PostCapitalism-_Paul-Mason_-_z-library.sk_-1lib.sk_-z-lib.sk_

Project Zero

If you believe there is a better system than capitalism then the past twentyfive years have felt like being – as Alexander Bogdanov put it in Red Star – ‘a Martian stranded on Earth’. You have a clear view of what society should be like, but no means of getting there.

In Bodganov’s novel, the Martians decide to obliterate humanity because we have proved incapable of achieving the postcapitalist society they already possess. That was Bogdanov’s metaphor of despair after the failure of the 1905 revolution.

The possibilities outlined in this book should provide an antidote to such despair. To understand why, let’s update Bogdanov’s metaphor: suppose the Martians really did arrive in orbit, ready to blast us to smithereens. What kind of economy would they see?

Just such a thought experiment was played out by Nobel laureate Herbert Simon in 1991, in a famous research paper entitled ‘Organisations and Markets’. Simon proposed that the arriving Martians would see three kinds of things in our economy: organizations, which would look like big green blobs; markets, which appear like thin red lines between the green blobs; and a set of blue lines within the organizations showing their internal hierarchy. No matter where they looked, said Simon, the Martians would see a system whose dominant colour was green. The message they sent home would say: this is a society primarily made up of organizations, not markets.¹

It was a highly political point to make, in the year the triumph of the market was declared. Simon’s lifelong concern was to understand how organizations work. His paper has been used to demonstrate that, for all the rhetoric about free markets, the capitalist system is primarily made up of organizations that plan and allocate goods internally, in ways not directly driven by market forces.

10

But carried out with greater realism, Simon’s model demonstrates something else: it shows how neoliberalism has opened up the possibility of postcapitalism. Let’s add some detail:

1. The turnover of each green blob (the organization) determines its size; the money involved in each transaction determines the thickness of the red lines between them.

1. The blue lines, which show the internal hierarchy of a firm, have to end in dots as well – the workers: baristas, computer programmers, aircraft engineers, shirt factory employees. Simon didn’t feel the need to model workers separately, but we do. Let’s make them blue dots.

1. To be realistic, each blue dot is also at the centre of a web of thin red lines – connecting each wage earner, as a consumer, to retailers, banks and service companies.

1. Already, the globe looks a lot redder than Simon originally described it. There are trillions of thin red lines.

1. Now let’s add the dimension of time: what happens during a typical twenty-four-hour cycle? If this is a normal capitalist economy we notice the blue dots (the workforce) oscillate in and out of the organizations once a day. As they leave work they start putting out red lines – spending their wages; when they go into the workplace they tend not to – this is a capitalist economy in 1991, remember.

Finally, let’s run the model forward in time, from 1991 to now. What happens to the picture?

First, a lot more tiny red lines appear. A young woman leaves her farm in Bangladesh to work in a factory – her wages generate a new red line; she pays a local nanny to look after her kids, generating a new market transaction: a new red line. Her manager earns enough to start buying health insurance, paying interest to a bank, obtaining a loan to send his son to college. Globalization and free markets generate more red lines.

Secondly, the green blobs split, forming smaller green blobs as firms and states outsource non-core operations. Some of the blue dots turn green – i.e. workers become self-employed. In the USA, 20 per cent of the workforce are now self-employed ‘proprietors’. They too generate more red lines.

Third, the red lines become longer, reaching out across the globe. And they don’t stop when people go to work: buying and selling is now happening digitally, both inside and outside the working day.

Finally, the yellow lines appear.

‘Whoa!’ says the Martian fleet commander. ‘What yellow lines?’

‘It’s interesting,’ says the ship’s economist. ‘We have spotted a whole new phenomenon. The yellow lines seem to show people exchanging goods, labour and services but not through the market and not within typical organizations. A lot of what they are doing seems to be done for free, so we have no idea how thick these lines should be.

Suppose, now, there’s a Martian bombardier with her finger on the trigger, as in Bogdanov’s novel, asking permission to nuke humanity as punishment for its inability to achieve communism.

Most probably, the fleet commander’s response is: ‘Wait! Those yellow lines are interesting.’

