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PostCapitalism: A Guide to Our Future

By Hannah Temple.

It is difficult to get through a day without encountering the idea that we as a species and a planet are at some kind of a tipping point. Whether for environmental, economic or social factors (or a mix of them all) there is a growing collective of voices claiming that the fundamental ways in which we live our lives, often linked to the structures and incentives of capitalism, must change. And they must change both radically and soon if we are to protect the future of the human race. Paul Mason’s PostCapitalism: A Guide to Our Future adds another compelling voice to this increasingly hard-to-ignore din. However, what makes this book refreshingly different is the tangible picture it paints of our possible path to a “postcapitalist” world. Mason’s belief is that capitalism’s demise is in fact already happening, and it is happening in ways we both know and like.

The book starts by looking at Kondratieff waves– the idea developed by Nokolai Kondratieff in the 1920s that capitalist economies experience waves or cycles of prosperity and growth, followed by a downswing, characterised by regular recessions, and usually ending with a depression. This is then followed by another phase of growth, and so on and so on. Many people, especially those that benefit from the current economic model, argue that what we are experiencing currently is just another of these regular downswings and we all just have to hunker down and ride the wave until the going gets good again. Mason, however says that even a quick glance at whatever form of evidence takes your fancy (global GDP growth, interest rates, government debt to GDP, money in circulation, inequality, financialization, productivity), demonstrates that the 5th wave that we should currently be riding has stalled and is refusing to take off.

The shift from the end of one wave and the start of a new one is always associated with some form of societal adaptation. Usually this is through attacks on skills and wages, pressure on redistribution projects such as the welfare state, business models evolving to grab what profit there is. However, if this de-skilling and wage reduction is successfully resisted then capitalism is forced instead into more fundamental mutation- the development of more radically innovative technologies and business models that can restore dynamism based on higher wages rather than exploitation. The 1980s saw the first adaptation stage in the history of long waves where worker resistance collapsed. This allowed capitalism to find solutions through lower wages, lower-value models of production and increasing financialization and thus rebalance the entire global economy in favour of capital. “Instead of being forced to innovate their way out of the crisis using technology, the 1 per cent simply imposed penury and atomization on the working class.”

This failure to resist the will of capital and the subsequent emergence of an increasingly atomised, poor and vulnerable global population is part of Mason’s explanation for our stalled 5th wave. The other half of the explanation comes from the nature of our recent technological innovations. Mason contends that the technologies of our time are fundamentally different to those of previous eras in that they are based on information. This is significant in that information doesn’t work in the ways that printing presses or telephones or steam engines work. Information throws all the basic tenets of capitalism- supply and demand, ownership, prices, competition- on their heads. Information technology essentially works to produce things that are increasingly cheap or even free. Think of music- from £10 for a CD in 1997 to 95p for an iTunes track in 2007 to completely free via sharing sites like Spotify in 2017. Over time, Mason claims the market mechanism for setting prices for certain information-based goods will gradually drive them down and down until they reach essentially or even actually zero – eroding profits in the process.

Capitalism’s response to this shift has basically been to put up lots of walls and retreat to stagnant rentier activity rather than productivity or genuine innovation. Legal walls such as patents, tariffs and IP property rights are used to try to maintain monopoly status so that profits can continue to be earnt. Politics is following in the same path with some real walls as well as plenty of metaphorical ones in the form of disintegrating international agreements and partnerships, import tariffs, immigration caps and so on. “With info-capitalism a monopoly is not just some clever tactic to maximise profit, it is the only way an industry can run. Today the main contradiction in modern capitalism is between the possibility of free, abundant socially-produced goods and a system of monopolies, banks and governments struggling to maintain control over power and information”.

However, what seems to be part of the problem is, according to Mason, a critical part of the solution. These new sharing, or “information” technologies, have led to what Mason sees as an already emerging postcapitalist sector of the economy. Time banks, peer-to-peer lending, open-source sharing like Linux and Wikipedia and other technologies are not based on a profit-making motive and instead enable individuals to do and share things of value socially, outside of the price system. This peer-to-peer activity represents an indication of the potential of non-market economies and what our future might look like.

