The coronavirus is an exogenous shock to the global economy, causing panic in the financial markets, a jobs apocalypse and an unprecedented crisis in health services. At the same time, the necessary safety measures are challenging the very nature of work and human sociality. Social distancing and lockdowns have been implemented around the world and in many countries, enforced by the state with a militaristic strictness. While Boris Johnson waxes Churchillian indulging in his “wartime” fantasy, the UK is facing a social catastrophe that goes beyond the economy. In the short term, there will be serious losses throughout many industries as many of their clients scale down or go bankrupt and we enter a recession. But in the long-term, we will see changes in the nature of work and human sociality that seem closer to the brave new worlds of science fiction than our pre-coronavirus reality. The tech giants are likely celebrating and the key to their success will be our quarantine. A different world will emerge as the economy recovers, a world where technology mediates a far greater proportion of our lives than any Silicon Valley ideologue could have dreamed was possible previously.
The notion of what constitutes intelligence and therefore what constitutes an intelligent machine has been widely debated throughout the history of Western thought. Descartes’ mind-body dualism, Marx’s humanist distinction between the intentionality of an architect versus the functionality of bee, and Allen Newell and Herbert Simon’s ‘Physical Symbol System’ hypothesis, which argued that any representational system “has the necessary and sufficient means for general intelligent action”, are just a few examples. Stories of something approximating an intelligent machine go back to the eighth century BCE in Homer’s Iliad. These self-moving machines or ‘automata’ were made by Hephaestus, the god of smithing, and were servants “made of gold, which seemed like living maidens. In their hearts there is intelligence, and they have voice and vigour”.[i] In De Motu Animalium, Aristotle essentially conceived of planning as information-processing.[ii] In developing ontology and epistemology he also arguably provided the bases of the representation schemes that have long been central to AI.[iii] The first edition of Russell and Norvig’s famous text Artificial Intelligence: A Modern Approach [iv] even shows the notation of Alice in Wonderland author Lewis Carroll[v] on Aristotle’s theory of the syllogism – the basis for logic-based AI – on the cover.
From Descartes to Turing
The idea that we can test machinic intelligence is nearly as old as the concept of intelligent machines. Writing in 1637, Descartes proposed two differences that distinguish human from machine in a way that is much more demanding than the Turing Test (see below):
“If there were machines which bore a resemblance to our body and imitated our actions as far as it was morally possible to do so, we should always have two very certain tests by which to recognise that, for all that, they were not real men”.[vi]
The first test imagines a machine’s “being” established such that it can “utter words, and even emit some responses to action on it of a corporeal kind, which brings about a change in its organs”. However, this machine cannot yet fully produce speech such that it could “reply appropriately to everything that may be said in its presence”. This is essentially the criteria for many contemporary artificial intelligences. The second test concerns situations in which machines can “perform certain things as well as or perhaps better than any of us can do”, yet fall short in others, which means that they did not “act from knowledge”, but rather only from “the disposition of their organs”. An intelligent machine can only pass both of Descartes’ tests if it has a functionality that is beyond a narrowly defined intelligence such that it has the capacity for knowledge. It must understand any given question enough to answer beyond programmed responses. This leads to the conclusion that it is “impossible that there should be sufficient diversity in any machine to allow it to act in all the events of life in the same way as our reason causes us to act”[vii].
Intelligent machines that approximate human understanding have yet to be produced. However, intelligent machines of a narrower type have existed – first virtually, then in reality – since Charles Babbage’s Analytical Engine of 1834. This machine was designed to use punch cards (an early form of computation) and could perform operations based on the mathematization of first-order logic. The Countess of Lovelace Ada Byron King – popularly known as Ada Lovelace – worked with Babbage and prophesised the implications of the algorithms that underpinned it. We can think of algorithms as a type of virtual machine or an “information-processing system that the programmer has in mind when writing a program, and that people have in mind when using it”[viii]. Ada Lovelace theorised virtual machines that formed the foundations of modern computing, including stored programs, feedback loops and bugs among other things. She also recognised the potential generality of such a machine to represent nearly “all subjects in the universe”, predicting that a machine “might compose elaborate and scientific pieces of music of any degree of complexity or extent”, though she could not say how[ix].
Advancements in mathematics and logic allowed for a breakthrough in 1936, when Alan Turing showed that every possible computation can in principle be performed by a mathematical system. This is now called a Universal Turing Machine[x]. Turing spent the next decade codebreaking at Bletchley Park during World War II and thinking about how this virtual machine could be turned into an actual physical machine. He helped design the first modern computer, which was completed in Manchester in 1948. Turing is usually credited with providing the theoretical break that led to modern computation and AI. In an unpublished paper from 1947, Turing discusses “intelligent machines”. A few years later Turing publishes his famous paper in which he asks, “Can a machine think?” and argues that machines are capable of intelligence. To make his case, he first constructs an “imitation game” or what is now known as the “Turing Test”, which continues to influence popular debates about AI[xi]. The test involves three people – a man (A) and a woman (B) who communicate through typescript with an interrogator (C) in a separate room. The interrogator aims to determine which of the other two is the man and which is the woman. Turing argue that the question “What will happen when a machine takes the part of A in this game?” should replace the original question “Can a machine think?”. The failure to distinguish between machine and human indicated the intelligence of the machine. Turing then goes on to consider nine different objections which form the classical criticisms of artificial intelligence. One of the most enduring is ‘Lady Lovelace’s Objection’, in which she argues that computers have “no pretensions to originate anything. It can do whatever we know how to order it to perform”[xii]. However contemporary “expert systems” and “evolutionary” AI have reached conclusions unanticipated by their designers[xiii]. Interestingly, a machine with a set of responses that happen to perfectly fit the questions asked by a human would pass a Turing test, but not pass Descartes’ test.
