The previous post focused on citizen science as participatory science. This post is discussing the meaning of this differentiation. It is the final part of the chapter that will appear in the book:
The typology of participation can be used across the range of citizen science activities, and one project should not be classified only in one category. For example, in volunteer computing projects most of the participants will be at the bottom level, while participants that become committed to the project might move to the second level and assist other volunteers when they encounter technical problems. Highly committed participants might move to a higher level and communicate with the scientist who coordinates the project to discuss the results of the analysis and suggest new research directions.
This typology exposes how citizen science integrates and challenges the way in which science discovers and produces knowledge. Questions about the way in which knowledge is produced and truths are discovered are part of the epistemology of science. As noted above, throughout the 20th century, as science became more specialised, it also became professionalised. While certain people were employed as scientists in government, industry and research institutes, the rest of the population – even if they graduated from a top university with top marks in a scientific discipline – were not regarded as scientists or as participants in the scientific endeavour unless they were employed professionally to do so. In rare cases, and following the tradition of ‘gentlemen/women scientists’, wealthy individuals could participate in this work by becoming an ‘honorary fellow’ or affiliated to a research institute that, inherently, brought them into the fold. This separation of ‘scientists’ and ‘public’ was justified by the need to access specialist equipment, knowledge and other privileges such as a well-stocked library. It might be the case that the need to maintain this separation is a third reason that practising scientists shy away from explicitly mentioning the contribution of citizen scientists to their work in addition to those identified by Silvertown (2009).
However, similarly to other knowledge professionals who operate in the public sphere, such as medical experts or journalists, scientists need to adjust to a new environment that is fostered by the Web. Recent changes in communication technologies, combined with the increased availability of open access information and the factors that were noted above, mean that processes of knowledge production and dissemination are opening up in many areas of social and cultural activities (Shirky 2008). Therefore, some of the elitist aspects of scientific practice are being challenged by citizen science, such as the notion that only dedicated, full-time researchers can produce scientific knowledge. For example, surely it should be professional scientists who can solve complex scientific problems such as long-standing protein-structure prediction of viruses. Yet, this exact problem was recently solved through a collaboration of scientists working with amateurs who were playing the computer game Foldit (Khatib et al. 2011). Another aspect of the elitist view of science can be witnessed in interaction between scientists and the public, where the assumption is of unidirectional ‘transfer of knowledge’ from the expert to lay people. Of course, as in the other areas mentioned above, it is a grave mistake to argue that experts are unnecessary and can be replaced by amateurs, as Keen (2007) eloquently argued. Nor is it suggested that, because of citizen science, the need for professionalised science will diminish, as, in citizen science projects, the participants accept the difference in knowledge and expertise of the scientists who are involved in these projects. At the same time, the scientists need to develop respect towards those who help them beyond the realisation that they provide free labour, which was noted above.
Given this tension, the participation hierarchy can be seen to be moving from a ‘business as usual’ scientific epistemology at the bottom, to a more egalitarian approach to scientific knowledge production at the top. The bottom level, where the participants are contributing resources without cognitive engagement, keeps the hierarchical division of scientists and the public. The public is volunteering its time or resources to help scientists while the scientists explain the work that is to be done but without expectation that any participant will contribute intellectually to the project. Arguably, even at this level, the scientists will be challenged by questions and suggestions from the participants and, if they do not respond to them in a sensitive manner, they will risk alienating participants. Intermediaries such as the IBM World Community Grid, where a dedicated team is in touch with scientists who want to run projects and a community of volunteered computing providers, are cases of ‘outsourcing’ the community management and thus allowing, to an extent, the maintenance of the separation of scientists and the public.
As we move up the ladder to a higher level of participation, the need for direct engagement between the scientist and the public increases. At the highest level, the participants are assumed to be on equal footing with the scientists in terms of scientific knowledge production. This requires a different epistemological understanding of the process, in which it is accepted that the production of scientific insights is open to any participant while maintaining scientific standards and practices such as systematic observations or rigorous statistical analysis to verify that the results are significant. The belief that, given suitable tools, many lay people are capable of such endeavours is challenging to some scientists who view their skills as unique. As the case of the computer game that helped in the discovery of new protein formations (Khatib et al. 2011) demonstrated, such collaboration can be fruitful even in cutting-edge areas of science. However, it can be expected that the more mundane and applied areas of science will lend themselves more easily to the fuller sense of collaborative science in which participants and scientists identify problems and develop solutions together. This is because the level of knowledge required in cutting-edge areas of science is so demanding.
Another aspect in which the ‘extreme’ level challenges scientific culture is that it requires scientists to become citizen scientists in the sense that Irwin (1995), Wilsdon, Wynne and Stilgoe (2005) and Stilgoe (2009) advocated (Notice Stilgoe’s title: Citizen Scientists). In this interpretation of the phrase, the emphasis is not on the citizen as a scientist, but on the scientist as a citizen. It requires the scientists to engage with the social and ethical aspects of their work at a very deep level. Stilgoe (2009, p.7) suggested that, in some cases, it will not be possible to draw the line between the professional scientific activities, the responsibilities towards society and a fuller consideration of how a scientific project integrates with wider ethical and societal concerns. However, as all these authors noted, this way of conceptualising and practising science is not widely accepted in the current culture of science.
Therefore, we can conclude that this form of participatory and collaborative science will be challenging in many areas of science. This will not be because of technical or intellectual difficulties, but mostly because of the cultural aspects. This might end up being the most important outcome of citizen science as a whole, as it might eventually catalyse the education of scientists to engage more fully with society.