Prasanna K Choudhary




France inherits a very rich and glorious intellectual-theoretical tradition. Beginning with Michel de Montaigne (1533-1592) and René Descartes (1596-1650), this tradition includes leading lights of French Enlightenment like, to name a few, Charles Louis de Montesquieu (1689-1755), François Voltaire (1694-1778), Jean-Jacques Rousseau (1712-1778), Denis Diderot (1713-1784), and Jean Antoine Condorcet (1743-1794). The French Enlightenment played a vital role in the making of modern mind. Marx’s methodology too was indebted to these great minds. This tradition was carried forward by later French thinkers as well. Even in the twentieth century, F Saussure and Claude Lévi-Strauss pioneered structuralism in linguistics and anthropology respectively. Jean Paul-Satre influenced a whole generation of intellectuals as well as activists. Simone de Beauvoir’s ‘The Second Sex’ became the guiding spirit behind the feminist movement. Émile Durkheim and his theories and hypotheses became an integral part of social science studies the world over. ‘Annales School’ found a large audience among the historians, and its clones emerged in various universities around the world. These are just a few names; it is not possible here to give even a brief description of France’s immense contribution to the intellectual wealth of humankind and their vital role in the evolution of the theory of knowledge. Many of these thinkers were system-builders and versatile genius – Descartes himself was one of the founders of analytical geometry, mathematician, physicist, physiologist, philosopher and founder of rationalism.

In this background, it is quite understandable that young Piketty’s dream was ‘to teach at the École des Hautes Études en Sciences Sociales, whose faculty has included such leading lights as Lucien Febvre, Fernand Braudel, Claude Lévi-Strauss, Pierre Bourdieu, Françoise Héritier, and Maurice Godelier, to name a few…’ He further writes, “There is one great advantage to being an academic economist in France: here economists are not highly respected in the academic and intellectual world or by political and financial elites. Hence they must set aside their contempt for other disciplines and their absurd claim to greater scientific legitimacy, despite the fact that they know almost nothing about anything. ….” Explaining his theoretical and conceptual framework, Piketty strongly criticizes ‘childish passion for mathematics .. at the expense of historical research and collaboration with other social sciences.’ ‘Economists are all too often preoccupied with petty mathematical problems of interest only to themselves. This obsession with mathematics is an easy way of acquiring the appearance of scientificity without having to answer the far more complex questions posed by the world we live in.’ Finally, he makes clear the aim behind his study – he wants to ‘contribute, however modestly, to the debate about the best way to organize society and the most appropriate institutions and policies to achieve a just social order.’ Furthermore, he ‘would like to see justice achieved effectively and efficiently under the rule of law, which should apply equally to all and derive from universally understood statutes subject to democratic debate.’ (‘Introduction/The Theoretical and Conceptual Framework’) Well said, indeed.


However, despite his somewhat emotional fondness for the French intellectual tradition and French theoreticians, his criticism of ‘childish passion for mathematics’, and his eagerness to collaborate with the other social sciences, Piketty, so far as the main theme of the book is concerned, follows the ‘big data methodology’. (His book is not a big data book in the strict sense of the term – what I am referring to is his methodology.) He appears to be consciously avoiding ‘why’, and remains content to explain ‘what’. He tells us ‘what’ the data (spread over a very long period of two centuries) reveals about the movement of inequality in the age of capital (i.e., r > g), but he desists from going into the question ‘why’ r > g. He does not critically examine existing hypotheses or theories on this question, and he himself does not advance any hypothesis or theory in this regard, and hence, does not put such hypothesis or theory to test in the light of appropriate data. In short, he deliberately avoids venturing into the field of hypotheses or theories or reasoning – he is satisfied with correlations, and does not feel the need of causal analyses.


‘With a cell phone in every pocket, a computer in every backpack, and big information technology systems in back offices everywhere’, the digital age has made it quite easy to generate, store, process and retrieve large amounts of data at a scale previously unheard-of. “In the analog age collecting and analyzing such data was enormously costly and time-consuming. New questions often meant that the data had to be collected again and the analysis started afresh. The big step toward managing data more efficiently came with the advent of digitization: making analog information readable by computers, which also makes it easier and cheaper to store and process. ….Google processes more than 24 petabytes of data per day, a volume that is thousands of times the quantity of all printed material in the US Library of Congress. Facebok, a company that did not exist a decade ago, gets more than 10 million new photos uploaded every hour. Facebook members click a ‘like’ button or leave a comment nearly three billion times per day, creating a digital trail that the company can mine to learn about users’ preferences. Meanwhile, the 800 million users of Google’s YouTube service upload over an hour of video every second. The number of messages on Twitter grows at around 200 percent a year and by 2012 had exceeded 400 million tweets a day. ….In 2013 the amount of stored information in the world is estimated to be around 1,200 exabytes (an exabyte is one billion gigabytes), of which less than 2 percent is non-digital. ….The era of big data challenges the way we live and interact with the world. Most strikingly, society will need to shed some of its obsession for causality in exchange for simple correlations: not knowing why but only what. This overturns centuries of established practices and challenges our most basic understanding of how to make decisions and comprehend reality. ….By changing the amount, we change the essence. ….The change of scale has led to a change of state. ….The quantitative change has led to a qualitative one. … As we transition from a hypothesis-driven world to a data-driven world, we may be tempted to think that we also no longer need theories.”1

