Understanding ‘anticipatory governance’
By David H. Guston. Social Studies of Science, 2014
645 citations recorded by the source corpus.
Anticipatory governance is ‘a broad-based capacity extended through society that can act on a variety of inputs to manage emerging knowledge-based technologies while such management is still possible’. It motivates activities designed to build capacities in foresight, engagement, and integration – as well as through their production ensemble. These capacities encourage and support the reflection of scientists, engineers, policy makers, and other publics on their roles in new technologies. This article reviews the early history of the National Nanotechnology Initiative in the United States, and it further explicates anticipatory governance through exploring the genealogy of the term and addressing a set of critiques found in the literature. These critiques involve skepticism of three proximities of anticipatory governance: to its object, nanotechnology, which is a relatively indistinct one; to the public, which remains almost utterly naïve toward nanotechnology; and to technoscience itself, which allegedly renders anticipatory governance complicit in its hubris. The article concludes that the changing venues and the amplification within them of the still, small voices of folks previously excluded from offering constructive visions of futures afforded by anticipatory governance may not be complete solutions to our woes in governing technology, but they certainly can contribute to bending the long arc of technoscience more toward humane ends.
Subfields: Biomedical Engineering, Cognitive Neuroscience, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/cf7bb07f807583c20567ccd2583dc54284eaff51
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Citations in the corpus
- Exploring the normative turn in regional innovation policy: responsibility and the quest for public value (2019, positive): “articulations of RRI have sought to expand longstanding frameworks dealing with the ethical, legal and societal aspects to contribute to their governance (Balmer et al., 2016; Guston, 2014).”
- Machine learning, social learning and the governance of self-driving cars (2018, background): “The ends enabled by technological innovation are typically hard to anticipate and hard to challenge, in part because of innovators’ lack of reflexivity about uncertainties and contingencies (Guston, 2014).”