From Russell to MINDER
Following the innovations of Turing and Lovelace, the advancement of intelligent machines picks up speed from the 1950s into the 1970s in large part to three developments: Turing’s work, Bertrand Russell’s propositional logic and Charles Sherrington’s theory of neural synapses. In a famous paper titled “A Logical Calculus of the Ideas Immanent in Nervous Activity,” the neurologist and psychiatrist Warren McCulloch and the mathematician Walter Pitts combined the binary systems of Turing, Russell and Sherrington by mapping the 0/1 of individual states in Turing machines onto the true/false values of Russell’s logic, onto the on/off activity of Sherrington’s brain cells.[xiv] During this time a number of different proto-intelligent machines were built. For example, a Logic Theory Machine proved eighteen of Russell’s key logical theorems and even improved on one of them. There was also the General Problem Solver (GPS) machines, which could apply a set of computations to any problem that could be represented according to specific categories of goals, sub-goals, actions and operators.[xv] At the time, these intelligent machines relied almost exclusively on formal logic and representation, which dominated the early development of computing. Margaret Boden terms this type of artificial intelligence “Good Old-Fashioned AI” or GOFAI.
The binary systems synthesised by McCulloch and Pitts helped to catalyse the embryonic cybernetics movement, which emerged alongside the symbolic/representational paradigm discussed above. Cybernetics was coined in 1948 by Norbert Wiener, an MIT mathematician and engineer who developed some of the first automatic systems. Wiener defined cybernetics as “the study of control and communication in the animal and the machine.”[xvi] Cyberneticians examined a variety of phenomena related to nature and technology including autonomous thought, biological self-organisation, autopoiesis and human behaviour. The driving idea behind cybernetics was the idea of the feedback loop or “circular causation”, which allows a system to make continual adjustments to itself based on the aim it was programmed to achieve. Such cybernetic insights were later applied to social phenomena by Stafford Beer to model management processes among others. Wiener and Beer’s insights were used in Project Cybersyn – a pathbreaking method of managing and planning the Chilean national economy under the presidency of Salvador Allende from 1971-73.[xvii] However, as AI gained increasing attention from the public and government funding bodies, there began to be a split between two paradigms – the symbolic/representational paradigm which studied mind and the cybernetic/connectionist paradigm which studied life itself. The symbolic/representational paradigm came to dominate the field.
There were numerous theoretical and technological developments from the 1960s through to the present that provided the foundations for the range of intelligent machines that we rely on today. One of the most important was the re-emergence in 1986 of parallel distributed processing, which formed the basis for artificial neural networks, a type of computing that mimics the human mind. Artificial neural networks are comprised of many interconnected units that are each capable of computing one thing; but instead of computing sequential instructions based on top-down instructions given by formal logic, they use a huge number of parallel processes, controlled from the bottom up based on probabilistic inference. They are the basis for what is called “deep learning” today. “Deep learning” uses multi-layer networks and algorithms to systematically map the source of a computation, thus allowing it to adapt and improve itself. Another important development was Rosalind Picard’s ground-breaking work on “affective computing”, which inaugurated the study of human emotion and artificial intelligence in the late 1990s.[xviii] Marvin Minsky also influenced the incorporation of emotion into AI in considering the mind as a whole, inspiring Aaron Sloman’s MINDER program in the late 1990s.[xix] MINDER indicates some ways in which emotions can control behaviour, scheduling competing motives. Their approaches also inspired more recent hybrid models of machine consciousness such as LIDA (Learning Intelligent Distribution Agent), by researchers led by Stan Franklin.[xx]
What puts the ‘intelligence’ in Artificial Intelligence?
Today there are many different kinds of intelligent machines, with many different applications. In 1955, the study of intelligent machines is essentially rebranded as “artificial intelligence” via a conference at Dartmouth College during the summer of 1956.[xxi] In the proposal for the conference, the authors state that “a truly intelligent machine will carry out activities which may best be described as self-improvement”.[xxii] However, a single definition of artificial intelligence is difficult to adhere to, especially in a field rife with debate. For perspective, Legg and Hutter provide over seventy different definitions of the term.[xxiii] It has been variously described as the “art of creating machines that perform functions that require intelligence when performed by people”,[xiv] as well as “the branch of computer science that is concerned with the automation of intelligent behaviour”.[xv] One of the best definitions comes from the highly influential philosopher and computer scientist Margaret Boden: “Artificial intelligence (AI) seeks to make computers do the sorts of things that minds can do”.[xvi] Within this definition, Boden (2016, p. 6) classifies five major types of AI, each with their own variations. The first is classical, or symbolic “Good Old-Fashioned AI” (GOFAI mentioned in a previous post), which can model learning, planning and reasoning based on logic; the second is artificial neural networks or connectionism, which can model aspects of the brain, recognise patterns in data and facilitate “deep learning”; the third type of AI is evolutionary programming, which models biological evolution and brain development; the last two types, cellular automata and dynamical systems, are used to model development in living organisms.
None of these types of AI can currently approximate anything close to human intelligence in terms of general cognitive capacities. A human level of AI is usually referred to as artificial general intelligence or AGI. AGIs should be capable of solving various complex problems in various different domains with the ability of autonomous control with their own thoughts, worries, feelings, strengths, weaknesses and predispositions (Goertzel and Pennachin, 2007). The only AI that exists right now is of a narrower type (often called artificial narrow intelligence or ANI), in that its intelligence is generally limited to the frame in which it is programmed. Some intelligent machines can currently evolve autonomously through deep learning, but these are still a weak form of AI relative to human cognition. In an influential essay from the 1980s, John Searle makes the distinction between “weak” and “strong” AI. This distinction is useful in understanding the current capacities of AI versus AGI. For weak AI, “the principal value of the computer in the study of the mind is that it gives us a very powerful tool”; while for strong AI “the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states”.[xvii] For strong AI, the programs are not merely tools that enable humans to develop explanations of cognition, the programs themselves are essentially the same as human cognition.