“In 2008 WIRED magazine’s editor-in-chief Chris Anderson trumpeted that ‘the data deluge makes the scientific method obsolete.’ In a cover story called ‘The Petabyte Age’, he proclaimed that it amounted to nothing short of ‘the end of theory’. The traditional process of scientific discovery – of a hypothesis that is tested against reality using a model of underlying causalities – is on its way out, Anderson argued, replaced by statistical analysis of pure correlations that is devoid of theory.’2 Piketty rightly acknowledges his indebtedness to ‘recent improvements in the technology of research’, but, I hope, he does not subscribe to Anderson’s views.

However, the big data experts Viktor Mayer-Schönberger and Kenneth Cukier do not view analogs and algorithms, causality and correlation, ‘why’ and ‘what’ as dichotomous categories. They admit that big data itself is founded on theory (statistical theories, mathematical, computer science theories), and big data analysis is based on theories (how we select the data). ‘They shape both our methods and our results.’ They conclude, “We still need causal studies and controlled experiments with carefully curated data in certain cases. ….But for many everyday needs, knowing what not why is good enough. And big data correlations can point the way toward promising areas in which to explore causal relationships.”3


Amartya Sen who also grapples with the problem of inequality, justice and democracy in our modern world, derives his inspiration from the French Enlightenment. His methodology traces its origin to the ‘social choice theory’ (of Condorcet in the eighteenth century) which has been developed in the present form by the pioneering contributions of Kenneth Arrow in the mid-twentieth century (Condorcet → Kenneth Arrow → Amartya Sen). He critically examines John Rawls’s theory of justice, while developing his own views and propositions. Tracing the genesis of his own theory, he writes, “ There is a substantial dichotomy between two different lines of reasoning about justice that can be seen among two groups of leading philosophers associated with the radical thought of the Enlightenment period. One approach concentrated on identifying perfectly just social arrangements, and took the characterization of ‘just institutions’ to be the principal – and often the only identified – task of the theory of justice. Woven in different ways around the idea of hypothetical ‘social contract’, major contributions were made in this line of thinking by Thomas Hobbes in the seventeenth century, and later by John Locke, Jean-Jacques Rousseau and Immanuel Kant, among others. The contrarian approach has been the dominant influence in contemporary political philosophy, particularly since a pioneering paper (‘Justice As Fairness’) in 1958 by John Rawls which preceded his definitive statement on that approach in his classic book, ‘A Theory of Justice’.

In contrast, a number of other Enlightenment philosophers (Smith, Condorcet, Wollstonecraft, Bentham, Marx, John Stuart Mill, for example) took a variety of approaches that shared a common interest in making comparisons between different ways in which people’s lives may be led, influenced by institutions but also by people’s actual behavior, social interactions and other significant determinants. This book (‘The Idea of Justice’) draws to a great extent on that alternative tradition. The analytical – and rather mathematical – discipline of ‘social choice theory’, which can be traced to the works of Condorcet in the eighteenth century, but which has been developed in the present form by the pioneering contributions of Kenneth Arrow in the mid-twentieth century, belongs to this second line of investigation. That approach, suitably adapted, can make a substantial contribution …. to addressing questions about the enhancement of justice and the removal of injustice in the world.”4 Thus, Sen talking about the dichotomy between ‘transcendental institutionalism’ (or an ‘arrangement-focused view of justice’) and ‘realization-focused comparison’ (or ‘realization-focused understanding of justice’) follows the latter line of reasoning. (However, the way Sen classifies Enlightenment philosophers into two opposing camps seems to be somewhat arbitrary.) Since Piketty mentions Sen only in the passing, I will not expand this discussion on Sen’s methodology further.


Here, it will be sufficient to mention that in the dichotomy between ‘why’ and ‘what’, causality and correlation, analog and algorithm, Piketty chooses the latter, thereby misses the opportunity to pursue the dialectical method in order to grasp why and what, causality and correlation, analog and algorithm in their interconnections, in their motion and constantly changing places, and in their interpenetration. He falls prey to the method that views opposing categories in irreconcilable, absolute terms – why versus what, causality versus correlation, analog versus algorithm (and in case of Sen ‘arrangement-focused view of justice’ versus ‘realization-focused understanding of justice’). He thus departs from the great French tradition that played a vital role in the development of the science of thought. Descartes was himself a ‘brilliant exponent of dialectics’, and Rousseau (‘Discourse on the Origin of Inequality Among Men’) and Diderot (‘Rameau’s Nephew’) produced ‘masterpieces of dialectics’.5

The genealogy of big data methodology can well be traced back to John Locke’s empiricism, and then to Auguste Comte’s positivism, to William James’s pragmatism, and to John Dewey’s instrumentalism (not to mention various shades of twentieth-century positivism). Big data methodology is, in fact, digital-age avatar of above-mentioned philosophical tradition.6

Karl Marx

It seems that ‘his vaccination for life, at the age of eighteen (when the Berlin Wall fell) against the conventional but lazy rhetoric of anti-capitalism’ went much deeper, creating mistrust of theories and hypotheses; and this mistrust and prejudice was further reinforced when, at the age of twenty-two, he ‘experienced the American dream’ at Boston.

