Similar problems play out in the area of what we might call ‘privately counted’ data. These include cases where data of significant public value is indeed gathered but is held by private companies with an interest in what part of it is publicly countable, and how. The roles of Facebook and Cambridge Analytica in the UK’s Brexit referendum and the election of Donald Trump as US President highlight the potential threat to democracy.14 Another example is that of the limitations of access to medical trial data generated by pharmaceutical companies. Ben Goldacre has shown how the failure to regulate for effective access to medical trial data results in inferior medical treatments continuing to be widely marketed and used – with human impacts up to and including large-scale excess mortality.15
Cathy O’Neil’s analysis of the biases in algorithms reveals just how far we are from the dream that big data or its use in the public or private sectors could be a tool for equalizing power. Instead, there are multiple, opaque avenues for discrimination, both deliberate and accidental, with grave implications for a range of inequalities.16 More trivially, unless you take seriously Bill Shankly’s suggestion that football surpasses life and death in importance, the Tax Justice Network’s Offshore Game project has shown how the unregulated financial secrecy used by owners can lead football fans to suffer all sorts of risks – including exploitation and even liquidation of their clubs.17
The common thread across all the cases touched on here is the relationship between power, inequality and being uncounted – a relationship that demands we pay much more attention to who and what are and are not counted. The sociologist William Bruce Cameron observed that not everything that can be counted counts, and not everything that counts can be counted.18 While this antimetabole is undoubtedly true, so, too, is another: much that goes uncounted matters, and much that matters goes uncounted.
There are reasons to be optimistic: as attention to inequality has grown, so, too, has awareness of the need to reveal the uncounted. Concerted efforts to challenge the uncounted at the bottom and the top are possible now in a way that simply was not the case even ten years ago.
The first part of this book explores the uncounted at the bottom of the distribution, ranging from international development findings to evidence of the exclusion of marginalized groups in high-income countries. The second part focuses on the uncounted at the top of the distribution. This includes the core tax justice analysis of the nature and extent of financial secrecy, the scale of revenue losses through ‘tax havens’ promoting individual tax evasion and multinational profit shifting, as well as the largely unacknowledged bias that overreliance on the Gini coefficient introduces into common perceptions of inequality. Together, the evidence points towards great damage being done to the world’s prospects for genuinely sustainable human progress – and quite unnecessarily.
The book concludes with an Uncounted Manifesto: a political and technical call to action, to change the relationships we tolerate between data, power and inequality. Before they change us any further …
Our societies owe a debt to those we have caused to go uncounted, through their marginalization. At the same time, we are owed a debt by those who conspire to hide from tax and other responsibilities. Both debts are rising by the day, and both are driving up inequality, uncounted. Before we can make the past right, we must stop the clock. We need to understand the systematic flaws that make us ignorant of ourselves and our world – and start counting as if we cared.
Notes
1 1. Michel Foucault, 1995, Discipline and Punish: The Birth of the Prison, New York: Random House (2nd ed.), p. 194.
2 2. James C. Scott, 1998, Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed, London: Yale University Press, pp. 345–346.
3 3. Alain Desrosières, 2001, ‘How “real” are statistics? Four possible attitudes’, Social Research 68, pp. 339–355.
4 4. Desrosières, ‘How “real” are statistics?’, p. 340.
5 5. Wendy Espeland and Mitchell Stevens, 2008, ‘A sociology of quantification’, European Journal of Sociology XLIX (3), pp. 401–436: p. 431.
6 6. Theodore Porter terms as ‘funny numbers’, the problem that power distorts: those that are both responsible for creating statistics, and judged upon resulting metrics, face a conflict of interest that is unlikely to give rise to good data. Theodore Porter, 2012, ‘Funny numbers’, Culture Unbound 4, pp. 585–598.
7 7. Sakiko Fukuda-Parr and Desmond McNeill, 2019, ‘Knowledge and politics in setting and measuring the SDGs: Introduction to special issue’, Global Policy 10(S1), pp. 5–15.
8 8. William Seltzer and Margo Anderson, 2001, ‘The dark side of numbers: The role of population data systems in human rights abuses’, Social Research 68(2), pp. 481–513.
9 9. Not unrelated is the idea of resistance to the set of identification possibilities that census enumeration may require – perhaps most famously, the objection to a particular categorization by insisting on ‘Jedi’ as a religious identification.
10 10. Marco Deseriis, 2015, Improper Names: Collective Pseudonyms from the Luddites to Anonymous, London: Minnesota University Press, p. 4.
11 11. Compare Muchiri Karanja, 2010, ‘Myth shattered: Kibera numbers fail to add up’, Daily Nation, 3 September: https://www.nation.co.ke/News/Kibera%20numbers%20fail%20to%20add%20up/-/1056/1003404/-/13ga38xz/-/index.html; and Paul Currion, 2010, ‘Lies, damned lies and you know the rest’, humanitarian.info, 13 September: https://web.archive.org/web/20120803154806/http://www.humanitarian.info/2010/09/13/lies-damned-lies-and-you-know-the-rest/; with, e.g., Martin Robbins, 2012, ‘The missing millions of Kibera: Africa’s propaganda trail’, Guardian, 1 August: https://www.theguardian.com/science/the-lay-scientist/2012/aug/01/africa-propaganda-kibera.
12 12. See, e.g., Duncan Green, 2010, ‘Are women really 70% of the world’s poor? How do we know?’, From Poverty to Power, 3 February: https://oxfamblogs.org/fp2p/are-women-really-70-of-the-worlds-poor-how-do-we-know/ (and the many valuable comments); and Philip Cohen, 2013, ‘“Women own 1% of world property”: A feminist myth that won’t die’, The Atlantic, 8 March: https://www.theatlantic.com/sexes/archive/2013/03/women-own-1-of-world-property-a-feminist-myth-that-wont-die/273840/. As an antidote reflecting the state of research beforehand, see Carmen Diana Deere and Cheryl Doss, 2008, ‘The gender asset gap: What do we know and why does it matter?’, Feminist Economics 12(1–2): https://doi.org/10.1080/13545700500508056; see also the whole special issue which it introduces.
13 13. James Baldwin, 1962, ‘As much truth as one can bear’, New York Times, 14 January: https://www.nytimes.com/1962/01/14/archives/as-much-truth-as-one-can-bear-to-speak-out-about-the-world-as-it-is.html.
14 14. On which the investigative work of Carole Cadwalladr at the Guardian has been invaluable.
15 15. Ben Goldacre, 2012, Big Pharma, London: Fourth