The Prospect of General Intelligence
While we currently do not have AGI, investment in ANI is only increasing and will have a significant impact on scientific and commercial development. These narrow intelligences are very powerful, able to perform a huge number of computations that would in some cases take humans multiple lifetimes. For example, some computers can beat world-champions in popular games of creative reasoning such as chess (IBM’s Deep Blue in 1997), Jeopardy (IBM’s Watson in 2011), and Go (Google’s AlphaGo in 2016). The Organisation for Economic Co-operation and Development [OECD], found that private equity investments in AI start-ups have increased from just 3% in 2011 to roughly 12% worldwide in 2018.[xviii] Germany is planning to invest €3 billion in AI research between now and 2025 to help implement its national AI strategy (“AI Made in Germany”), while the UK has a thriving AI startup scene and £1 billion of government support.[xxix] The USA had US$5 billion of AI investments by VCs in 2017 and US$8 billion in 2018.[xxx] The heavy investment in ANI start-ups and the extremely high valuations of some of the leading tech companies funding AGI research might lead to an artificial general intelligence in the coming years.
Achieving an artificial general intelligence could be a watershed moment for humanity and allow for complex problems to be solved at a scale once unimaginable. However, the rise of AGI comes with significant ethical issues and there is a debate as to whether AGI would be a benevolent or malevolent force in relation to humanity. There are also people who fear such developments could lead to an artificial super intelligence (ASI), which would be “much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills”. [xxxi] With an increasingly connected world (referred to as the internet of things) artificial super intelligences could potentially “cause human extinction in the course of optimizing the Earth for their goals”.[xxxii] It is important, therefore, that humans remain in control of our technologies to use them for social good. As Stephen Hawking noted in 2016, “The rise of powerful AI will be either the best or the worst thing ever to happen to humanity. We do not yet know which”.
[i] Homer, 1924. The Iliad. William Heinemann, London. pp. 417–421
[ii] Aristotle, 1978. Aristotle’s De motu animalium. Princeton University Press, Princeton.
[iii] Glymour, G., 1992. Thinking Things Through. MIT Press, Cambridge, Mass.
[iv] Russell, S.J. and Norvig, P., 2010. Artificial intelligence: a modern approach, 3rd ed. Pearson Education, Upper Saddle River, N.J;Harlow;
[v] Carroll, L., 1958. Symbolic logic, and, The game of logic : (both books bound as one), Mathematical recreations of Lewis Carroll. Dover, New York.
[vi] Descartes, R., 1637, 1931. The philosophical works of Descartes. Cambridge University Press, Cambridge.
[vii] Ibid., p. 116
[viii] Boden, M.A., 2016. AI : Its Nature and Future. OUP, Oxford. p. 4
[ix] Lovelace, A.A., 1989. Notes by the Translator (1843), in: Hyman, R.A. (Ed.), Science and Reform: Selected Works of Charles Babbage. Cambridge University Press, Cambridge, pp. 267–311.
[x] Turing, A.M., 1936. “On Computable Numbers with an Application to the Entscheidungsproblem,” Proceedings of the London Mathematical Society, Series 2, 42/3 and 42/4., in: Davis, M. (Ed.), The Undecidable: Basic Papers on Undecidable Propositions, Unsolvable Problems, and Computable Functions. Raven Press, Hewlett, NY, pp. 116–53.
[xi] Nisson, N., 1998. Artificial Intelligence: A New Synthesis. Morgan Kaufmann, San Francisco.
[xii] Lovelace, A.A., 1989. Notes by the Translator (1843), in: Hyman, R.A. (Ed.), Science and Reform: Selected Works of Charles Babbage. Cambridge University Press, Cambridge, pp. 303.
[xiii] See Boden, M.A., 2016. AI : Its Nature and Future. OUP, Oxford. See also Luger, G.F., 1998. Artificial intelligence : structures and strategies for complex problem solving. England, United Kingdom.
[xv] See Newell, A., Simon, H., 1956. The logic theory machine–A complex information processing system. IRE Transactions on Information Theory 2, 61–79. https://doi.org/10.1109/TIT.1956.1056797. See also Simon, H.A., Newell, A., 1972. Human problem solving / Allen Newell, Herbert A. Simon, Human problem solving / Allen Newell, Herbert A. Simon. Prentice-Hall, Englewood Cliffs, N.J.
[xvi] Wiener, N., 1961. Cybernetics : or, Control and communication in the animal and the machine, Second edition. ed. M.I.T. Press, New York.
[xvii] Medina, E., 2014. Cybernetic revolutionaries : technology and politics in Allende’s Chile. The MIT Press, Cambridge.
[xviii] Picard, R.W., 1997. Affective computing. MIT Press, Cambridge, Mass.
[xix] Minsky, M., 2006. The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind. Simon & Schuster, Riverside.
[xx] Baars, B.J., Franklin, S., 2009. CONSCIOUSNESS IS COMPUTATIONAL: THE LIDA MODEL OF GLOBAL WORKSPACE THEORY. International Journal of Machine Consciousness 1, 23–32. https://doi.org/10.1142/S1793843009000050
[xxi] McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E., 2006. A proposal for the Dartmouth summer research project on artificial intelligence: August 31, 1955. AI Magazine 27, 12.
[xxii] Ibid., p 14
[xxiii] Legg, S., Hutter, M., 2007. Universal Intelligence: A Definition of Machine Intelligence.(Author abstract)(Report). Minds and Machines: Journal for Artificial Intelligence, Philosophy and Cognitive Science 17, 391. https://doi.org/10.1007/s11023-007-9079-x
[xxiv] Kurzweil, R., 1990. The age of intelligent machines. MIT Press, London;Cambridge, Mass
[xxv] Luger, G.F., 1998. Artificial intelligence: structures and strategies for complex problem solving. England; p. 1.
[xxvi] Boden, M.A., 2016. AI : Its Nature and Future. OUP, Oxford. p.1.
[xxviii] OECD, 2018. Private Equity Investment in Artificial Intelligence (OECD Going Digital Policy Note). Paris.
[xxix] Deloitte, 2019. Future in the balance? How countries are pursuing an AI advantage (Insights from Deloitte’s State of AI in the Enterprise, No. 2nd Edition survey). Deloitte, London.
[xi] Bostrom, N., 2006. How Long Before Superintelligence? Linguistic and Philosophical Investigations 5, p.11.
