Seeing like a market
Open accessPublished version of a preprint
Abstract
What do markets see when they look at people? Information dragnets increasingly yield huge quantities of individual-level data, which are analyzed to sort and slot people into categories of taste, riskiness or worth. These tools deepen the reach of the market and define new strategies of profit-making. We present a new theoretical framework for understanding their development. We argue that (a) modern organizations follow an institutional data imperative to collect as much data as possible; (b) as a result of the analysis and use of this data, individuals accrue a form of capital flowing from their positions as measured by various digital scoring and ranking methods; and (c) the facticity of these scoring methods makes them organizational devices with potentially stratifying effects. They offer firms new opportunities to structure and price offerings to consumers. For individuals, they create classification situations that identify shared life-chances in product and service markets. We discuss the implications of these processes and argue that they tend toward a new economy of moral judgment, where outcomes are experienced as morally deserved positions based on prior good actions and good tastes, as measured and classified by this new infrastructure of data collection and analysis.
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In the case of eBay, reputation is not 'there' to facilitate exchange; rather, reputation is the result of evaluative infrastructure's disclosing, constituting an asset described as 'ubercapital'.
“In the case of eBay, reputation is not “there” to facilitate exchange; rather, reputation is the result of evaluative infrastructure's disclosing, constituting an asset which Fourcade and Healy (2013;2016) described as “ubercapital”-the form of capital arising from the “digital record” which evaluative infrastructure unfurls.”
From Evaluative infrastructures: Accounting for platform organization (2017) · cites this paper as Fourcade and Healy, 2016
Cites
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Barocas, S., & Selbst, A. D. (2014) · doi:10.2139/ssrn.2477899 · Cited by 3,048 · see citing works
Exposed: Desire and Disobedience in the Digital Age
Harcourt, B. E. (2015) · doi:10.4159/9780674915077 · Cited by 193 · see citing works
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Evaluative infrastructures: Accounting for platform organization
Kornberger, M., Pflueger, D., & Mouritsen, J. (2017) · Accounting Organizations and Society · doi:10.1016/j.aos.2017.05.002 · Cited by 349 · see citing works
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“Although in the modern neoliberal era, markets have been an emerging force in categorization and segmentation [39], the entity tasked with categorization above all others has been the state.”
BackgroundTechnologies of Crime Prediction: The Reception of Algorithms in Policing and Criminal Courts
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- Authors
- Fourcade, M., & Healy, K.
- Affiliations
- University of California, Berkeley (US)
- Duke University (US)
- Corresponding author
- Fourcade, Marion
- Healy, Kieran
- Venue
- Socio-Economic Review
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-12-23
- Pages
- mww033
- ISSN
- 1475-1461 (ISSN-L)
- 1475-147X
- OpenAlex
- W2562793958
- Cited by
- 474
- References
- 3
- Citations by year
- 2026: 28 · 2025: 40 · 2024: 64 · 2023: 37 · 2022: 38 · 2021: 93 · 2020: 105 · 2019: 41 · 2018: 15 · 2017: 9 · 2016: 2 · 2015: 1
- FWCI
- 54.55
- Type
- journal article
- Language
- en
- Open access
- green
- escholarship.org
- Locations
- Socio-Economic Review (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Yale University
- University of California, Santa Cruz
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Communication › Cultural Studies and Postmodernism
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- data-driven markets, microdata, classification, stratification, moral judgment, consumer classification, pricing strategy
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