Data

Birch, Kean

doi:10.1007/978-3-031-46402-7_2

Kean Birch²

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Abstract

Digital personal data are always a construct or artefact of the digital architectures implicated in its collection: data cannot exist without this architecture. Drawing on James C. Scott’s work on statecraft, I define this practice of data construction as techcraft to help analyse how digital technology designers and developers find ways to make personal data legible, measurable, and valuable. Unfortunately, this techcraft practice obscures the fact that personal data are relational, meaning that they have impacts beyond the relevant individual(s), and entail emergent properties that change data’s qualities when it’s combined and aggregated. Perhaps the most important dimension of personal data is their reflexive nature, in that the framing, collection, and use of data—through techcraft practices—actually ends up changing it in unpredictable and often counter-performative ways as individuals alter their behaviours, preferences, and decisions in light of changing understandings of their ‘data twins’.

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Notes

1.
Gitelman, L. and Jackson, V. (2013) Introduction, in L. Gitelman (ed.), “Raw Data” Is an Oxymoron, Cambridge, MA: MIT Press; also see Hoeyer, K. (2023) Data Paradoxes, Cambridge, MA: MIT Press.
2.
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3.
Examples include: van Dijck, J. (2014) Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology, Surveillance & Society 12(2): 197–208; Helmond, A. (2015) The platformization of the web: making web data platform ready, Social Media + Society 1(2): 1–11; Nieborg, D. and Poell, T. (2018) The platformization of cultural production: Theorizing the contingent cultural commodity, New Media & Society 20(11): 4275–4292; West, S.M. (2019) Data capitalism: Redefining the logics of surveillance and privacy, Business & Society 58(1): 20–41; Blanke, T. and Pybus, J. (2020) The material conditions of platforms: Monopolization through decentralization, Social Media + Society 6(4): https://doi.org/10.1177/2056305120971632; and Wu, A.X., Taneja, H. and Webster, J. (2021) Going with the flow: Nudging attention online, New Media & Society 23(10): 2979–2998.
4.
For example, see Edwards, L. (2018) Data protection: Enter the general data protection regulation, in L. Edwards (ed.), Law, Policy and the Internet, Oxford: Hart, pp. 77–117; Prainsack, B. (2020) The value of healthcare data: To nudge, or not?, Policy Studies 41(5): 547–562; Hansen, K.B. and Borch, C. (2022) Alternative data and sentiment analysis: Prospecting non-standard data in machine learning-driven finance, Big Data & Society 9(1): https://doi.org/10.1177/20539517211070701; and Jacobsen, B. (2023) Machine learning and the politics of synthetic data, Big Data & Society 10(1): https://doi.org/10.1177/20539517221145372.
5.
See Birch, K. (forthcoming) Assetization as a mode of techno-economic governance: Knowledge, education, and personal data in the UN’s System of National Accounts, Economy & Society.
6.
Quoted in OECD (2022) Going Digital Toolkit Note: Measuring the Economic Value of Data, Paris: Organisation for Economic Co-operation and Development; somewhat tautologically, the OECD defines “observable phenomena” as a fact or situation that can be recorded.
7.
OECD (2013) Exploring the Economics of Personal Data: A Survey of Methodologies for Measuring Monetary Value, Paris: Organisation for Economic Co-operation and Development; and Eben, M. (2018) Market definition and free online services: The prospect of personal data as price, I/A: A Journal of Law and Policy for the Information Society 14(2): 227–281.
8.
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9.
OECD (2022) Going Digital Toolkit Note: Measuring the Economic Value of Data, Paris: Organisation for Economic Co-operation and Development; and WEF (2011) Personal Data: The Emergence of a New Asset Class. Geneva: World Economic Forum.
10.
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11.
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12.
Edwards, L. (2018) Data protection: Enter the general data protection regulation, in L. Edwards (ed.), Law, Policy and the Internet, Oxford: Hart, pp. 77–117.
13.
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14.
Edwards, L. (2018) Data protection: Enter the general data protection regulation, in L. Edwards (ed.), Law, Policy and the Internet, Oxford: Hart, pp. 77–117.
15.
Spiekermann, S. and Korunovska, J. (2017) Towards a value theory for personal data, Journal of Information Technology 32: 62–84.
16.
Obviously, I’m not the only one to think this: there is a growing debate about how to value data as an economic object, including discussions by statistical agencies in the USA, UK, Canada, Netherlands, and elsewhere, as well as statistical offices of international organizations like the UN and OECD. See Coyle, D. and Manley, A. (2022) What Is the Value of Data? A Review of Empirical Methods, Bennett Institute for Public Policy, University of Cambridge.