Mason argues that we have now reached a juncture at which there are so many internal and external threats facing our existing system- from climate change, migration, overpopulation, ageing population, government debts- that we are in a similar position to that faced by feudalism before it dissolved into capitalism. The only way forward entails a break with business as usual. Mason emphasises that it is important to remember that capitalism is not a “natural” state of being, nor has it gone on for such a long time. We live in a world in which its existence is seen to be unquestionable but we must take time to teach our brains how to imagine something new again. For Mason, in rather sci-fi fashion, this “something new” is called Project Zero.

Project Zero aims to harness to full capabilities of information technologies to:

– Develop a zero-carbon energy system
– Produce machines, services and products with zero marginal costs (profits)
– Reduce labour time as close as possible to zero

“We need to inject into the environment and social justice movements things that have for 25 years seemed the sole property of the right: willpower, confidence and design.”

Mason provides us with a comprehensive and exciting list of activities to be cracking on with to shape our new world. Some of his ideas are excitingly fresh and new such as the development of an open, accurate and comprehensive computer simulation of current economic reality using real time data to enable the planning of major changes. Others are more familiar such as the shifting of the role of the state to be more inventive and supportive of human wellbeing by coordinating infrastructure, reshaping markets to favour sustainable, collaborative and socially just outcomes and reducing global debts. He also supports the introduction of a universal basic income, the expansion of collaborative business models with clear social outcomes and the removal of market forces- particularly in the energy sector in order to act swiftly to counter climate change. He calls for the socialisation of the finance system. This would involve the nationalization of central banks, setting them explicit sustainability targets and an inflation target on the high side of the recent average to stimulate a “socially just form of financial repression”. It would also involve the restructuring of the banking system into a mixture of non-profit local and regional banks, credit unions and peer-to-peer lenders, a state-owned provider of financial services and utilities earning capped profits. Complex, financial activities should still be allowed but should be separate and well-regulated, rewarding innovation and punishing rent-seeking behaviour.

This push towards a system that rewards and encourages genuine innovation underlies most of Mason’s suggestions for our postcapitalist future. He contends that, if we continue down our current path, it will suffocate us and lead to a world of growing division, inequality and war. We already have systems for valuing things without prices. Working on optimising the technologies we have available to expand these systems, allowing us to live more sustainable, equal and happy lives, Mason argues, should be the key focus for us all.

This book review of Paul Mason’s PostCapitalism by Hannah Temple is originally posted at Rethinking Economics. 

The Automation Grift: From Flying Cars to Ordering Cat Food on the Internet – Part 2

It’s conventional wisdom among pundits that automation will cause mass unemployment in the near future, fundamentally changing work and the social relations that underpin it. Part 1 of this series contrasted this extreme rhetoric with the data that should support the inevitable robot apocalypse, and found that these predictions are likely motivated by politics or outlandish assessments of technology, not data. Part 2 assesses the technology behind these predictions, and follows a thread from the mid-20th century onwards. Subsequent parts will examine the political economy of automation in both general and specific ways, and will also discuss what the future should look like — with or without the robots.

The Automation Grift: From Flying Cars to Ordering Cat Food
on the Internet – Part 2
By Kevin Cashman

Part 1 of this article made a case that macroeconomic data does not suggest that there is rapid automation occurring broadly in the economy nor in large industries or sectors. Other indicators, like slack in the labor market, support that assertion. It pointed to periods of rapid automation in the past as well, and found these were times with generally low unemployment and healthy job growth.

Regardless of the data past or present, there are still claims that society is on a precipice, facing mass unemployment due to wide-scale automation. Many say that the technology in the near future is different than developments that occurred in the past, and that instead of slow or moderate change that the economy can adapt to, the rate of change will be so profound that suddenly millions will be out-of-work.

There are good reasons to be suspicious of this narrative. First, it is very difficult to predict how technology will develop and affect the world, and if it will be viable or even necessary in the first place. Second, adopting new technology — for example, automating a process and replacing workers — and more importantly, the threat of adopting new technology, gives power to employers and capital instead of workers. This weaponization of technology needs to be credible in order to be taken seriously; hence, it relies on the broader narrative that rapid automation is happening. The first point will be considered now; the second, in Part 3.