[xii] Yudkowsky, E., Salamon, A., Shulman, C., Nelson, R., Kaas, S., Rayhawk, S., McCabe, T., 2010. Reducing Long-Term Catastrophic Risks from Artificial Intelligence. Machine Intelligence Research Institute. p. 1
Last year I was contacted by Kim Walker at Zed books to put together a book series in collaboration with Autonomy. I’m pleased to say that our first book by Mark Bergfeld is nearing completion now and we have 4 more on the way. We hope to build this momentum throughout 2020. With that in mind, the open call for proposals is below:
The labour market has been hollowed out and the future of work lies in the shadow of political crises. Many have argued that this growing social polarisation is driven by technological change. However, research has not kept up with the speed at which these changes are occurring. Social protections for workers are being eroded across the globe and technology is arguably catalysing this trend. Historically, the loss of employment in one industry has been more than offset by the expansion of employment in other industries. Yet, this employment tends to emerge under different social conditions. Research has often neglected how new technologies have catalysed exploitation, rather than helped workers overcome it.
This new series in collaboration with Zed aims to explore the rapidly changing nature of existing jobs as well as the variety of emergent occupations in new sectors. It takes technological change neither as an inherently liberatory force nor as an inherently constraining force, but rather as a function of social relations. Topics could include anything from sociological analysis of particular technical changes in industry such as the introduction of platforms and AI, to detailed ethnographies of particular experiences of workers themselves such as those of migrant carers, delivery drivers or freelance coders.
Proposals: We solicit academics and non-academics to write punchy, trade-oriented, 30-40,000 word books on the above themes. Proposals should have the weight and rigour of academic thought, yet be accessible to a general audience.
If you are interested in submitting a proposal for the series, please contact M.Cole@leeds.ac.uk for further information.
Matt Cole – Post-Doctoral Fellow in Work and Employment, University of Leeds
Kendra Briken – Chancellor’s Fellow in Work and Employment, Strathclyde University
Will Stronge – Co-director of Autonomy
I thought I should update the internet on my work.
I’m currently working on two journal articles – one related to labour process theory and another related to wage theft in the hospitality industry.
I’m also working on some blogs and research on AI for Autonomy (a think tank on work and its futures).
My current research is looks at the tensions between human and machine intelligence in interactive service work, focusing on platforms specifically.
There is also a book series in the works, which has not been announced yet.
Conference Season is approaching, which means I’ll be presenting at SASE in New York, BUIRA in Newcastle, and IIPPE in Lille.
I’m very happy to have my first book contribution published in the Bloomsbury Companion to Marx.
The entry introduces the Marxist conception of exploitation and summarises some key debates over the last century. I highly recommend ordering a copy for your university library or for personal reference. The text is below.
The concept of exploitation has a rich history in Marxist as well as non-Marxist political, economic and social theory. These multiple, and sometimes conflicting definitions, often rely on different assumptions concerning power, labor and economics generally. Etymologically, the modern term for exploitation1 emerged in the early-nineteenth century and referred to the ‘productive working’ of something. Generally, the word had a positive connotation among those who first used it; however, it later developed negative connotations during the 1830s to 1850s due to the influence of French socialists like Saint Simon and Charles Fourier. Marx was likely influenced by this negative conception of exploitation when he began his study of classical political economy (Adam Smith, David Ricardo, James Mill, etc.) while he lived in Paris from 1843 to 1845. Like Marx, I will focus primarily on the economic dimensions of exploitation because these form what he understood as the material foundation for social relations. The following will explain Marx’s conception of exploitation; contextualize its development within both historical debates and the development of Capital itself; and conclude with the political implications of the concept. The final point is the most important; as without a proper understanding of exploitation, there is no possibility of truly overcoming it.
To understand Marx’s concept of exploitation, it is first necessary to understand his conception of the development of the capitalist mode of production. A mode a production is made up of forces and relations of production, which codetermine one another. Forces of production are the range of possible means, determined by knowledge, science and technology. Relations of production are determined by the prevailing patterns of property or class relations. The classical Marxian periodization of modes of production and exploitation of labor follows the pattern: slave, feudal, and then capitalist (see Banaji 2010). The slave mode of production relies on private property in people and non-labor means of production; the feudal mode of production relies on private property in land and non-labor means of production; and the capitalist mode of production relies on private property in non-labor means of production and land. In pre-capitalist modes of production, exploitation was directly mediated through the appropriation of the immediate surplus product, and labor was formally coerced. In the capitalist mode of production, by contrast, exploitation is abstracted through economic relations and labor is, formally, free, which is to say that workers can sell their labor as they see fit.
Over the course of the three volumes of Capital, Marx develops two aspects of exploitation: ‘primary exploitation’, which takes place in the production process itself and ‘secondary exploitation’, which takes places outside of the production process and requires the capitalist’s mastery and advantage, based on property ownership. The former can be productive of surplus value, which is translated into profits through the market and competition. The latter is essentially an antediluvian form of accumulation and operates through appropriation of the former’s surplus or ‘profit upon alienation’. Understanding the relation between these two types of exploitation is essential in order to grasp Marx’s critique of political economy.
Primary exploitation is the human and social process of ‘exploitation of the workman’ by the capitalist, which relies on a classed monopoly of power over the means of industrial production. It relies on the extraction of surplus value. Value is the representation of abstract homogenized labor, which emerges in the process of exchange and is measured by money. The rate of surplus value extracted in the labor process is ‘an exact expression for the degree of exploitation of labor-power by capital, or of the worker by the capitalist’ (Marx 1990: 326). However, this does not mean that rate of surplus value is an expression for ‘absolute magnitude’ of exploitation, because not all exploited labor produces surplus value.
For Marx, some labor is productive of value, while some is non-productive. In most Marxian economics, the distinction between productive and non-productive labor is central (see Foley 1986; Shaikh and Tonak 1994; Mohun 1996). Activities such as trade, financial services and advertising are not socially productive of value, yet firms who carry out these activities nonetheless exploit workers. The rate of primary exploitation for both productive and nonproductive workers is the ratio of necessary labor time (the average annual consumption per worker in the sector) to surplus labor time (the excess of working time over necessary labor time). It important to note that, for Marx, capitalists cannot be exploited. The work of the capitalist appears as a labor process in its own right, however it is the labor of exploitation rather than exploited labor. The wages of managers, just as the incomes of capitalists are, as Marx notes in Capital Vol. 3, ‘precisely the quantity of others’ labor that is appropriated, and depends directly upon the rate of exploitation of this labor’ (Marx 1992: 511).
