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Big Data, Cognitive Extension, Self-Organizing Processes and Economic Development
Language: Spanish This thesis is written in Spanish
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Original Spanish title:
Big Data, Amplìación Cognitiva, Procesos de Autoorganización y Desarrollo Económico
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Author
Jesús Figueres Cañadas, Universidad Autónoma de Madrid, 2017
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Academic area
Economics
Abstract
This thesis was born as an effort to improve our comprehension of the emerging phenomenon called “Big Data” and its potential impacts on the Economy, in particular Economic Development and fight against poverty. Big Data include in the first place data generated by billions of people in a decentralized way through the Social Media. Another important aspect of Big Data is the evolution of the services and business processes due to the Digital Transformation, and last, but not least, we should also consider the growing data flow originated by the Internet of Things.

Given the immensity of this challenge, the first question is targeted at exploring to what extent the current economic theories could be used as a basis for analyzing this new disruptive phenomenon, especially since many experts in the new age of Big Data are sceptical about possibility of fitting it within the existing theoretical framework due to some features that come with this phenomenon, such as: free services, shared ownership, network creativity, serendipity in social networks, hybrid decision systems, etc.

Due to the complex nature of the problem, the thesis is divided into two parts. The first part explores how the phenomenon of Big Data may fit within Economic Theory. The second part complements the first one by identifying some key elements of the Big Data and their impact on Economic Development.

Among the theoretical mainstream reviewed in the first part are the Theories of Economic Growth (Neoclassical, Keynesian and Evolutionist) that recognize the generation of knowledge as a primary motor of growth. Aside from already mentioned theories, this work also analyzes Theories of Economic Development rooted in the ideas of pioneering authors such as Adam Smith, Karl Marx or the first economists of the Austrian School, which mainly focused on social institutions and human organization. Based on this comparative analysis, the priority is given to the Austrian School of Economics since its methodological framework is the most appropriate to analyze the Big Data due to its epistemological consistency and the realism of its economic agent. A new analytical framework is defined that will allow to link Big Data, human’s cognitive extension, self-organizing processes and Economic Development.

In the second part of this thesis, a new methodology for investigation of Big Data phenomenon is suggested. The essence of it consists in carrying outwhat I call a "Generative Economic Analysis" (Theoretical and Historical) in the first place, and, secondly, in implementing a so called "Discriminative Economic Analysis" (Entrepreneurial). A new model of economic agent is introduced. It features a multidimensional cognitive system, sensitive to the essential elements of the Age of Big Data: feelings that govern actions, subjectivation (perception, attention and memory), creativity and calculation. Based on this methodology, the decentralized exploitation of the Big Data will be seen as one that extends our cognitive system and thereby transforms our entrepreneurial skills, improving the way we perceive reality, anticipate the future and save. The cognitive expansion in the Age of Big Data introduces new ways of self-organization, giving rise to macroeconomic processes such as the reduction of business costs, the evolution of the capital structure, the smoothing of the business cycles, the revaluation of human life or the conservation of natural resources and cultural heritage.

The second part of the thesis draws a conclusion that the most socially beneficial potential effects of the Big Data will not be achieved by trying to establish centralized control mechanisms over society, but rather by allowing human beings to discover new ways of cooperating with each other in a decentralized way, while taking advantage of the signaling power of the Big Data. This self-organizing processes will favor the emergence of more inclusive market institutions driven by an individual’s will to pursue the common good, thus contributing to Economic Development.