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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Notes
”Science and Democratic Social Structure” in Social Theory and Social Structure—Enlarged Edition, New York: The Free Press, 1968. The article was first published in 1942 as “A Note on Science and Democracy”, Journal of Legal and Political Sociology 1: 115–126.
Reliable Knowledge, Cambridge University Press, 1978. pp. 6–8.
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Garbage In, Garbage Out (abbreviated to GIGO) is an aphorism in the field of computer science. It refers to the fact that computers, unlike humans, will unquestioningly process the most nonsensical of input data and produce nonsensical output. It was most popular in the early days of computing, but has fallen out of use as programs have become more sophisticated and now usually have checks built into reject improper input. Font: http://www.en.wikipedia.org/wiki/Garbage_in,_garbage_out.
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Acknowledgment
This is an ongoing project I am developing at my university. This research has been developed under the main activities of the TECNOCOG research group (UAB) about Cognition and Technological Environments, [HUM2005-01552], funded by MEC (Spain).
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Vallverdú i Segura, J. Computational Epistemology and e-Science: A New Way of Thinking. Minds & Machines 19, 557–567 (2009). https://doi.org/10.1007/s11023-009-9168-0
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DOI: https://doi.org/10.1007/s11023-009-9168-0