At the most abstract level, aggregate profit is essentially the monetary expression of aggregate surplus value; however, companies can also generate profit through purely redistributive techniques, taking advantage of the dynamics of circulation between social spheres. These profits come from what Marx terms secondary exploitation, or profit upon alienation. Secondary exploitation is mediated through financial and property relations that ensure the collection of interest payments, rents or profits through unequal exchange (merchant’s capital). This aspect of exploitation extracts and redistributes a portion of the total surplus value of society. The existence of secondary exploitation allows for two things: first, it explains how capitalism can profit from non-capitalist spheres without the creation of new value; and, second, it allows Marxian economics to account for the difference between the sum of profits and the sum of surplus values that emerges as values are transformed into prices (see Shaikh and Tonak 1994).
Marx defines secondary exploitation in volume three of Capital as an essentially archaic form of accumulation. This dynamic persists in those branches of industry that have not transitioned to the modern mode of production. In this mode of exploitation, money and means of production, such as tools, software, appliances, machinery, cars and business premises, are loaned in kind. These represent a specific sum of money and the borrower must not only pay interest, but also the price for wear and tear which arises from the use-value of the items. Usury, trade and finance, exploit a given mode of production without reproducing it and thus relate to the mode of production from the outside. Usurer’s capital, for example, ‘has capital’s mode of exploitation without its mode of production’ (Marx 1992: 732). The primary distinction that should be made in terms of the form of accumulation is whether these means of production are loaned to immediate producers, which presupposes a non-capitalist mode of production, or whether they are loaned to industrial capitalists, which presupposes a capitalist mode of production. Both are forms of secondary exploitation.
Defining the precise role of exploitation in production and capitalism has been the source of considerable debate in the history of economics and political economy. From the late-ninetieth to late-twentieth century, the debates were largely between two distinct paradigms: the Marxist and the neo-classicalist (influenced by the Austrian and Lausanne Schools). Marxist thinkers asserted the centrality of value and exploitation in capitalism as a mode of production. They viewed the labor processes of capitalism, from the satanic mills to the penthouses of haute finance, as a totalizing system. Neo-classicalist thinkers, by contrast, typically denied the existence of exploitation, largely through omission of the labor process as a social phenomenon. They tended to flatten social phenomena to fit mathematical models and relied on the anomalous assumptions of Walrasian marginal equilibrium conditions, such that all market exchanges are perfectly competitive, yet reciprocal and voluntary. In sum, Marxists denied the possibility of capitalism persisting without exploitation, while neo-classicalists deny the possibility of a persistently exploitative system
During the early1980s the stark divisions between Marxist and Neoclassicalist approaches to economics and exploitation began to soften as Marxists were influenced by neo-Ricardian and Sraffian economics. Two overlapping tendencies of Marx-inspired thought emerged, which were called the neo-Ricardian Marxists and the analytical Marxists, respectively. Both tendencies shared a rejection of Marx’s labor theory of value as a foundation for the Marxian theory of exploitation. Neo-Ricardian Marxists were theoretically indebted to Cambridge economists Maurice Dobb, Piero Sraffa, and Joan Robinson, among others. Sraffa shared Ricardo’s so-called ‘corn theory of value’ or the idea that one can measure the rate of profit as a share of any particular commodity. Ian Steedman used the Sraffian approach to argue that a neo-Ricardian framework is a superior system and method compared to Marx’s when analyzing a range of issues involving prices and production under capitalism. Steedman and other neo-Ricardians claimed that, since magnitudes in terms of values tend to differ from those in terms of price, Marx’s labor theory of value must be abandoned (Steedman 1977: 205–07). This position influenced other analytical Marxists (see Roemer 1982), but also elicited strong criticisms from those who retained value-informed approach (see Himmelweit and Mohun 1981; Shaikh 1981). The latter’s main criticisms were that they conceptually flattened all labor process relations into money relations. The ideological roots of the series of concepts that neo-Ricardians relied on – equilibrium, profit as cost, and perfect competition – limited their analytical capacity to understand exploitation. Marxists claimed that Steedman and the neo-Ricardians could not accommodate social dimensions of the labor process or the relative autonomy of value and prices relations.
The analytical Marxists (or ‘rational choice’ Marxists), included scholars such as John Roemer, John Elster and G.A. Cohen. Roemer in particular argued that Marxian economics, particularly the notion of exploitation, should be able to be derived from Walrasian axioms of market equilibrium, perfect competition, full employment, etc., and should use neoclassical methodological assumptions such as the rational individual and normative preferences. This was intended to make Marx more palpable to the mainstream. This ‘simpler Marxian Argument’ claimed that, because labor is the singular human element in production that generates the commodity, and because people who own means of production and do not labor in production control some of the revenues from the sale of the commodity, people who labor are exploited by those who do not (Cohen 1979). This led them to conclude ‘the relationship between the labor theory of value and the concept of exploitation is one of mutual irrelevance’ (Cohen 1979: 338; see also Steedman 1981). Marxian political economists responded with wide-ranging criticisms of the analytical approach. For example, they argued that Roemer’s approach fails as a result of ignoring the distinction between labor and labor power (Lebowitz, 1988); that the logic of a non-dialectical approach necessarily fails to grasp Marx’s theory of exploitation (Smith 1989); that Roemer’s analysis must be rejected because it cannot account for the emergence of class consciousness (Anderson and Thompson 1988); and that it’s reliance on Walrasian foundations is idealistic and ahistorical (Dymski and Elliot 1989).