To be fair to Piketty, it must be mentioned that the quintessential French intellectual (as distinct from the American) asserts and shines forth occasionally in different chapters of the book, particularly when he passionately deals with the Euro-zone crisis and comes out with a number of propositions and proposals.

The role of data should not be underestimated. Piketty’s study of the ‘World Top Income Database’ (WTID, based on the joint work of some thirty researchers around the world) and his findings which form the main content of the book, are definitely major contributions towards understanding income inequality in our time. However, since capital is a network of social relationships, to explore distributive injustice (why) is as much, and more so, important as the data-based movement of income inequality (what).

To sum up, so far as the methodology of Piketty is concerned, his pious wish to resurrect the spirit of classical political economy on the one hand, and his pragmatic preference for the big data methodology on the other hand, constitute the first major inconsistency of the book.


Before moving ahead, a little more on the question of methodology will not be out of context. Piketty rightly suggests that his book can be read as a history book as well. Here, a brief reference from Michel Foucault seems relevant: “For many years now historians have preferred to turn their attention to long periods, as if, beneath the shifts and changes of political events, they were trying to reveal the stable, almost indestructible system of checks and balances, the irreversible processes, the constant re-adjustments, the underlying tendencies that gather force, and are then suddenly reversed after centuries of continuity, the movements of accumulation and slow saturation, the great silent, motionless bases that traditional history has covered with a thick layer of events. The tools that enable historians to carry out this work of analysis are partly inherited and partly of their own making: models of economic growth, quantitative analysis of market movements, accounts of demographic expansion and contraction, the study of climate and its long-term changes, the fixing of sociological constants, the description of technological adjustments and of their spread and continuity. These tools have enabled workers in the historical field to distinguish various sedimentary strata; linear successions, which for so long had been the object of research, have given way to discoveries in depth. ….

At about the same time, in the disciplines that we call the history of ideas, the history of science, the history of philosophy, the history of thought, and the history of literature (we can ignore their specificity for the moment), in those disciplines which, despite their names, evade very largely the work and methods of the historians, attention has been turned, on the contrary, away from vast unities like ‘periods’ or ‘centuries’ to the phenomenon of rupture, of discontinuity. ….One is now trying to detect the incidence of interruptions. ….They suspend the continuous accumulation of knowledge, interrupt its slow development and force it to enter a new time, cut it off from its empirical origin and its original motivations, cleanse it of its imaginary complicity; they direct historical analysis away from the search for silent beginnings, and the never-ending tracing back to the original precursors, towards the search for a new type of rationality and its various effects. There are ‘displacements’ and ‘transformations’ of concepts; ..they show that the history of a concept is not wholly and entirely that of its progressive refinement, its continuously increasing rationality, its abstract gradient, but that of its various fields of constitution and validity, that of its successive rules of use, that of the many theoretical contexts in which it developed and matured. ..”7

Any study of capital in the twenty-first century required the ‘architectonic unity’ of both the methods described above by Foucault, but Piketty obviously avoids to ‘enter a new time’, to search for a ‘new type of rationality’, and to attempt ‘displacements’ and ‘transformations’ of concepts, thereby creating architectural fault-lines in the book which I will deal with in course of this critique.


  1. Mayer-Schönberger, Viktor, and Cukier, Kenneth; ‘Big data’, John Murray, London, 2013.
  2. Ibid.
  3. Ibid.
  4. Sen, Amartya; ‘The Idea of Justice’, Allen Lane, London. 2009.
  5. Engels, Frederick; ‘Anti-Duhring’, Foreign Languages Press, Peking, 1976.
  6. “In the Preface to Sir Dudley North’s ‘Discourses upon Trade’ (1691) it is stated that Descartes’ method had begun to free Political Economy from the old fables and superstitious notions of gold, trade, &c. On the whole, however, the early English economists sided with Bacon and Hobbes as their philosophers; while at a later period, the philosopher of Political Economy in England, France and Italy was Locke.” Karl Marx, ‘Capital’, Volume I, Part IV (Continued), Chapter XV, Section 2, Second Footnote, p. 368. Progress Publishers, Moscow, 1977. Translated from the third German edition by Samuel Moore and Edward Aveling.
  7. Foucault, Michel; ‘The Archaeology of Knowledge’, Routledge Classics, Oxon, 2006.

[This critique is divided in eight parts, tentatively titled as: i. Apocalypse and Exuberance; ii. Data and Dialectics; iii. Capital Social and Self-Expanding; iv. Wealth Inherited and Created; v. Century Twentieth and Twenty-First; vi. Yes Marx No Marx; vii. London Chicago Paris; and viii. Thank You Mr Piketty.]

July, 2014.



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