Participation in medical research has been discussed heatedly since the feminist self-help movement of the 1970s. These careful practices of knowledge-sharing among lay people challenged the patriarchal and increasingly profit-driven medical profession (Murphy 2015). As Murphy also showed, who gets empowered, who is cared for and who is excluded from profiting has to be scrutinized in complex global entanglements. Also, questions of whose data are relevant for the development of medical products, who is considered to represent all humans or specific humans and who is perceived as reliable test subject for medical trials, are rather complicated (Epstein 2003). Moreover, it has to be reflected that the right to take part may not always be considered as equally important as the right for ?informed refusal? (Benjamin 2016).
To continue this discussion seems important when data of human bodies have become a highly valued currency not only for medical care but also for big technoscience business. Today, with Artificial Intelligence as the promise for technical solutions for social and medical problems, the access to valid data on a voluntarily basis has become an urgency. What are the technopolitics of care involved?
In the paper, these questions are discussed with the example of diagnostic accuracy of breast cancer. An abundance of breast cancer screening data is needed to train algorithms to make the promise of AI come true to detect breast cancer ?even better? than medical personnel (Nature 577, 2020). Although there are debates about the efficiency of mammography, especially because of many false positive and false negative diagnosis, women are urged by big campaigns to donate their screening data as a measure of solidarity. Is this an example for care-less datafication processes or care-ful datafied futures? What has to be considered?