This talk will concern the importance of data management in the light of multidisciplinary or interdisciplinary research. Coming together to formulate aims and research questions of a study together with researchers from differing faculty and disciplinary backgrounds will require some common grounds. At the same time, being from different disciplines and thereby being able to provide different perspectives on a phenomena or problem would be the very idea of working together. For me this is an interesting point to depart from in reflecting on data management. In this talk I will do that with a discussion on these seemingly different positions in relation to data and AI from the frameworks of FAIR and CARE.
With the FAIR principles as a point of departure follows data at a more common level, data that is open, transparent, and possible to exchange between researchers. With the CARE principles follows aspects of context, and not least power. With these frameworks in mind I reflect on the somewhat easy access for AI-driven analysis that might present itself through the FAIR-principles, and the at the same time less visible ethical aspects of AI-driven analysis that can be highlighted through the CARE-principles.