automation Archives

Can’t talk right now, I’m transferring energy.

You work all the time. But what is work, really? And how has that changed? In Work: A Deep History, from the Stone Age to the Age of Robots, anthropologist James Suzman digs into these questions. But whether he realizes it or not, he leaves an even bigger one to us.

The future of work is a hot topic. Automation, climate, and inequality make us wonder what’s coming down the pipe, and how to prepare. We might have to change how work works by decoupling labor from pay… difficult questions. But one thing is clear: if we are to change our conception of work, it will help to understand the one we have.

So what’s work, really?

Suzman starts at the beginning—3.5 Billion years ago. Because at its essence, he argues, work is not whatever you get paid for. It is a transfer of energy.

Thanks to the law of entropy, he explains, everything in the universe tends to chaos. Life forms impose some kind of order, but creating and maintaining that order takes energy. It requires work to grow leaves or make honey or build a house. So yes, even bacteria and trees do work, despite the fact that they don’t have thoughts about it.

So, Suzman posits that the act of work has been around for a long time, but the idea of work is newer. He explains that our mastery over fire was a likely catalyst. In reducing the energy required to survive, fire gave us leisure. And that might have helped us conceive of its counterpart: work.

How has it changed?

With that energy-definition in place, Suzman talks us through work’s cultural evolution. We start with hunter gatherers: there’s a Kalahari desert tribe who still hunt large animals by chasing them down on foot, just like back in the day. They run until the animal is so dehydrated that it lays down and awaits their spear.

He points out that although such hunts are exhausting, the tribe is lounging most of the time. They conceive of the world as abundant, and have no concept of private property. You only worry about your immediate needs, which are almost always met.

With the arrival of agriculture, that’s what we lost. Because Suzman suspects that the first food surpluses also introduced the concept of scarcity. Once you have a pile of crops, that pile—unlike nature—starts and ends somewhere. And it can be said to belong to somebody.

So farming ushered in modern economics. We started thinking everything was scarce, and inequalities increased. At the same time, farmers had to wait for their crop to mature and thus needed to live on credit for much of the year. So by keeping a record of their debt we created—you guessed it—money.

After that it’s domesticated animals, machines, cities, and the industrial revolution, causing living standards to rise. Working hours rose, then fell, then rose again. Suzman takes us past Luddites, the Great Depression, JK Galbraith, and the War on Talent, all the way until the present where we continue to work a lot while AI seems to breathe down our neck.

As he sends us off, Suzman admits that we can’t go back to hunter-gathering, but hopes that we take inspiration from the tribes and broaden our understanding of work. He reminds us that scarcity and limitless needs are not inevitable truths, nor are they necessary assumptions. These are fantastic points and his detailed evolution of work is very insightful. But it’s missing a piece.

Now for the biggest question

Imagine that you decide to clean up your room, and you call Suzman in to help. He comes over and finds all kinds of junk drawers you didn’t even realize you had, and he spreads the contents all over your living room floor. Then he leaves.

He helped with a crucial step. To reorganize something, you need to know what you’ve got, and identify all the items. But to put them in a better place, you need to know what they’re for. Why did you buy the things you own? And what’s your purpose in rearranging?

To put it bluntly, Work falls short on the question of why. It’s a big book about what we’ve been doing, without much to say about what we do it for.

To be fair, there are occasions where motives are discussed. One is when he points to a rare bird that builds very elaborate nests only to break them apart and all start over again. Similarly, some people run ultramarathons. Darwin’s survival of the fittest can’t explain it, Suzman says, so it’s probably a way to get rid of energy surpluses.

I can’t explain the bird either. But ask any ultramarathon-runner, and I bet they’ll tell you they did it because it was a meaningful experience—not because they were sitting on the couch bouncing up and down and only 31 miles would do the trick.

The second occasion is consumer culture. Suzman cites Galbraith who points to the way advertisers exploit our relative needs, making us want to work more to buy more. This undoubtedly plays a role. And to state the obvious, many of those less affluent will do any work that can help them survive.

But is that it?

Consider your own case

Why do you do the job you have? Is it the easiest way to survive? Is it a means to get rid of surplus energy? I doubt it. The right kind of work GIVES you energy. How does it do that? Because it’s meaningful. Why is it meaningful? Because you are able to contribute something. You are able to make a change. You are fulfilling a purpose you set for yourself. So these are the questions to ask: What’s the work out there that we think needs doing? What should work be for?

