Computational epistemology and e-science: A new way of thinking [Book Review]

Minds and Machines 19 (4):557-567 (2009)
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Abstract

Recent trends towards an e-Science offer us the opportunity to think about the specific epistemological changes created by computational empowerment in scientific practices. In fact, we can say that a computational epistemology exists that requires our attention. By ‘computational epistemology’ I mean the computational processes implied or required to achieve human knowledge. In that category we can include AI, supercomputers, expert systems, distributed computation, imaging technologies, virtual instruments, middleware, robotics, grids or databases. Although several authors talk about the extended mind and computational extensions of the human body, most of these proposals don’t analyze the deep epistemological implications of computer empowerment in scientific practices. At the same time, we must identify the principal concept for e-Science: Information . Why should we think about a new epistemology for e-Science? Because several processes exist around scientific information that require a good epistemological model to be understood.

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Citations of this work

Ecological-enactive scientific cognition: modeling and material engagement.Giovanni Rolla & Felipe Novaes - 2022 - Phenomenology and the Cognitive Sciences 21 (3):625-643.
E-Science and the data deluge.David Casacuberta & Jordi Vallverdú - 2014 - Philosophical Psychology 27 (1):1-15.
Governing ignorance through abduction.Lorenzo Magnani - 2021 - Logic Journal of the IGPL 29 (4):409-424.

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References found in this work

Color perception (in 3000 words).Austen Clark - 1998 - In George Graham & William Bechtel (eds.), A Companion to Cognitive Science. Blackwell.

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