The main criticisms of Marx by neoclassical economists were primarily influenced by Böhm-Bawerk’s Karl Marx and the Close of His System (1896). Böhm-Bawerk claims Marx’s fundamental error is that the labor theory of value set out in Capital Vol. I contradicts the theory of the rate of profit and prices of production set out in volume three. Most subsequent critiques of Marx have made similar arguments. For example, Joan Robinson in An Essay on Marxian Economics, argued that there was a contradiction between Marx’s assumptions in volume one, namely that a rising labor productivity leads to a rising rate of exploitation, and those assumptions in volume three, i.e. if the rate of exploitation remains stable, rising labor productivity could lead to a rising rate of real wages and a declining rate of profit. However, a careful analysis shows that these critiques stem from the failure to recognize the fact that Capital, volumes one and volume three, are at different levels of abstraction, make different assumptions and address different questions (see Hilferding 1949; Kay 1979; Mandel 1990).
Marx does not begin Capital volume one with a ‘labor theory of value’ prior to market relations, but, rather, with an analysis of the commodity. Marx suspends all other differences in terms of production conditions, competition, interest, prices etc. in order to examine concrete heterogeneous labor in the production of commodified ‘useful’ things. He does this to make the commodification of labor power (the capacity to labor) explicit. In volume one, only the ‘law of value’ matters. Marx restricts his analysis based on the assumption that the total profit available for capitalists is purely limited to the amount of surplus value appropriated from workers, and that the average rate of profit for the entire economy is simply the ratio of total surplus value to total value. This serves to make exploitation in the labor process transparent, and designate it as the specifically capitalist type of exploitation. Unlike exploitation under feudalism, where exploitation is transparent, personal and direct, specifically capitalist (primary) exploitation is indirect and socially mediated through commodity relations in the market.
Whether an individual exploits or is exploited depends on the nature and price of the commodified object and the actual activity performed by that person. In volume one, capitalists are deemed to exploit workers collectively through the impersonal domination of the market, yet Marx’s analysis is limited to the fact that capitalists are only able to accumulate as much surplus as they are individually able to extract from their workers. Throughout volumes two and three, Marx progressively removes the assumptions of the first volume, so that industrial capitalists no longer must trade and distribute on their own behalf, rely on their own financial means, or use their own land. Trading can be undertaken by commercial capitalists and banking by money or finance capitalists, allowing a variety of types of assets to be incorporated into commodity relations. Capitalists’ capacity to accumulate is no longer restrained by their assets. This effectively transforms the means of production into the property of the capitalist class as a whole. Property-based class relations are thusly generalized to the entire social system. Marx also introduces additional variables such as cost price, fixed capital and circulating capital that effect the rate of surplus value and the rate of profit. As a consequence of Marx’s increasingly complex analysis, the dynamics of price and profit end up obscuring the primary exploitation of surplus value. However, these different levels of abstraction are necessary because, as Marx notes, if he simply started from the calculation of the rate of profit, he would have never been able to ‘establish any specific relationship between the excess and the part of capital laid out on wages’ (1992: 138).
The political implications of using Marx’s concept of exploitation cannot be understated. Exploitation is the basis for the production of surplus value, which forms a link between labor process relations in production and money relations in the market. Labor process relations, which correspond to concrete labor and the organization of production, manifest themselves in the struggle over intensity, time and interpersonal dynamics. The politics of the labor process are what Elson calls a ‘politics of production’, which concentrates on ‘trying to improve conditions of production; shorten the working day, organize worker resistance on the shop-floor; build up workers’ co-operatives, produce an alternative plan …’ such as co-operatives and socialist organization (1979, p. 172). Money relations, which can be defined as those relations directly mediated by the universal equivalent (money), correspond to abstract labor and become manifest in the struggle over the payment or non-payment of wages. The politics of money relations are what Elson calls a ‘politics of circulation’, which concentrate on changing distribution in a way that is advantageous to workers. For example, raising money wages, controlling money prices, regulating the financial system, establishing a welfare state and so on. Marx’s theory of exploitation offers a framework that unifies labor process and money relations and, in doing so, contains within it a politics that aims to move beyond capitalism. As Ernest Mandel pointed out: ‘The growth of the proletariat, of its exploitation and of organized revolt against that exploitation, are the main levers for the overthrow of capitalism’ (1990: 83).
1 The root word ‘exploit’ comes from the late-fourteenth century French espleiten or esploiten, ‘to accomplish, achieve, fulfill’, from Old French esploitier, espleiter, ‘to carry out, perform, accomplish’ (Harper 2017).
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IIPPE 9th Annual Conference in Political Economy
The Political Economy of Work and Social Reproduction Working Groups invite you to submit proposals for individual papers, themed panels or streams of panels related to our lines of inquiry. These may include theoretical and empirical contributions that focus primarily on the relationship between work and social reproduction. Previous IIPPE conferences have highlighted the clear overlaps and synergies in many contributions on the Political Economy of Work and on Social Reproduction. Our aim at the Pula conference is therefore to deepen and strengthen such synergies. In this spirit, we welcome contributions on the following themes:
- The relationship between the productive and reproductive sphere
- Feminist political economy of work
- Gender, labour movements and capitalism
- Conceptualising and measuring value in productive and reproductive work
- Domestic labour, migration and global capitalism
- The care crisis under capitalism
- The political economy of time and time-use in relation to work and social reproduction
- Empirically grounded discussions of concrete, abstract, private, social and caring labour
- Emotional labour, value, and the political economy of production and social reproduction
- Gender and inequality in the workplace: the gender pay gap, occupational segregation and other dimensions of gender and inequality in work
- Debating the feminization of labour
We encourage the submission of panel proposals (consisting of up to four presentations) as an opportunity to showcase the work of study groups in greater depth than is possible in single presentations.
Papers and panel proposals can be submitted on iippe.org by 15 March 2018, ticking the Social Reproduction and/or Political Economy of Work Working Groups as part of your submission.
