An engineering paradigm in the biomedical sciences: Knowledge as epistemic tool

Abstract

In order to deal with the complexity of biological systems and attempts to generate applicable results, current biomedical sciences are adopting concepts and methods from the engineering sciences. Philosophers of science have interpreted this as the emergence of an engineering paradigm, in particular in systems biology and synthetic biology. This article aims at the articulation of the supposed engineering paradigm by contrast with the physics paradigm that supported the rise of biochemistry and molecular biology. This articulation starts from Kuhn's notion of a disciplinary matrix, which indicates what constitutes a paradigm. It is argued that the core of the physics paradigm is its metaphysical and ontological presuppositions, whereas the core of the engineering paradigm is the epistemic aim of producing useful knowledge for solving problems external to the scientific practice. Therefore, the two paradigms involve distinct notions of knowledge. Whereas the physics paradigm entails a representational notion of knowledge, the engineering paradigm involves the notion of 'knowledge as epistemic tool'.

Milestones and Outcomes in Health and Human Services Informatics Education Programmes

“…Referring to Kuhn, Boon presented an expanded vision of science, an engineering paradigm of science, highlighting the interdisciplinary nature in 'real-world' problemsolving contexts of research. Essentially, the discrepancy between 'real' and 'proposed' suggests gaps regarding issues such as value, ontology, or interoperability requiring attention, development, and ultimately adoption, demanding a universal standards framework [28]. It is also highlighted that knowledge generation and usage for solving complex real-world problems require higher-order cognitive skills, because rules or algorithms for how to use a concept, theory, model, or data in this respect are usually seen as interdisciplinary.…”

“…It is also highlighted that knowledge generation and usage for solving complex real-world problems require higher-order cognitive skills, because rules or algorithms for how to use a concept, theory, model, or data in this respect are usually seen as interdisciplinary. Thus, teaching higher-order cognitive skills is a crucial part of evolving expertise [28][29].…”

From Multidisciplinarity to Transdisciplinarity and from Local to Global Foci: Integrative Approaches to Systemic Resilience Based upon the Value of Life in the Context of Environmental and Gender Vulnerabilities with a Special Focus upon the Brazilian Amazon Biome

“…Currently, most environmental scientists deal with the complexity of eco-social systems and generate applicable results by adopting concepts and methods from the engineering sciences that have the epistemic objective of producing useful knowledge for solving problems external to scientific practice. This is interpreted by philosophers of science as the emergence of an "engineering paradigm" [125]. Interdisciplinarity is acknowledged in science-based problem-solving research (engineering) and transdisciplinarity is acknowledged in resilience research [126].…”

How Scientists Are Brought Back into Science—The Error of Empiricism

“…One may even defend that the aim of science is not useful theories, but true theories. Science may be of epistemic and practical value to all kinds of applications such as in engineering and medicine, but this is a by-product of science, not its intended aim (also see Boon 2011Boon , 2017c. Rather, science has an intrinsic cultural value in telling us what the world is like, which is a task that cannot be replaced by machine learning technologies whatsoever since incomprehensive, opaque data-models do not tell us anything meaningful about the world.…”