reinforces a manifested lack of systematic and empirical research of the symbiotic relation of AI with human computation and crowd computing in scientific endeavors.