Digital capitalism or digital socialism?

Mayer-Schönberger and Ramge argue that the price system was always limited, reducing multidimensional preferences into a single measure. It facilitates manipulations, frustrates nuance and loses context. They argue that it is now possible to move from price to data in the coordination of market activities. This will facilitate match-making with a degree of granularity which the price system cannot hope to meet, reducing inefficiencies at every level of capitalism. The problem is that we currently have monopoly ownership over the feedback systems through which this data is generated from commercial transactions, leaving data with value to many actors in the hands of the few largest digital corporations. They argue a New Deal on Data is necessary in order to force these firms to share the data with other actors for whom it might have value and interest. However as Morozov observes, there is “scant sense in this analysis of capitalism as a system, with a history, a present and a perceptible logic – of competition – that imposes significant constraints on its future paths” (39).

In this sense, it is quite a dangerous vision which advocates profound reform alongside little engagement of the politics preceding it or accompanying it. He draws a parallel to Zuboff’s recent book and suggests these texts postulate a previous stage of capitalism and then present the digital as a deus ex machina giving rise to a profound transformation, leaving them with a “presentist two-stage schema” (39). He predicts “we are likely to see further furries of books that are nominally about the future of capitalism, but offer, at best, depictions of observed regularities in how capitalist frms expand their stocks of capital to include data” (42) (ouch).

The problem is that many of the developments in an arena like FinTech which the authors seize upon are better explained by the dynamics of capital accumulation in a way continuous with what we have seen before, as well as being driven by the existing players within finance. From pg 40

The big banks—heavyweight ambassadors of supposedly outdated fnance capitalism—are spending large sums on tech: Citigroup’s tech budget was $8 billion in 2019; Wells Fargo’s, $9 billion; Bank of America’s, $10 billion; jp Morgan’s topped out at $11 billion. These are impressive fgures, on a par with the tech giants them-selves. Indeed, the top ten us spenders on technology last year were banks and tech frms, with the addition of Walmart.12 jp Morgan has launched a well-staffed ai team in New York and a 1,000-person FinTech campus in California, suggesting it’s on the cutting-edge of innovation. Palo Alto now also hosts BlackRock Lab for Artifcial Intelligence.

However Morozov claims much of this investment is going into maintaining legacy systems, rendered increasingly expensive by multiple rounds of mergers, rather than innovation as such. However the bigger banks are spending more, as well as more of what they spend being directed towards advanced technology. The promise is that FinTech can provide profits on a par with contemporary banking but at substantially lower costs, highlighting again how the pattern of investment is explained by existing dynamics of capital accumulation rather than something extrinsic to them. The future behaviour of these firms is presented in breathless terms as the future of capitalism, as opposed to being a predictable expression of already familiar dynamics.

Morozov observes that the price system rests upon patterns of behaviour which renders shifts in prices legible. If I understand correctly, it presupposes a common background of orientation towards prices and their significance. If data is to substitute for price then what is the comparable common background of orientation? Where are the “new behavioural modes and frameworks of meaning” (46)? There was always a knowledge system, facilitating coordination at a distance from the commodities which are circulating, underpinning the price system and digitalisation merely formalised the latter. From pg 47:

Read from a Hayekian perspective, the digital economy simply formalizes and improves earlier processes of opinion formation, making the reputations of market participants easier to update in real time, or simply alerting cus-tomers, via a notifcation on their phone, to the launch of a new taxi service where the driver would be happy to whistle the client’s favourite tune.

Reducing platform services to technological innovation obscures the institutional change at work. Rather than price being replaced by information, facilitated by the magic of digital technology, collective-legal solutions are being replaced by individual-market ones, with the mystification of technology playing a role in legitimating this transition. As Morozov notes of taxi fare on pg 51:

The rigidity of taxi fares was not a consequence of fawed assumptions about price and information, but a refection of the legal conditions imposed on the cab owners: what they knew about passengers or changing market conditions was irrelevant, as they were legally compelled to offer the same service, at the same rates, to everyone.

Morozov argues that what is at stake here are modes of social coordination. The significance of the technological change rests in feedback infrastructure and the politics surrounding their ownership, operation and use of the data generated. As he writes on pg 53, “the active dismantling of existing forms of planned or law-based social coordination requires the ability to furnish alternative forms that would at least avoid complete anarchy and chaos”. The politics of feedback infrastructure begin here as a struggle over the modes of social coordination which will become hegemonic as we move forward, over a decade after the financial crisis and with populisms of left and right emerging around the world.

The project for the left is how to “find ways to deploy ‘feedback infrastructure’ for new, non-market forms of social coordina-tion, thus challenging neoliberalism with the very tools it has helped to produce” (54). The Chinese social credit system is one example of the form this could take, at a cost which most people would find too high. A more liberal mechanism could be found in deliberative discover mechanisms existing between competition and centralised planning. As he describes on pg 56:

Social existence presents us with a plethora of problems to solve, some of them highly specifc and only relevant to small groups of people, others of much wider impor-tance. Digital ‘feedback infrastructure’ could be used to flag social problems and even to facilitate deliberation thagf them, by presenting different conceptual approaches to the issues involved. What counts as aghh‘problem’ would also be open for debate: citizens could enlist allies and convince others of the virtues of their own readings of particular problems and proposed solutions to them. This framing would suggest that deliberation-based democratic procedures could themselves be modes of problem-solving and means of social coordination.

A nascent form of this coordination between problem-providers and solution-providers can be seen in something like hackathons, notes Morozov, at least in their non-commercial variants. What he advocates is that these processes could be scaled through technological mediation in a way which leaves them independent of co-presence for a defined period of time. The other would be designing ‘non-markets’ which find ways to distribute scarce resources without recourse to the price system. He offers a fascinating account of how Beer’s Cybernetics help us make sense of the modalities of such an initiative. But the underlying question is what social coordination might look like for socialist ends what it is liberated from the ideological baggage of the price system. As he writes on pg 63:

Given this new context, it does not seem very productive for the left to keep advocating for the use of more powerful computers to calculate input prices for the Central Planning Board—or to retain a centralized bureaucracy, with all the political problems it entails. Why insist on central planning, when a more decentralized, automated and apparatchik-free alternative might be achievable by putting the digital feedback infra-structure to work? The most ambitious effort to sketch what such an alternative might look like—think ‘guild socialism’ in the era of Big Data—was undertaken by the American radical economist Daniel Saros, in his rigorous, lucid—and unjustly neglected—Information Technology and Socialist Construction.

Aspects of this system are already in operation, as he writes on pg 65

How realistic is Saros’s system? An examination of how big technol-ogy frms organize their platforms reveals that some aspects of it are already in operation. Amazon, for example, rewards customers with lower prices for registering their expected future needs and ‘subscribing’ to periodic deliveries of regularly consumed products; it also carefully studies product searches and the offerings of other suppliers in its own ‘general catalogue’ to locate gaps in the market. Democratizing access to that information infrastructure, so that all producers can build on these emerging product insights, would surely result in a system that is far less centralized than today’s, where just one frm (Amazon) monopolizes all the planning based on that data.

For Morozov feedback infrastructures are the means for producing alternative modes of social coordination. What matters most is getting them out of the hands of the tech giants. The ecology of social coordination, the many kinds of institutions and technologies which can mediate it, have been obscured by the post-Cold war binary between central planning and the price system. What Morozov describes as “The emancipatory promise of information technology is to rediscover and enrich this repertoire, while revealing the high invisible costs of relying on the current dominant mode of social coordination—capitalist competition” (67)