Researchers in the biological and biomedical sciences, particularly those working in laboratories, use a variety of artifacts to help them perform their cognitive tasks. This paper analyses the relationship between researchers and cognitive artifacts in terms of integration. It first distinguishes different categories of cognitive artifacts used in biological practice on the basis of their informational properties. This results in a novel classification of scientific instruments, conducive to an analysis of the cognitive interactions between researchers and artifacts. It then uses (...) a multidimensional framework in line with complementarity-based extended and distributed cognition theory to conceptualize how deeply instruments in different informational categories are integrated into the cognitive systems of their users. The paper concludes that the degree of integration depends on various factors, including the amount of informational malleability, the intensity and kind of information flow between agent and artifact, the trustworthiness of the information, the procedural and informational transparency, and the degree of individualisation. (shrink)

Drawing on a range of literature, I introduce two new concepts for understanding and exploring distributed cognition: resilience engineering and degeneracy. By re-examining Ed Hutchins’ (1995) ethnographic study of the navigation team I show how a focus on the developmental acquisition of cognitive practices can draw out several crucial insights that have been overlooked. Firstly, that the way in which agents learn and acquire cognitive practices enables a form of resilience engineering: the process by which the system is able to (...) overcome and adapt to errors and the vagaries of nature. Secondly, that the best way to engineer a resilient system is through promoting degeneracy – how differing structures produce the same function – at the level of cognitive practices. These two features show that focusing on cognitive practices and developmental trajectories is important for both greater explanatory leverage; and is also useful in regard to the practicalities of designing real-world cognitive systems. (shrink)