Citizen science is a relatively new phenomenon in the scientific community. There is no single model to using citizens in research projects. In the DIG1t0 project, citizen researchers are involved throughout process in coproduction of knowledge, including gathering research data and analysing data in collaboration with professional researchers. In co-research, the research is based on the personal experiences of citizens at risk of exclusion using various services. The idea of such collaborative citizen science is to open dialogue between digital service providers, researchers and citizens who use them at the grassroots level.
Experts by experience in mental health and substance abuse participate in the DIG1t0 project. Participation in the research group are done in a variety of ways, such as peer interviews, participatory mind maps and photo diaries, video recordings of usage of digital services, or group discussions and workshops with mental health rehabilitees and immigrants.
We emphasise the significance of co-research to obtain authentic information, especially from the vulnerable users of digital services, so that digital services can be developed better meet their needs. Language problems, such as the ambiguity of the official language and the difficulty of perceiving the architecture of electronic forms, hamper, for example, the ability of immigrants to use digital services.
The role of the language in digitalisation is not evident only in the interaction between a user and a digital system, but also at the different levels of code and algorithms. For example, language plays a key role in structuring and classifying training data for machine learning algorithms using different keywords. In the field of social work, for example, the keywords used by professionals about their clients can be quite varied. The combination of used keywords and statistic-based algorithm models can lead to various degrees of bias and even exclusion of citizens.