Abstract

(with Samuli Reijula and Miles MacLeod)

Interdisciplinarity is strongly promoted in science policy across the world. It is seen as a necessary condition for providing practical solutions to many pressing complex problems for which no single disciplinary approach is adequate alone. In this paper we model multi- and interdisciplinary research as an instance of collective heuristic problem-solving. Our goal is to provide a basic representation of this type of problem-solving and chart the epistemic benefits and costs of researchers engaging in different forms of cognitive coordination. Our findings suggest that typical forms of interdisciplinary collaboration are unlikely to find optimal solutions to complex problems within short time frames and can lead to methodological conservatism. This provides some grounds both for reflecting on current science policy and envisioning more effective scientific practices with respect to interdisciplinary problem-solving.