FIVE PRINCIPLES OF TRANSITION

The yellow lines in this construct are just a way of trying to visualize goods, labour and services provided collaboratively, beyond the market. They are weak – but they signal that a new route beyond capitalism has opened up, based on promoting and nurturing non-market production and exchange, and driven by information technology.

Up until this point, I’ve treated postcapitalism as a process emerging spontaneously. The challenge is to turn these insights into a project.

Almost everything that’s driving the change is conceived as a project: Wikipedia, Open Source, open information standards, low-carbon energy installations. But few have bothered to ask what a high-level project would look like if we want to move the world economy beyond capitalism.

In part, that’s because many of the old left are infected by the same despair as Bogdanov’s stranded Martian. Others – in the green movement, or NGOs, or community activists and peer-to-peer economists – are so determined to avoid ‘big narratives’ that they’ve stuck to small-scale radical reforms.

In this chapter I will try to spell out what a large-scale postcapitalist project might involve. I call it Project Zero – because its aims are a zerocarbon energy system; the production of machines, products and services with zero marginal costs; and the reduction of necessary labour time as close as possible to zero. Before we start we should outline some principles based on the knowledge gleaned from past failure.

The first principle is to understand the limitations of human willpower in the face of a complex and fragile system. The Bolsheviks failed to understand it; to be fair, most mainstream politicians of the twentieth century also failed to understand it. Now we understand it well. The solution is to test all proposals at small scale and model their macroeconomic impact virtually many times over before we attempt them at a large scale.

Evgeny Preobrazhensky, the murdered Soviet economist, predicted that as market forces began to disappear, economics would become a discipline for designing the future, not just analysing the past. ‘This is quite a different science,’ he said, ‘this is social technology.’²

There’s a chilling quality to that phrase, conjuring the dangers of treating society like a machine. But Preobrazhensky’s description of the tools ‘social technology’ would use were prescient and subtle. He called for an ‘extremely complex and ramified nervous system of social foresight and planned guidance’. Note the terms: foresight and guidance, not command and control. And note the simile: a nervous system, not a hierarchy. All the Soviets had was command, control and the bureaucratic hierarchy, but we have the network. When it comes to organizing change, the network can function better than a hierarchy, but only if we respect the complexity and fragility that comes with it.

The second principle for designing the transition is ecological sustainability. The external shocks discussed in chapter 9 will probably hit us in sequence: short-term localized energy shortages in the next decade; ageing and migration challenges over the next thirty years; and the catastrophic outcomes of climate change after that. The task is to develop technologies that respond to these problems through sustainable growth; we do not have to go backwards in developmental time to save the planet.

The third principle I want to insist on is: the transition is not just about economics. It will have to be a human transition. The new kinds of people being created by networked economies come with new insecurities and new priorities. We already have a different perception of the self from the one in our grandfathers’ and grandmothers’ heads.³ Our roles as consumers, lovers, communicators are as important to us as our role at work. So the project cannot be based purely on economic and social justice.

The French writer André Gorz was right to say that neoliberalism has destroyed the possibility of a utopia based on work. But we will still face a challenge similar to the one the early soviet republics faced with workers: specific social groups may have short-term priorities that clash with the wider priorities of the economy and the ecosystem. That’s what networks are for: to argue things out and model the alternative possibilities. We will need new forms of democracy to arbitrate between valid competing claims. But it won’t be easy.

A fourth principle should be: attack the problem from all angles. With the rise of networks, the capacity for meaningful action is no longer confined to states, corporations and political parties; individuals and temporary swarms of individuals can be just as powerful agents of change.

At present, the community of thinkers and activists around the peer-topeer movement are heavily focused on experimental, small-scale projects – credit unions or co-ops, for example. When they think about the state, it is at the level of laws to protect and extend the peer-to-peer sector. With the exception of thinkers such as Michel Bauwens⁴ and McKenzie Wark⁵, few have bothered to ask what a whole new system of governance and regulation might look like in this new mode of production.

In response, we should broaden our thinking so that solutions can be found through a mixture of small-scale experiment, proven models that can be scaled up and top-down action by states.

