Algorithmic Ideology. How capitalist society shapes search engines

By Astrid Mager. 2014

217 citations recorded by the source corpus.

Information, Communication & Society 2012, pp. 1-19, iFirst Article This article investigates how the new spirit of capitalism gets inscribed in the fabric of search algorithms by way of social practices. Drawing on the tradition of the social construction of technology (SCOT) and 17 qualitative expert interviews it dis- cusses how search engines and their revenue models are negotiated and stabilized in a network of actors and interests, website providers and users first and foremost. It further shows how corporate search engines and their capitalist ideology are solidi- fied in a socio-political context characterized by a techno-euphoric climate of inno- vation and a politics of privatization. This analysis provides a valuable contribution to contemporary search engine critique mainly focusing on search engines’ business models and societal implications. It shows that a shift of perspective is needed from impacts search engines have on society towards social practices and power relations involved in the construction of search engines to renegotiate search engines and their algorithmic ideology in the future.

Subfields: Marketing, Sociology and Political Science

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Citations in the corpus

Governance by algorithms: reality construction by algorithmic selection on the Internet (2017, unknown): “The perspective on algorithms as ideologies (Mager, 2012) reflects this situation.”
Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology (2014, background): “…privacy policies and surveillance tactics to be quite limited; individuals are steered by platforms’ technologies and business models of single platforms while it is extremely hard to gain insight in the system’s interdependence and complexity (Draper 2012; Hartzog and Selinger 2013; Mager 2012).”
Human-Computer Insurrection: Notes on an Anarchist HCI (2019, background): “tures under capitalism, and even absent capitalism, infrastructure enacts control and hegemony [26, 109]; this is nowhere more apparent than in the infrastructures HCI researchers actively help build [98, 141]. Consequently from both an anti-oppressive and autonomous perspective, an anarchistHCIisat”
Algorithmic Transparency in the News Media (2017, unknown): “These values, biases, or ideologies (Mager 2012) can create consequences for the formation of publics and the fair and unbiased provision of information (Gillespie 2014).”
Mapping the field of Algorithmic Journalism (2016, methodology): “With algorithms editing, aggregating, publishing, and distributing content, processes of media production and consumption are increasingly being automated (Broussard 2014; Diakopoulos 2014; Gillespie 2014; Mager 2012; Napoli 2014; Pavlik 2013).”
Thinking critically about and researching algorithms (2014, unknown): “, 2011), or with respect to their political economy and the reproduction of capitalism (Mager 2012), or from a legal or regulatory perspective, and other methods might be deployed such as ethnomethodology or surveys.”
Governance of algorithms: options and limitations (2015, unknown): “Increasing automation (Steiner, 2012) and the power of technology are discussed by researchers and journalists who focus on the role of code and algorithms as agents (Machill and Beiler, 2007), institutions (Napoli, 2013; Katzenbach, 2011), ideologies (Mager, 2012), gatekeepers (Jürgens et al.”
What are algorithmic cultures (2016, unknown): “…notes something similar when he underscores that "more than mere tools, algorithms are also stabilizers of trust, practical and symbolical assurances that their evaluations are fair and accurate, free from sub jectivity, error, or attempts at influence" (Gillespie 20 I 4, 179; see also Mager 2012).”
The Relevance of Algorithms (2013, background): “Mager (2012) e Van Couvering (2010) propõem que os princípios do capitalismo estão incorporados no funcionamento das ferramentas de busca.”
The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity (2019, unknown): “…algorithm studies have examined algorithms directed toward constituents outside the organization, such as platform users (Bucher 2012, 2017; Mager 2012; Willson 2017), customers (Crawford 2015), consumers (Carah 2015), or freelance workers (Kushner 2013) but less on algorithms influencing…”
Algorithmic Accountability (2015, background): “More recent research has considered how values (Fleischmann and Wallace 2010) or even ideologies (Mager 2012) manifest themselves in computational models, as well as how such biases are observed in media systems (Bozdag 2013; Gillespie 2014).”
Heuristics of the algorithm: Big Data, user interpretation and institutional translation (2015, background): “…taking up Big Data as a heuristic – or if it is more a case of powerful institutions using the discourse or ‘myth’ of ‘Big Data’ (Boyd and Crawford, 2012; cf. Boellstorﬀ, 2013) to foster an almost religiously tainted ‘dataism’, as van Dijck (2014) calls this structure of belief (cf. Mager, 2012).”