Weber, J., & Prietl, B. (2022). AI in the age of technoscience: On the rise of data-driven AI and its epistem-ontological foundations. In The Routledge Social Science Handbook of AI (pp. 58-73). Routledge.
As I engaged with the meta-theoretical foundations of knowledge-making for scaffolding methodological development in my doctoral thesis, I increasingly began wondering what were the underlying set of assumptions (called inquiry paradigm by Lincoln & Guba 1995, 2005; also research paradigm, Pretorius 2024) which informs knowledge products spat out of a machine in response to a prompt. The dimensions of these ‘sets of assumptions’ are recognized as epistemology (the nature of knowledge), ontology (the nature of reality), axiology (the nature of values) in addition to methodology which together encapsulate a ‘research paradigm’; it lays the foundation for any systematic program of knowledge-making. Here, in the age of generative AI, when pop-ups in academic publishers’ websites offer to ‘make sense’ of the article you clicked on, it raises the question: what are the assumptions on knowledge and reality and values which underlie the knowledge product constructed by a machine? What is it’s research paradigm? How might I navigate any incommensurabilities between it’s assumptions and mine? Or, is the legacy dominance of positivism being imposed on us, regardless of our own paradigmatic preferences (e.g. constructivism or pragmatism) simply as a result of using past data to predict future content?
The book chapter I link to here by Jutta Weber and Bianca Prietl offers me some answers to these questions; and, in a way, confirms my worst case scenario. Continue reading “Does a chatbot dream of research paradigms?”