Paper short abstract:

While the debate around citizen science revolves around the question of whether it will make science more democratic, this paper proposes an alternative reading: To what extent is citizen science a transient phenomenon - just another step on the way to an automated system of knowledge production?

Paper long abstract:

Citizen science is currently experiencing a boom in almost all scientific disciplines. Citizens' participation in the research process is seen on the one hand as an opportunity to generate socially robust knowledge for sustainable development, and on the other hand as a participatory method for bridging the gap between science and society. And indeed, Citizen Science is EU-funded for precisely these reasons.

Extending the virtual workforce from scientists to non-scientists can sometimes lead to impressive research results. This is particularly evident in gamified projects with a large number of participants, which have a clear task structure and do not require any specialist expertise. However, if we look at the majority of citizen science projects, citizens are only involved in certain stages of the research process, namely data gathering and processing. When collecting data, citizens often act as sensors in wildlife monitoring or as unpaid crowd workers who take over the curating of Big Data.

Against this background, and taking into account further socio-technical trends, it seems misleading to further speak of citizen science under the heading of a democratisation of science. This paper therefore proposes a different interpretation, focusing on the aspect of human computation. From this perspective, the rise of citizen science can rather be understood as a transitional phenomenon - as one step on the path from individual knowledge acquisition, through crowdsourcing of routine scientific activities to the gradual automation of knowledge production.