My research addresses the experiences of workers in the hospitality industry. It takes a political economic approach to studying the labour process, which entails an analysis grounded in the unity of production and valorisation. Ethnographies of work such as Diamond’s (1992) study of the industrial production of care and Sherman’s (2007) study of the industrial production of luxury attempt to incorporate a theory of service production into labour process analysis; however, they lack any conception of the capitalist labour process as one that relies on the production of surplus value. The absence of a social conception of the commodity fundamentally hinders the capacity to analyse work as the unification of money and labour relations in the process of exploitation. Without a theory grounded in a Marxist conception of value, we cannot understand the relations between the structural imperatives of accumulation and the immediate process of production. This distinctly social relation oversdetermines workers’ experiences of work. Understanding the production of experience as a commodity links the concrete labour of its production with the abstract labour that produces value in the capitalist mode of production. The research provides an empirical and theoretical approach to understanding the politics of hospitality work as specifically related to the nature of the service commodity and the tensions that arise within the valorisation process.
Economic contribution and sector composition
What is hospitality? The BHA defines it as, “the provision of accommodation, meals and drinks in venues outside of the home” to both UK residents and overseas visitors”. In the UK, the hospitality industry is the fourth largest industry by employment and has been the largest growth industry over the past decade. It employs around 3 million people in the UK (over a quarter million more than manufacturing). Since 2011, it has grown by 13%, more than double the employment growth of the economy overall. The hospitality industry also makes a significant economic contribution to the UK. The industry added an estimated £57 billion to the economy in 2014, roughly 4% of GDP. Yet in the context of this dramatic growth, working conditions remain poor. Average gross earnings for full-time workers in the hotel industry are the lowest in the UK and the industry has the highest incidence of low-paid workers at 59 per cent. Added to this is its dubious status as one of the lowest rates of unionisation, standing at 3.5 per cent today. These elements make the London hospitality industry a particularly pertinent case study of the contemporary experiences of workers in the UK. Hotels are a subsector of the hospitality industry, but they are uniquely representative of the labour processes involved in hospitality work generally.
I collected data through ethnographic participant observation over three months as an agency worker in London hotels. I conducted 35 semi-structured interviews with workers, supervisors and managers, which I have transcribed and coded. These interviews were spread across 25 different companies including 5 agencies and 20 hotels, 3 of which also used the same outsourced hotel management firm.
In Capital vol. 1, Marx argues that surplus value is produced through the capacity of the capitalist to extract more labour-time and hence value than is required to purchase labour power from workers. This labour-time is not that of private individuals, but rather socially necessary labour-time, which refers to the “labour-time required to produce any use-value under the conditions of production normal for a given society and with the average degree of skill and intensity of labour prevalent in that society” (Marx 1976, p. 129). In a given labour process, the difference between socially necessary labour time and the concrete labour time of the working day is surplus labour time. The average ratio of socially necessary labour time to surplus labour time is what determines the rate of surplus value. Marx (1976, p. 326) defines the rate of surplus value as the “exact expression for the degree of exploitation of labour-power by capital, or of the worker by the capitalist”.
The commodity is a social use value represented by the materialisation of labour in the form of its exchange value i.e. money. As Marx first argued, it is an imaginary and “purely social mode of existence”, which has “nothing to do with its corporal reality” (Marx 1969 p. 171). Commodities thus have no necessary physicality. The concrete labour that produces the commodity “leaves no trace in it”. It is thus conceived as simply a “definite quantity of social labour or of money” (ibid). Marx’s analysis may appear to focus on tangible objects, but the theoretical framework clearly does not put physical limitations on the definition of a commodity. Marxist economists such as Fiona Tregenna have also argued that the physical properties of something neither qualify it as a commodity nor exclude it from the realm of commodities (Tregenna 2011: p. 287). It is the form of the organisation of the labour process that is decisive, not it’s content. Relations in the exchange of labour and capital alone determine the form. Capital’s indifference to the physicality of the product means that commodities are therefore essentially ‘amaterial’ along with the value contained within them. In other words, just as ‘production’ is not limited to the production of tangible objects, commodities are not limited to physical goods. The amateriality of the commodity-form thus allows both goods and services to be considered commodities.
The Service Commodity
The primary criteria that defines a service-commodity, as distinguished from physical commodities, is the relative simultaneity of production and consumption, independent of the material form or product of the labour. This means that for service commodities, the labour represented in the value of a service commodity remains living labour, while for the manufacturing of physical commodities, it is dead labour that can be re-circulated on secondary markets. Concrete labour may not be observable in same way for services commodities as for physical manufactured commodities. For a service commodity, the individual use-value might vanish with the cessation of the labour-power itself. The product of the labour may be an immaterial transformation, in the case of knowledge transfer, customer interaction or the production of affect. Production may have an aspect of perceptible material transformation (clean rooms) or it may have an immaterial transformation (knowledge, emotion).
The Hospitality Experience
The focus on ‘experience’ is derived directly from company literature and workers’ responses themselves. A repeated idiom, articulated over and over again by workers and managers alike was that “it’s all about the experience” (Danilo, hospitality assistant, Hilltop). Workers saw themselves as responsible for providing a “certain standard of contemporary life and service (Ammon, Operations manager, Amnesty Hotel). They viewed customers as not only paying for a place to stay, but also satisfying interactions and spaces. I take this prosaic idea and develop it in more depth, drawing directly from the experiences of workers through their own voices, as well as Hochschilds’ (1983, p. 6) insight that, “In processing people, the product is a state of mind”. However, her Weberian approach focuses on the “immediacy of the individualised commodification process”, which fails to locate her analysis in the wider context of social relations under capitalism. Emotional labour is not a “means of production” but rather a particular feature of concrete labour. Emotional labour is only labour insofar as it assumes a social form, mediated by exchange. An approach with a more rigorous engagement with Marxist theories of labour and value would make this more readily apparent and use it to present a more complete theory of the service labour process.