The (False) Promises of Technology

Predicting how technology affect the future is a difficult endeavor. The flying cars, spaceships, and moon bases that many were sure would arrive by the year 2000 never materialized. Anthropologist David Graeber posits that technological progress did not keep up with imaginations because capitalism “systematically prioritize[s] political imperatives over economic ones.” In a capitalist system like that in the U.S., if political threats do not align with technological advancement like they did during part of the Cold War, flying cars will stay in science fiction books, he says. As the perceived threat from the Soviet Union fell away, neoliberalism’s project shifted to cementing itself as the only viable political system, at the “end of history.”

More recent predictions have remained as bold as they were in the past, but reflect this change in focus. Audrey Watters, an education technology writer, details many in her excellent presentation, “The Best Way to Predict the Future is to Issue a Press Release.” She makes the case that narratives are spun about technology for mostly political reasons or for self-interest, rather than around higher, collective ideals. Bold predictions today are about the destruction and privatization of educational institutions, technology as consumption, or mass unemployment as human labor fades into obsolescence. Pointing to the dismal track record of those who analyze technological trends — based on methods that include opaque and ill-suited taxonomies and graphs, like the one-way hype cycle — she suggests that we are actually in a period of technological stagnation. “[T]he best way to resist this future,” she says, “is to recognize that, once you poke at the methodology and the ideology that underpins it, a press release is all that it is.”

Recent evidence from the dot-com bubble lends itself to these observations. Over-enthusiastic predictions of how the Internet would fundamentally change nature of shopping — not quite a lofty aspiration to begin with — led in large part to the bubble, which popped when it became clear that these companies’ business models did not work. (For example, individually shipping very heavy bags of pet food is expensive, a fact lost on the “innovative” owners of, and “savvy” investors in, Pets.com.) As neoliberalism was busy fashioning itself as the only ideology left standing, it served as the basis for allocating capital in unproductive ways. Whereas the ballooning of the finance sector over the last forty years is sustainable inasmuch as bankers are able to make money by creating and protecting the illusion of their usefulness, the dot-com era was a hard landing for companies that tried the same approach but ultimately could not drum up enough business to survive.

But even if past predictions are incorrect and past technological advances were limited (or had an economic potential that was much less than anticipated), the technology that is developing today could still could be extraordinary and kick off a period of very rapid automation, right? Before going further it is important to define what sort of technological developments could lead to these sorts of changes in the labor market. Often general advances in technology, or things like Moore’s law or speculation about the singularity, are used as evidence that the conditions that underlie the economy are shifting today. Here it is worth quoting directly from Economic Policy Institute’s State of Working America:

“We are often told that the pace of change in the workplace is accelerating, and technological advances in communications, entertainment, Internet, and other technologies are widely visible. Thus it is not surprising that many people believe that technology is transforming the wage structure. But technological advances in consumer products do not in and of themselves change labor market outcomes. Rather, changes in the way goods and services are produced influence relative demand for different types of workers, and it is this that affects wage trends. Since many high-tech products are made with low-tech methods, there is no close correspondence between advanced consumer products and an increased need for skilled workers. Similarly, ordering a book online rather than at a bookstore may change the type of jobs in an industry — we might have fewer retail workers in bookselling and more truckers and warehouse workers — but it does not necessarily change the skill mix.”

The takeaway from this should be that some technological advances that seem significant are not necessarily things that threaten jobs, change their pay or working conditions, or point to a jobless future. Technology can create new consumer products — let’s say smartphones — that seem like they fundamentally change the foundation of the economy. But they actually only shift jobs to the companies making smartphones, and don’t mean that workers making consumer products are somehow unnecessary. More significant developments like the technology behind the car or airplane can make entire industries obsolete but also can create an entire ecosystem of industries that generate wealth. Still other advancements can reduce the costs of products to a large degree so that they are increasingly used as inputs in other industries, benefiting both supplier and buyer.

These sorts of technological development are usually conflated with each other, and with the kind that is supposed to lead to mass automation and job loss. That kind of development is when very expensive robots or software replace humans completely, without spawning new industries and jobs. Two commonly cited examples are self-driving cars and delivery services. Delivery robots and drones might capture imaginations (and make for good PR) but that doesn’t mean that the economics behind them lead to a situation where workers will be replaced anytime soon.¹ Self-driving car technology is massively hyped, but many think they won’t arrive in even a lifetime. Labor platforms, like TaskRabbit, a marketplace to find help with errands or odd jobs, or Uber, the taxi app, are other Silicon Valley “innovations” often lumped in with this discussion. But they don’t threaten to reduce the total number of jobs at all: they shift jobs to their platforms.