So if the solution in finance is to create a diverse, socialized banking system, then setting up a credit union attacks the problem from one

direction, outlawing certain forms of speculation attacks it from another, while changing our own financial behaviour attacks it from still another angle.

The fifth principle for a successful transition is that we should maximize the power of information. The difference between a smartphone app today and the programs on PCs twenty years ago is that the modern apps selfanalyse and pool performance data. Almost everything on your phone and computer is feeding back information on your choices to a corporate owner. Soon the information will be flowing from ‘smart’ electricity meters, public transport passes and computer-controlled cars. The aggregated data of our lives – which will soon include our driving speed, our weekly diet, our body mass and heart rate – could be a hugely powerful ‘social technology’ in itself.

Once the Internet of Things is rolled out, we are at the real takeoff point of the information economy. From then on, the key principle is to create democratic social control over aggregated information, and to prevent its monopolization or misuse by states and corporations.

The Internet of Things will complete a vast social ‘machine’. Its analytical power alone could optimize resources on a scale that significantly reduces the use of carbon, raw materials and labour. Making the energy grid, the road network and the tax system ‘intelligent’ are just the most obvious things on the task list. But the power of this emerging vast machine does not lie solely in its ability to monitor and feed back. By socializing knowledge, it also has the power to amplify the results of collective action.

The socialists of the belle époque eyed the monopolies and cartels with glee: seize them, and control of society from the centre becomes easy, they believed. Our project is to decentralize control – but there could be no better tool for doing so than the vast physical information machine that is being created.

Once we take hold of it, we can put much of social reality under collaborative control. For example, in epidemiology the focus is now on breaking the feedback loops that create poverty, anger, stress, atomized families and ill health.⁶ Efforts to map these problems and mitigate them constitute the cutting edge of social medicine. How much more powerful would that medicine be if the poverty and disease that blight poor communities could be mapped, understood and collaboratively dismantled in realtime – with the micro-level participation of those affected?

Maximizing the power and openness of information needs to become an instinct, embedded in the project.

TOP-LEVEL GOALS

With the above principles in mind, I want to offer not a political programme, but something more like a distributed project. It is a set of linked, modular, non-linear tasks that lead to a probable outcome. Decisionmaking is decentralized; the structures needed to deliver it emerge during the delivery; targets evolve in response to realtime information. And on the precautionary principle, we should use the new breed of simulation tools to model every proposal virtually before we enact it for real.

If I could write the rest of this chapter as post-it notes on a whiteboard, it would better express the modularity and interdependence. The best method for doing a distributed project is for small groups to pick a task, work on it for a bit, document what they’ve done and move on.

Absent the post-it notes, I’ll stick to a list. The top level aims of a postcapitalist project should be to:

1. Rapidly reduce carbon emissions so that the world has warmed by only two degrees Celsius by 2050, prevent an energy crisis and mitigate the chaos caused by climate events.

1. Stabilize the finance system between now and 2050 by socializing it, so that ageing populations, climate change and the debt overhang do not combine to detonate a new boom-bust cycle and destroy the world economy.

1. Deliver high levels of material prosperity and wellbeing to the majority of people, primarily by prioritizing information-rich technologies towards solving major social challenges, such as ill health, welfare dependency, sexual exploitation and poor education.

1. Gear technology towards the reduction of necessary work to promote the rapid transition towards an automated economy. Eventually, work becomes voluntary, basic commodities and public services are free, and economic management becomes primarily an issue of energy and resources, not capital and labour.

In game terms, these are the ‘victory conditions’. We may not achieve them all but, as all gamers know, a lot can be achieved short of total victory.

In pursuit of these goals, it will be important in all the economic changes we make to send transparent signals. One of the most powerful aspects of the Bretton Woods system was the explicit rules it enshrined. By contrast, throughout the twenty-five-year course of neoliberalism, the global economy has been run on implicit rules or, as with the Eurozone, rules that are always broken.

The sociologist Max Weber believed the rise of capitalism was driven not by technology but by a ‘new spirit’ – a new attitude to finance, machinery and work, not the things themselves. But for a new spirit of postcapitalism to take off, we need to focus on where the externalities are being generated and distributed – and to actively propagate an understanding of the phenomena. We need to answer: what is happening to the social benefit that network interactions produce, and which capitalist accounting can’t usually see? Where does it fit in?