17.
See, for example: OECD (2022) Going Digital Toolkit Note: Measuring the Economic Value of Data, Paris: Organisation for Economic Co-operation and Development; and Purtova, N. and van Maanen, G. (forthcoming) Data as an economic good, data as a commons, and data governance, Law, Innovation, and Technology.
18.
Cohen, J. (2019) Between Truth and Power, Oxford: Oxford University Press; although ‘data’ are not ownable per se, some countries and jurisdictions do allow property rights for databases since they represent a particular arrangement and structuring of data, equivalent to copyright.
19.
See Parsons, A. (forthcoming) The shifting economic allegiance of capital gains, Florida Tax Review 26; U of Colorado Law Legal Studies Research Paper No. 22-19, Available at SSRN: https://ssrn.com/abstract=4152114 or http://dx.doi.org/10.2139/ssrn.4152114.
20.
Viljoen, S. (2020) Democratic data: A relational theory for data governance, Yale Law Review, available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3727562.
21.
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22.
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23.
Beauvisage, T. and Mellet, K. (2020) Datassets: Assetizing and marketizing personal data, in K. Birch and F. Muniesa (eds.), Assetization, Cambridge, MA: MIT Press, pp. 75–95; and Helmond, A. and van der Vlist, F. (2023) Situating the marketization of data, in K. van Es and N. Verhoeff (eds.), Situating Data, Amsterdam: Amsterdam University Press, pp. 279–286.
24.
Guay, R. and Birch, K. (2022) A comparative analysis of data governance: Socio-technical imaginaries of digital personal data in the USA and EU (2008–2016), Big Data & Society 9(2): 1–13.
25.
Nissenbaum, H. (2017) Deregulating collection: Must privacy give way to use regulation? Available at SSRN: https://ssrn.com/abstract=3092282 or https://doi.org/10.2139/ssrn.3092282.
26.
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27.
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28.
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29.
Edwards, L. (2018) Data protection: Enter the general data protection regulation, in L. Edwards (ed.), Law, Policy and the Internet, Oxford: Hart, pp. 77–117.
30.
https://gdpr-info.eu/.
31.
Birch, K., Cochrane, D.T. and Ward, C. (2021) Data as asset? The measurement, governance, and valuation of digital personal data by big tech, Big Data & Society 8(1): 1–15.
32.
Scott, J. (1998) Seeing Like a State, New Haven: Yale University Press.
33.
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34.
Hwang, T. (2020) Subprime Attention Crisis, New York: FSG Originals x Logic.
35.
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36.
Wu, A.X., Taneja, H. and Webster, J. (2021) Going with the flow: Nudging attention online, New Media & Society 23(10): 2979–2998.
37.
https://ads.tiktok.com/help/article/all-metrics?redirected=2#.
38.
https://support.google.com/google-ads/answer/2375431?hl=en&ref_topic=3119144&sjid=2053450622374324604-NA.
39.
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40.
See this website for other examples of metrics: https://www.adriel.com/blog/advertising-metrics-benchmarks.
41.
Renieris, E. (2023) Beyond Data, Cambridge, MA: MIT Press.
42.
McDonald, S.M. (2021) Data governance’s new clothes, Waterloo: Centre for International Governance Innovation, available at: https://www.cigionline.org/articles/data-governances-new-clothes/.
43.
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44.
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45.
Esayas, S. (2017) The idea of ‘emergent properties’ in data privacy: Towards a holistic approach, International Journal of Law and Information Technology 25: 139–178.
46.
Sadowski, J. (2019) When data is capital: Datafication, accumulation, and extraction, Big Data & Society 9: 1–12.
47.
https://theconversation.com/personal-data-isnt-the-new-oil-its-a-way-to-manipulate-capitalism-126349.
48.
https://www.facebook.com/help/112146705538576.
49.
https://nymag.com/intelligencer/2018/12/how-much-of-the-internet-is-fake.html.
50.
Tepper, J. and Hearn, D. (2019) The Myth of Capitalism, New Jersey: Wiley.
51.
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52.
One example is Augustine Fou, who writes regularly about online ad scams: https://www.forbes.com/sites/augustinefou/?sh=42b0b2dbdb68.

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Toronto, ON, Canada
Kean Birch

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Birch, K. (2023). Data. In: Data Enclaves. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-46402-7_2

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DOI: https://doi.org/10.1007/978-3-031-46402-7_2
Published: 10 November 2023
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-031-46401-0
Online ISBN: 978-3-031-46402-7
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