Science as Culture (SaC) Forum on “Big Tech”
Forum Editor: Kean Birch
Big Tech is in the spotlight. Usually defined as Apple, Amazon, Microsoft, Google/Alphabet, and Facebook, “Big Tech” has become a watchword for corporate surveillance, monopoly, and market power. Arguably, they are the defining institutions of our day, dominating our political economies, societies, and polities as Big Oil or Big Banks did in their time. Criticism of Big Tech is increasingly evident as well, cutting across popular books, academic work, film, and journalism: examples include, Shoshana Zuboff’s 2019 book The Age of Surveillance Capitalism; recent documentaries like Social Dilemma and Agents of Chaos; and regular column inches in print media like the Financial Times and The Economist, this being particularly notable as these two are intellectual bastions of capitalism. Furthermore, Big Tech has been the subject of critical political investigations, like the recent US Congressional Hearings on Online Platforms and Market Power, or the International Grand Committee on Big Data, Privacy and Democracy.
Although Big Tech is facing the glare of negative publicity, there is a notable absence of discussion about it in science and technology studies (STS), with some exceptions (e.g. Birch et al. 2020a, 2020b; Fourcade and Kluttz 2020; Geiger 2020; Sadowski 2020). Cognate fields – like information science, communication studies, law, algorithm or data studies, and so forth – have engaged with particular aspects of Big Tech or its antecedents (e.g. Gillespie 2014; Pasquale 2015; Roseblat and Stark 2016; O’Neil 2017; Noble 2018). For example, in analyses of how digital platforms and technologies reinforce social discrimination or disrupt political process.
But STS as a field has not engaged analytical or empirically with ‘Big Tech’ as a specific and perhaps still emergent configuration of contemporary, technoscientific capitalism underpinned by monopoly and market power (Birch 2020; Birch and Muniesa 2020). Such configurations entail the techno-economic measurement and management of social relations and action, performatively driven by a particular techno-economic logic. For example, research on digital data illustrates the configuring of organizational practices by an “imperative to collect as much data as possible” (Fourcade and Healy, 2017). These data are necessarily scored and ranked in particular ways (e.g. individually), thereby re-configuring organizations in the process (ibid.). Similar techno-economic assumptions have been analysed for innovation more generally (Birch, 2017).
Here, STS scholars are ideally placed to unpack and explore the techno-economic assumptions and knowledge claims, measurement tools and standards, organizational practices and expertise, innovation and business strategies, and policy debates underpinning the ascendance of Big Tech. All such aspects are normative as much as they are constitutive, reflecting key public debates right now about Big Tech’s monopoly or market power derived from digital network effects, threats to privacy in its collection of personal data as an asset, and role in generating new political-economic inequalities through automation, algorithms, and platforms.
This SaC Forum seeks to engage scholars in an STS analysis of Big Tech, especially their role in science, technology, innovation, and expertise more generally. Submissions should address questions like the following:
- What are the different ways to analyse Big Tech as a techno-economic configuration?
- In what ways are digital technologies different – or not – from other technologies in configuring market power?
- How do some digital components (e.g. technologies, platforms, networks) become monopolistic?
- In what ways is digital data – personal, health, etc. – a key constituent of Big Tech’s dominance?
- What technoscientific and economic knowledges, expertise, and organizational practices underpin Big Tech?
- How might digital technologies have politics or political economy (Winner 1980)?
- What role does and should Big Tech have in society? In ethics? In politics?
- What alternatives are there to Big Tech?
- In discussing the above questions, how should we define Big Tech?
Details
- Deadline: end of February 2021
- Length: flexible, ranging between 2k-6k words.
- Format: author’s contact details (postal address and email address) should be at the top of the file; articles should contain an Introduction and Conclusion, but are otherwise flexible. Forum pieces have key words but no Abstracts, so the Conclusion should summarise the overall argument.
- Contact: please email Kean Birch (keanbirch@gmail.com) with queries about suitability or abstract proposals.
- Submission: send submissions to both Les Levidow (L.Levidow@open.ac.uk) and Kean Birch (keanbirch@gmail.com); forum articles will be reviewed by both Les and Kean, but will not be sent out for peer review.
- Full-scale papers (10k words maximum) are also welcome. But these would need to follow the SaC editorial guidelines and undergo the normal referee procedure through the online system. If not ready in time for the Forum, they will be published in a later issue.
- See https://www.tandf.co.uk/journals/authors/csac_edit_guidelines.pdf
References
Birch, K. (2017) Guest Introduction: Techno-economic assumptions, Science as Culture26(4): 433-44; special issue, https://www.tandfonline.com/action/doSearch?AllField=economic+assumptions&SeriesKey=csac20
Birch, K. (2020) Automated neoliberalism? The digital organisation of markets in technoscientific capitalism, New Formations 100-101: 10-27.
Birch, K. and Muniesa, F. (eds) (2020) Assetization: Turning Things into Assets in Technoscientific Capitalism, Cambridge MA: MIT Press.
Birch, K., Chiappetta, M. and Artyushina, A. (2020a) The problem of innovation in technoscientific capitalism: Data rentiership and the policy implications of turning personal digital data into a private asset, Policy Studies 41(5): 468-487.
Birch, K., Cochrane, D.T. and Ward, C. (2020b) Data as (intangible) asset? Unpacking the governance and valuation of digital personal data in Big Tech firms, unpublished manuscript.
Fourcade, M. and Healy, K. (2017) Seeing like a market, Socio-Economic Review 15(1): 9-29.
Fourcade, M. and Kluttz, D. (2020) A Maussian bargain: Accumulation by gift in the digital economy, Big Data & Society, doi: 10.1177/2053951719897092
Geiger, S. (2020) Silicon Valley, disruption, and the end of uncertainty, Journal of Cultural Economy 13(2): 169-184.
Gillespie, T. (2014) The Relevance of Algorithms, in T.Gillespie, P.Boczkowski, and K.Foot (eds), Media Technologies. Cambridge MA: MIT Press.
Noble, S. (2018) Algorithms of Oppression. New York: New York University Press.
O’Neil, C. (2017) Weapons of Math Destruction, New York: Broadway Books
Pasquale, F. (2015) The Black Box Society, Cambridge MA: Harvard University Press.
Rosenblat, A. and Stark, L. (2016) Algorithmic labor and information asymmetries: A case study of Uber’s drivers, International Journal of Communication 10: 3758-3784.
Sadowski, J. (2020) The internet of landlords: Digital platforms and new mechanisms of rentier capitalism, Antipode 52(2): 562-580.
Winner, L. (1980) Do Artifacts Have Politics?, Daedalus 109(1): 121-136.
Zuboff, S. (2019) The Age of Surveillance Capitalism, New York: Public Affairs.