The Experiential Commodity
The experiential commodity is a dynamic and flexible product assembled through the reproduction of hospitable environments, the cultivation of affects, and the maintenance of supplementary services. The primary component is the provision of a room and associated services delivered with the affect of care. It is primary because it requires the largest investment of fixed and variable capital and is the main source of profit for hotel companies as room revenues generally contribute between 60 and 80 per cent of Total Revenues (Kinnard et al. 2001). Research has found that the “service encounter” between guests and workers is crucial for guest satisfaction and the profit chain (Urry, 1990; Schneider and Bowen, 1999). Accommodation is the tangible aspect of the primary component of the experiential commodity. Housekeepers and room attendants had essential roles in the production of the hospitality experience. Guests expected clean rooms, fresh bedding, unworn furniture and working facilities. The intangible aspects of the primary component of the experiential commodity are the reception services, which include catering to guests’ tastes, offering advice on the local, and generally providing attention on demand.
The secondary component includes the provision of food, beverages, and supplementary services (the quantity increases with the number of stars), which contribute 10 to 20 per cent of Total Revenues (ibid) Hotel kitchens produced the tangible aspects of this secondary component. The organisation of the kitchens and the production of food and beverage corresponded to both the size and star-rating of the hotel. Waiters, servers, and hospitality assistants (an official title for certain lower-level positions) in food and beverage-related departments produce the intangible elements of the secondary component of the guest experience. They take orders and deliver the consumable objects prepared in kitchens; however their primary role is the production of positive guest interactions, which guests expect due to the hotel’s commodification of affect.
|PRIMARY COMPONENT||SECONDARY COMPONENT|
Service Assembly Lines
There is a progressive temporal order to the assembly of these multiple elements that corresponds to specific labour processes and departments. This temporal order or ‘service assembly line’ operates on a circuit that begins with a guest’s request, received by a member of staff in the ‘front-of-house’ [FOH] who relays this request to the ‘back-of-house’ [BOH] where the tangible and material aspects such as food ingredients or bedding are transformed as components of the commodity. Once this labour is performed, the BOH relays this information to the FOH who are expected to deliver this product to the guest with their own contribution of positive interaction in order to produce satisfaction. The FOH staff take orders and deliver the experience, while the BOH staff produce or reproduce the tangible consumables. Front and back of house thus have a symbiotic relationship mediated by both the customer and management.
The hotel’s service assembly line can be illustrated by following the path of its guests. As they enter the hotel, the doorman would greet them and the concierge would open their profile in the hotel registration system. Hotels typically keep detailed records of a customer’s purchase history and preferences. Based on this data, the receptionists would have already directed the food and beverage department to send the guests’ favourite bottle of wine up to their room. The luggage porter would bring their bags to their room in anticipation of a tip. Once settled, the guests might call reception to book them at table at the restaurant. Meanwhile, beyond the public spaces of the hotel, housekeepers, room attendants, maintenance, and porters would work to reproduce the physical spaces and articles of guests’ consumption. The laundry services would reproduce clean linen and employee uniforms while the porters cleaned the public spaces. Room attendants would scrub toilets, top up room amenities, and replace bedding. There were daily changes to room allocation and the order of cleaning demonstrating how different concrete labours must work together in relation to customer demand.
In the hotel restaurant, guests would be greeted and seated by the host. They would then place an order with their waiter who, using their capacity for emotional labour, would transform the atmosphere to appeal to the customer’s tastes in anticipation of a tip. The waiter would relay their order and special requests to the chefs who had spent most of the day preparing food for the dinner service. After the kitchen finished preparing the food and the bartender finished making their drinks, the server would deliver them to the table with a smile. Respondents’ experiences explained the difficulty of balancing the emotional labour of providing seemingly authentic positive customer interactions with the managerial imperative to turn tables and increase profits. The assembly of secondary components was in constant flux relative to the inputs of the kitchen (in terms of both ingredients and labour), the servers (in terms of capacity to manage tables and orders) and customer demand (in terms of attention).
Braverman (1998: p. 361) was the first to note that the reproduction of clean rooms in hotels was “an assembly operation which is not different from many factory assembly operations”. However, in hotels the assembly is not linear like manufacturing, but rather a circuit in which customer feedback continually drives production as long as the service is offered. The relative simultaneity of production and consumption of services means that the customer adds a secondary element of variability to the variable capital of the labour process.
The concept of the service assembly line is important in the analysis of hotel work because it allows us to understand the production of experience as a service commodity. Approaches to service work have largely failed to recognise the production of services in terms of commodification and the progressive assembly of seemingly independent labour processes (Braverman 1998; Taylor and Bain, 2005; Korczynski, 2005; Sherman, 2011). Belanger and Edwards (2013) defined front line service as work in which the “contribution of the front-line employee to the labour process and the creation of use value appear at the same time” (p. 441). This conceptualisation is accurate in certain cases, such as those situations when the commodity produced is solely reliant on the activity of the front-line worker. However, as the case of hotels demonstrates, customers do not pay for a bed to be made separately from the service they receive by the concierge or the luggage porter. These seemingly independent elements are part of the same production process. The service assembly line is thus a dynamic circuit that operates according to a structured temporal sequence yet the specific results of that sequence can be continually altered or revised according to the customer feedback. Without descriptions of the detailed division of labour and the concrete processes at work, abstracting from those processes to examine the broader social relations of production remains ungrounded.
 The necessity of capital’s expanded reproduction drives capital to produce new commodities, the value of which can only be realised through their consumption. Capital thus continually transforms humanity’s relation to nature and need, which is socially mediated; “Production not only supplies a material for the need, but it also supplies a need for the material” (Marx 1993  p. 92). The production of a new social use-value also produces the manner of social consumption. For example, a factory produces trains for railway companies who then use them to sell transport services to other firms and individual consumers who need to travel. A hotel produces rooms and positive affects, which people need when they travel. Production thus creates both the commodity as object and the consumer as subject. The produced object becomes integrated into normal use, earlier commodities become technologically obsolete along with the knowledge of their use. Production therefore produces “the object of consumption, the manner of consumption and the motive of consumption” (1993  p. 92). If capitalist production not only produces the object of consumption, but also the manner and motive of consumption, then hotels do not simply satisfy the expectations of customers, they produce their very needs and desires. The rating system of a hotel stratified allowed companies to differentiate between the object, manner, and motive of consumption by stratifying the market according to spending capacities and tastes. The hotels’ process of commodification and production of experience also produces the manner of its consumption.