Machine Habitus. Massimo Airoldi. Читать онлайн. Newlib. NEWLIB.NET

Автор: Massimo Airoldi
Издательство: John Wiley & Sons Limited
Серия:
Жанр произведения: Социология
Год издания: 0
isbn: 9781509543298
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and beyond to platform-based machine learning systems. This socio-technical evolution can be roughly broken into three main eras, visually summarized in Figure 1 at the end of this section. Without pretending to be exhaustive, the proposed periodization focuses especially on the emergence of ‘public relevance algorithms’ (Gillespie 2014: 168), that is, automated systems dealing with the social matter of human knowledge, experience and practice.

      With supercomputers making their appearance in companies and universities, the automated processing of information became increasingly embedded into the mechanisms of post-war capitalism. Finance was one of the first civil industries to systematically exploit technological innovations in computing and telecommunications, as in the case of the London Stock Exchange described by Pardo-Guerra (2010). From 1955 onwards, the introduction of mechanical and digital technologies transformed financial trading into a mainly automated practice, sharply different from ‘face-to-face dealings on the floor’, which had been the norm up to that point.

      From the late 1970s, the development of microprocessors and the subsequent commercialization of personal computers fostered the popularization of computer programming. By entering people’s lives at work and at home – e.g. with videogames, word processors, statistical software, etc. – computer algorithms were no longer the reserve of a few scientists working for governments, large companies and universities (Campbell-Kelly et al. 2013). The digital storage of information, as well as its grassroots creation and circulation through novel Internet-based channels (e.g. emails, Internet Relay Chats, discussion forums), translated into the availability of novel data sources. The automated processing of large volumes of such ‘user-generated data’ for commercial purposes, inaugurated by the development of the Google search engine in the late 1990s, marked the transition toward a third era of algorithmic applications.