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12 MAY 2013

With Enough Data, the Numbers Speak for Themselves...

"Not a chance. The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or employee productivity. But many big–data evangelists avoid taking a hard look at the weaknesses. Numbers can't speak for themselves, and data sets –– no matter their scale –– are still objects of human design. The tools of big–data science, such as the Apache Hadoop software framework, do not immunize us from skews, gaps, and faulty assumptions. Those factors are particularly significant when big data tries to reflect the social world we live in, yet we can often be fooled into thinking that the results are somehow more objective than human opinions. Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation."

(Kate Crawford, 12 May 2013, Foreign Policy)

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TAGS

Apache Hadoop • biasbig data • big-data science • blind spot • causal relationshipscausationcodecomputer utopianism • consumer spending • criminal actscyberspacedata abstractiondata analysisdata collection and analysisdataset • Foreign Policy (magazine) • globalisationhealthy habitsimplicit informationimplicit meaningInternetinternet utopianism • looking at the numbers • network ecologynetworked society • objects of human design • patterns of human behaviourpatterns of meaningquantified measurementreliability and validityscientific ideas • security intelligence • social world • terrorist acts • Twitterunderlying order • universal insights • universal methoduniversal rationality

CONTRIBUTOR

Simon Perkins
12 MARCH 2011

Scientists revise their criteria of rationality as they enter new domains

"The conventional model of science, technology and society locates sources of violence in politics and ethics, that is, in the application of science and technology, not in scientific knowledge itself.

The fact–value dichotomy is a creation of modern, reductionist science which, while being an epistemic response to a particular set of values, claims to be independent of values. According to the received view, modern science is the discovery of the properties of nature in accordance with a 'scientific method' which generates 'objective', 'neutral', 'universal' knowledge. This view of modern science as a description of reality as it is, unprejudiced by value, can be rejected on at least four grounds.

All knowledge, including modern scientific knowledge, is built through the use of a plurality of methodologies. As Feyerabend observes:

There is no 'scientific method'; there is no single procedure, or set of rules that underlines every piece of research and guarantees that it is 'scientific' and, therefore, trustworthy. The idea of a universal and stable method that is an unchanging measure of adequacy and even the idea of a universal and stable rationality is as unrealistic as the idea of a universal and stable measuring instrument that measures any magnitude, no matter what the circumstances. Scientists revise their standards, their procedures, their criteria of rationality as they move along and perhaps entirely replace their theories and their instruments as they move along and enter new domains of research (Feyerband, 1978, p. 98).

The view that science is just a discovery of facts about nature does not get support from philosophy either. If scientific knowledge is assumed to give true, factual knowledge of 'reality as it is', then we would have to 'conclude that Newtonian theory was true until around 1900, after which it suddenly became false, while relativity and quantum theories became the truth' (Bohm, 1981, p. 4)."

(Vandana Shiva, 1990)

1). Shiva, V. (1990). 'Reductionist science as epistemological violence'. 'Science, Hegemony and Violence: A Requiem for Modernity'. A. Nandy, Oxford University Press: 314.

Paul Feyerabend, Science in a Free Society (London: New Left Books, 1978).

David Bohm, Wholeness and the Implicate Order (London: Routledge and Kegan Paul, 1981).

TAGS

analytical thinkingCartesiancultural valuesdescription of realitydiscoursediscoverydiscursive fieldepistemologyethicsfactual knowledgehierarchy of legitimacyIsaac Newtonknowledge • logical-analytical • logical-analytical paradigmmeasuring instrument • model of science • Modernmodern science • modern scientific knowledge • myth of neutralityobjectiveobjective reality • Paul Feyerband • plurality of methodologies • positivismproperties of naturerationalityreductionism • reductionist science • researchresearch methodsciencescientific knowledgescientific method • scientific options • sociology • stable knowledge • stable rationality • theorytraditiontrust • trustworthy • truthuniversal • universal knowledge • universal methoduniversal rationalityVandana Shiva

CONTRIBUTOR

Simon Perkins
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