In his analysis of “the essential tension between tradition and innovation” Thomas S. Kuhn focused on the apparent paradox that, on the one hand, normal research is a highly convergent activity based upon a settled consensus, but, on the other hand, the ultimate effect of this tradition-bound work has invariably been to change the tradition. Kuhn argued that, on the one hand, without the possibility of divergent thought, fundamental innovation would be precluded. On the other hand, without a strong emphasis (...) on convergent thought, science would become a mess created by continuous theory changes and scientific progress would again be precluded. On Kuhn’s view, both convergent and divergent thought are therefore equally necessary for the progress of science. In this paper, I shall argue that a similar fundamental tension exists between the demands we see for novel insights of an interdisciplinary nature and the need for established intellectual doctrines founded in the classical disciplines. First, I shall revisit Kuhn’s analysis of the essential tension between tradition and innovation. Next, I shall argue that the tension inherent in interdisciplinary research between, on the one hand, intellectual independence and critical scrutiny and, on the other hand, epistemic dependence and trust is a complement to Kuhn’s essential tension within mono-disciplinary science between convergent and divergent thought. (shrink)

I start with a brief assessment of the implications of Sterelny’s anti-individualist, anti-internalist apprentice learning model for a more historical and interdisciplinary cognitive science. In a selective response I then focus on two core features of his constructive account: collaboration and skill. While affirming the centrality of joint action and decision making, I raise some concerns about the fragility of the conditions under which collaborative cognition brings benefits. I then assess Sterelny’s view of skill acquisition and performance, which runs counter (...) to dominant theories that stress the automaticity of skill. I suggest that it may still overestimate the need for and ability of experts to decompose and represent the elements of their own practical knowledge. (shrink)

Scientific communities as social groupings and the role that such communities play in scientific change and the production of scientific knowledge is currently under debate. I examine theory change as a complex social interaction among individual scientists and the scientific community, and argue that individuals will be motivated to adopt a more radical or innovative attitude when confronted with striking similarities between model systems and a more robust understanding of specialised vocabulary. Two case studies from the biological sciences, Barbara McClintock (...) and Stanley Prusiner, help motivate the idea that sharing of models and specialised vocabulary fill the gap between discovery and scientific change by promoting the dispersal of important information throughout the scientific community. (shrink)