Let’s consider a concrete example. Coffee shops today often advertise ‘our beans are organic’ – i.e. this is how we are serving a greater social good. What they mean subtextually is ‘and you are paying a bit more for the feelgood factor’. But the signal is only partially transparent.

Now reimagine the coffee shop as a co-op, paying its workers well, ploughing profits back into activities that promote social cohesion, or literacy, or post-prison rehabilitation, or better public health. The important thing is to indicate – as clearly as the ‘organic’ label on the coffee does – what social good is being produced and who will benefit from it.

It’s more than a gesture: it’s a transparent signal, just as the loaded cannon placed at the gate of the Cromford cotton factory in England in 1771 was a transparent signal. You could erect a sign saying ‘we sell coffee for a profit and that helps us give away psycho-social counselling for free’. Or as with the grassroots foodbank network sponsored by Syriza in Greece, you could just get on with it quietly.

What follows is my best guess at what a project plan would look like, if we were to follow these principles and aim for these five top-level goals. I will be more than happy to see it quickly torn apart and revised by the wisdom of angry crowds.

MODEL FIRST, ACT LATER

First, we need an open, accurate and comprehensive computer simulation of current economic reality. The sources could be the models macroeconomists use – in banks and at the IMF and OECD – and the climate models that generate the IEA’s and other scenarios. But their lopsidedness is striking.

Climate models tend to simulate the atmosphere using advanced maths but simulate the economy like a train set. Meanwhile, most professionally built economic simulators, known as DGSE models, are constructed on the twin fallacy that equilibrium is likely and that all agents in the economy are making simple pleasure-vs-pain choices.

For example, the European Central Bank’s most advanced model of the Eurozone includes only three types of ‘agents’ – households, firms and the central bank. As current events show, it might have been useful to include in that model some fascists, or corrupt oligarchs, or several million voters prepared to put the radical left into power.

Given that we are decades into the info-tech era, it is startling that – as Oxford maths professor J. Doyne Farmer points out – there are no models that capture economic complexity in the way computers are used to simulate weather, population, epidemics or traffic flows.⁷

In addition, capitalist planning and modelling are typically unaccountable: by the time a major infrastructure project starts delivering results, ten or twenty years after its impact was first predicted, there is no person or organization still around to draw conclusions. Thus, most economic modelling under market capitalism is actually close to speculation.

So one of the most radical – and necessary – measures we could take is to create a global institute or network for simulating the long-term transition beyond capitalism.

It would start by attempting to construct an accurate simulation of economies as they exist today. Its work would be Open Source: anybody could use it, anybody could suggest improvements and the outputs would be available to all. It would most likely have to use a method called ‘agentbased modelling’ – that is, using computers to create millions of virtual workers, households and firms, and letting them interact spontaneously, within realistic boundaries. Even today such a model would be able to draw on realtime data. Weather sensors, city transport monitors, energy grids, postcode demographic data and the supply chain management tools of global supermarket groups are all giving off relevant macro-economic data in realtime. But the prize – once every object on earth is addressable, smart and feeding back information – is an economic model that does not just simulate reality but actually represents it. The agents modelled virtually are eventually substituted by granular data from reality, just as happens with weather computers.

Once we are able to capture economic reality in this manner, then planning major changes in an accountable way becomes possible. Just as aircraft engineers model millions of different stress loads on the tail-fin of a jet, it would be possible to model millions of variations of what happens if you reduce the price of Nike trainers to a point between their present \$190 and their production price, which is likely to be lower than \$20.

We would ask our supercomputer lateral questions: do young men get depressed because the Nike brand dies? Does the global sports industry suffer because Nike’s marketing spend is gone? Does quality decline when there is no brand value to maintain in the production process? And what would the climate impact be? To promote its brand, Nike has worked hard to reduce carbon emissions. We might decide keeping the price of Nike trainers high is a good thing. Or not.

This, rather than the meticulous planning of the cyber-Stalinists, is what a postcapitalist state would use petaflop-level computing for. And once we had reliable predictions, we could act.

THE WIKI-STATE