This doesn’t mean that more original uses for technology couldn’t significant impact specific sectors. However, it’s likely that, in general, technology that does affect jobs will complement those positions, replacing or changing the specific tasks that workers do, but not going as far as replacing them in all cases. For jobs that are replaced wholesale, it shouldn’t be assumed that they will disappear overnight. There still need to be decisions, investment, and planning involved in replacing workers with (usually expensive) alternatives, which are all things that take time. This has certainly been the case in manufacturing. One interesting table from the Bureau of Labor Statistics that supports this point details the fastest declining occupations. Even extrapolating out ten years, the BLS assumes that there will be significant employment in these occupations. And any changes will vary by specific industry and occupation. Even then, many “low-skill” or low-paying jobs, especially in the service sector, are not conducive to automation very much at all. (And the robots must have forgotten that those were their targets, since many of the fastest growing jobs require no formal education or only a high school degree.)

There’s really no definitive way to tell either way if the robot apocalypse is upon us. But the precedence for wildly inaccurate predictions; the history of technology companies being unable to deliver on extravagant promises; the fact that the technology that would threaten jobs today is more suited toward slow, incremental changes like in the past; and that the orientation of our political system is toward prioritizing political, rather than economic imperatives, strongly suggests that the robots are probably much farther off than is conventionally accepted.

Is the recent deluge of talk of disruptive technological change, ubiquitous automation, and mass unemployment a continuation of the trends and mistakes that Graeber and Watters have highlighted? It seems so, and might even be approaching the lunacy of the dot-com era. Venture capitalists pour billions of dollars into unprofitable companies with questionable business models, which are in turn valued at billions of dollars. Many of the most popular and “innovative” businesses are simply delivery services, transportation companies, or in the consumer goods industry. How many different delivery services does society need? How many different taxi apps does it need? Does anyone really need a $700 juicer, especially if it isn’t even necessary? How are these ways of doing business adding value to the economy, let alone the beginning of a jobless future? More ambitious technology has proven to been a bust, especially in biotechnology.² One also has to question the value of recent technological assessments and predictions when many of the economic and political commentators that are doing that prognosticating couldn’t see the dot-com bubble or even the massive housing bubble that preceded the Great Recession.

The reality is that companies that are seen as the forebearers of mass automation are often unoriginal, repackaging old ideas and existing technology and using political power, venture capital money, and a lot of press releases to survive. Like Graeber said, these “innovations” seem to be more in line with boosting the prevailing economic and political ideology. Old, obsolete ideas³ like flying cars have been resurrected; for example, as part of a public relations and investment strategy to distract from Uber’s myriad scandals and disastrous finances.

If anything, the novelty of this new era of technology seems to come from the lessons business have learned from the survivors of the dot-com bubble, like eBay, Google, and Amazon:⁴ mainly, that business models don’t need to make sense as long as a company is able to take over a big slice of the market and change the terms of that market. In this way, vague ideas about technology and the usefulness of Silicon Valley — promoted by neoliberal icons like Elon Musk, Steve Jobs, and Mark Zuckerberg — are used as a smokescreen for anti-competitive and anti-worker practices that seek to change the economic landscape.

Part 3 will explore an underexamined consequence of this debate: how it affects the social relations between employers, workers, and the government that are a foundation of the economy.

About the Author
Kevin Cashman lives in Washington, DC, and researches issues related to domestic and international policy at the Center for Economic and Policy Research. Follow him on Twitter: @kevinmcashman.

The Automation Grift: Robots Are Hiding From The Data But Not From The Pundits –Part 1

It’s conventional wisdom among pundits that automation will cause mass unemployment in the near future, fundamentally changing work and the social relations that underpin it. But the data that should support these predictions do not. Part 1 of this article contrasts this extreme rhetoric and the data that should support the inevitable robot apocalypse, and finds that these predictions are likely motivated by politics or outlandish assessments of technology, not data. Part 2 assesses the technology behind these predictions, and follows a thread from the mid-20th century onwards. Subsequent parts will examine the political economy of automation in both general and specific ways, and will also discuss what the future should look like — with or without the robots.

