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Futures of a distributed memory. A global brain wave measurement (1800–2000)

Steffen Roth, Carlton Clark, Nikolay Trofimov, Artur Mkrtichyan, Markus Heidingsfelder, Laura Appignanesi, Miguel Pérez-Valls, Jan Berkel and Jari Kaivo-oja

Technological Forecasting and Social Change, 2017, vol. 118, issue C, 307-323

Abstract: If the global brain is a suitable model of the future information society, then one future of research in this global brain will be in its past, which is its distributed memory. In this paper, we draw on Francis Heylighen, Marta Lenartowicz, and Niklas Luhmann to show that future research in this global brain will have to reclaim classical theories of social differentiation in general and theories of functional differentiation in particular to develop higher resolution images of this brain's function and sub-functions. This claim is corroborated by a brain wave measurement of a considerable section of the global brain. We used the Google Ngram Viewer, an online graphing tool which charts annual counts of words or sentences as found in the largest available corpus of digitalized books, to analyse word frequency time-series plots of key concepts of social differentiation in the English as well as in the Spanish, French, German, Russian, and Italian sub-corpora between 1800 and 2000. The results of this socioencephalography suggest that the global brain's memory recalls distinct and not yet fully conscious biases to particular sub-functions, which are furthermore not in line with popular trend statements and self-descriptions of modern societies. We speculate that an increasingly intelligent global brain will start to critically reflect upon these biases and learn how to anticipate or even design its own desired futures.

Keywords: Global brain; Google Ngram Viewer; Culturomics; Secularization; Capitalism; Functional differentiation (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:118:y:2017:i:c:p:307-323

DOI: 10.1016/j.techfore.2017.02.031

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