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Ignoring Complexity

Epistemic Wagers and Knowledge Practices among Synthetic Biologists

Bibliographic Data

ID5337185
AuthorsT Dan-Cohen (0000-0002-2578-2366, Washington University in St. Louis, corresponding author)
Year2016
Volume41
Issue5
Pages899-921
Publication date2016-09-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueScience Technology & Human Values (JOURNAL)
Journal identifiersISSN: 0162-2439 • E-ISSN: 1552-8251
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/0162243916650976
OpenAlexW2468692928
LanguageEN
Citations received11
References cited29

This paper links two domains of recent interest in science and technology studies, complexity and ignorance, in the context of knowledge practices observed among synthetic biologists. Synthetic biologists are recruiting concepts and methods from computer science and electrical engineering in order to design and construct novel organisms in the lab. Their field has taken shape amidst revised assessments of life's complexity in the aftermath of the Human Genome Project. While this complexity is commonly taken to be an immanent property of biological systems, this article presents an epistemological view of complexity according to which complexity relates to a specific scientific theory or model and refers to that which exceeds the theory or model's explanatory power. This epistemological view allows us to narrate a particular story about the changing relationship between biology and synthetic biology in the last decade and accounts for early knowledge practices in synthetic biology that "ignored" biology. This article further argues that while the failure of ignorance to produce clear-cut results for synthetic biologists has led practitioners back to biology, the entanglements between different pragmatic orientations and ways of knowing trouble the implications of this return for assessments of the complexity of biological systems

Biology · Computational biology · Data science · Epistemology · Ignorance · Synthetic biology · Cell Image Analysis Techniques · Computer Science · Evolution and Genetic Dynamics · Gene Regulatory Network Analysis · Mathematics · Philosophy

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Unique citing works11
Citations per year1,22
Citation span2017 - 2025 (9)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 11

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