The Automation Grift: The Robots Are Hiding From The Data But Not From The Pundits – Part 1

By Kevin Cashman

The Rhetoric

Few things are more breathlessly written about than automation and how it will affect society. In the mainstream discourse, technology writers, policy wonks, public relations hacks, self-stylized “futurists,” and others peddle their predictions and policy prescriptions, as if they are letting the rest of us in on a secret rather than following in a long history of over-enthusiastic predictions and misplaced priorities. Others view automation as a panacea for social problems. Either way, mass unemployment is usually at the center of this narrative and how workers, especially poorer workers, will become outmoded in the age of robots. In the waning days of the Obama administration, the White House joined the frenzy, publishing a report warning about the dangers automation posed to workers as well as the benefits of technology.

This report cited (and further legitimized) a 2013 report that boldly claimed that 47 percent of occupations were at risk from automation in the next two decades. Since its release, this study has been cited close to 900 times. Other predictions are just as bold. One is that the entire trucking industry will be automated in the next ten or so years. “Visionaries” like Bill Gates, Stephen Hawking, and Elon Musk use their stardom to add to the fears of these claims — and push for policies that don’t make much sense, like taxing robot workers or creating a basic income that is an excuse to eviscerate our other social programs and do other bad things. Still others blame automation for causing past problems, like the loss of manufacturing jobs in the U.S., when they are easily explained by political decisions, not economic realities.

With all this interest and all these forecasts, you’d think there would be evidence that automation is affecting the economy in a significant way. Indeed, economists have determined a measure for “automation”: productivity growth. As productivity growth expresses the relationship between inputs (e.g. robots, people, machines) and outputs (i.e. goods and services), it should be a decent and measurable proxy for automation. More automation and robots would result in greater outputs for fewer inputs, which would show up clearly in the data. This is because replacing humans with robots only makes economic sense if it saves money or increases output. In both of these scenarios, productivity would increase.

The Data

So what do the data points say? They show that productivity growth on an economy-wide scale has been very low for the past ten or so years, at a rate that is a bit over 1 percent annually. (In fact, multifactor productivity — productivity of all combined inputs — decreased 0.2 percent in 2016, the first decline since 2009.) The previous ten years — the mid-1990s to mid-2000s — was a period of moderate productivity growth, or just over 3 percent annual productivity growth. From the mid-1970s to mid-1990s, there was another period of slow growth. And before that, there was a sustained period of moderate growth post war until the mid-1970s: the so-called “Golden Age” of prosperity. These data points do not support the assertion that automation is happening on a large scale.

It is important to note that productivity growth and automation are constantly happening, and that automation can affect small industries or occupations in big ways. It can also replace individual tasks but not entire jobs themselves; for example, you may order your food on a computer at a restaurant rather than talk to a waiter, who would still deliver your food. These things may not show up in the data because they do not represent fundamental changes to the entire economy. In other words, automation on a small scale is not evidence that automation will cause a sea change in how work is done: it is normal.

Other macroeconomic indicators support the low rate of productivity growth seen today. The labor market has still not recovered to pre-recession levels, levels which were depressed compared to the highs of the late 1990s and early 2000s. Growth in wages and employment costs have also been relatively low. Since these indicate that there is still considerable slack in the labor market (i.e. in general it is easy to fill open positions, and there are many more applicants than open positions) there is less pressure to automate. After all, why would businesses en masse invest in automation on a significant scale if they can find desperate workers willing to be paid minimum wage?

History also provides useful data points. Technological change and its effects on the labor market have been consistently overstated in the past, which is acknowledged by even mainstream economists. If anything, this is evidence that automation is good for the economy because it creates jobs, in net, and it creates new sectors of the economy. It also can increase living standards by, for example, shortening work weeks or improving conditions of work (and together with organized labor, this happened in the “Golden Age,” which is how it got its moniker).

Supporters of the robots-are-taking-all-of-our-jobs myth usually ignore this evidence. They’ll say that productivity growth cannot take into account the changes that are happening and that automation will have catastrophic effects on the labor market either way. While there are legitimate debates to be had on how to measure automation, the reality is that despite all the spilled ink, the robot boosters do not have history or the data on their side. It is only their analysis of the technology that supports their assertions. They think that there is something extraordinary about the technological change that is happening now and it will be transformative, in contrast to the slow and steady automation that occurred in the past, where benefits were realized over a long horizon.

Part 2 assesses the technology behind these predictions.