The Future of Knowledge

• In Event: 40826 - Knowledge #2: Scientific and Social Scientific Knowledge

Abstract

Knowledge has been quite foundational for the transformations we associate with the enlightenment, modernity and industrialization. It is not, however, a temporally stable system of outcomes or of beliefs and practices. The research systems I compared and investigated in my earlier work on Epistemic Cultures (1999) changed continually. But many changes seemed to be prompted internally, almost as a matter of course as scientists discovered problems and moved from one question to the next advised by earlier results. More recently, changes of a different origin have risen to the foreground and become topics of scientific discourse, grant agency attention, and research re-orientations. These changes run deeper, may be quite contested and can turn over whole professions. What I mean here is the move toward an artificially intelligent science. AI is of course a massive transformative force in manifold areas of social life as it influences and remakes the thinking part of human systems. Scientific and technological fields are at the origin of these transformations, but they are also, or so it seems, their best client—eager not only to produce them but also to implement them in their own epistemic practices.
This paper looks at how various implementations of AI may impact epistemic essentials of science. Taking clues from STS, philosophy of science, and science of science, the paper considers empirical capacity, understanding capacity, and creative and learning capacity as such epistemic essentials. The paper draws on documentary analysis and in depth expert interviews in several natural scientific fields as well as on targeted participant observation to investigate relevant changes

Author

• Karin Knorr Cetina, University of Chicago