Perhaps Suzman didn’t get to these questions because there wasn’t much room for them in the past. In that case, fair enough. It may be that today’s circumstances of relative affluence and increasing levels of automation give them real relevance only now. But if we want a concept of work that we can carry forward, we can’t let ‘em drop.

And Suzman will be happy to know that there are plenty of young economists ready to do away with the assumptions of scarcity and limitless needs. But doing away with things is not enough. We need to introduce some new stuff too. And if you’re asking me, that new stuff is meaning.

Now if you’ll excuse me, I’ve got some work to do •

About the Author: Heske van Doornen is Manager of the Young Scholars Initiative and co-founder of this blog. Twitter: @HeskevanDoornen

Buy the Book
Work: A Deep History, from the Stone Age to the Age of Robots Book
By James Suzman | Penguin Press (2021)

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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. 

Don’t Be Afraid of Robots: Technology is What We Make of It

Rapid technological change, if it is even happening, does not necessarily need to lead to mass unemployment or even major disruptions in people’s lives. In all cases, new technology is what society makes of it — that is, it should be used to broadly improve lives and work, not reorient the world around the technology itself or redistribute wealth upwards. Ride-hailing services like Uber and the promise of self-driving cars illustrate both sides of this point; polices like a job guarantee provide a path forward.

Illustration: Heske van Doornen

Don’t Be Afraid of Robots: Technology is What We Make of It

By Kevin Cashman

There is a lot of talk of the rapid development of technology leading to changes in the way people work as well as mass automation and thus mass unemployment. However, the data generally don’t support this story (the most recent data being a notable, but very limited, exception). Nevertheless, the story has currency among the public and politicians, in part due to the novelty and allure of technology — and the political power of its promoters. Throughout recent history, the promises of revolutionary technology have captivated imaginations but also come up far short. Instead of flying cars, there are apps for refrigerators and ordering cat food over the internet.

It is important to note that the gains from technological advancements do not necessarily need to go to the rich or lead to mass unemployment. If shared fairly, the gains could lead to social benefits, such as increased social services, and broad individual gains, such as more leisure time. And there can be concerted action to help those directly affected by technological change. While there are many policies that could be implemented, a job guarantee — where the government provides jobs to all those that need them — is the simplest and most straightforward way to deal with job loss. If people lose their jobs due to factors outside of their control, why not simply provide them with new jobs?

If the gains go to the top, it is important to point out that this is because of deliberate policy. It is not a natural outcome. The rich and their allies in politics promote this redistribution to the top as inevitable — as the “future of work,” for example — whether or not advancements in technology pan out or not. Since advancements in technology do not fundamentally necessitate a change in social relations, this is intentionally deceptive at worst and wishful thinking at best. To see this dynamic, looking at particular jobs and industries is instructive, for example, in taxis and buses and trucking.

The ability to use smartphones and the internet to mediate services is not particularly revolutionary or unique but it does provide some benefits. Uber, the ride-hailing company, brought investment and these ideas to the taxi industry and quickly took over a large part of the market, despite many issues with its service and sustainability. In Uber’s case, appealing to the political power of affluent residents in cities and the supposed innovation of its app was enough to negate its blatant disregard for regulations, questionable safety record, exploitation of drivers, and unprofitability. In this sense, Uber’s investment allowed it to provide some benefits to its relatively wealthy passengers at the expense of the disabled, regular taxi drivers, and others. Most importantly, because it subsidizes every ride (Uber loses money on every ride taken), it was able to undercut the regulated taxi industry. The government’s lack of interest in maintaining fairness in the taxi industry effectively led to Uber being handed the market.

How could this have been different? The taxi industry on a whole is not an industry with large margins or much investment. In part, this is due to underlying characteristics of the industry as well as regulation, including those aimed at limiting the number of taxis operating in a city (which is good policy). To realize the benefits of technology, taxi commissions or groups of taxi drivers in various places could have developed their own app and infrastructure to facilitate ordering of cabs on the internet. This would have required substantial organization and money, which could have been facilitated and provided, respectively, by the government. The result could have been an app that allowed taxi authorities to continue to maintain standards for safety and operation and also provide the seamless service that certain groups of consumers desire. Indeed, competitor apps are being developed this way and existed before Uber, but they must now claw market share away from Uber. This is quite difficult because Uber is still subsidizing rides and keeping prices artificially low.

Let us now assume that rapid technological advancement is inevitable: self-driving cars and buses are finally right around the corner, as has been promised for years. (Indeed society could be on the cusp of this sort of technology, although the challenges shouldn’t be understated.) There would be massive benefits if self-driving vehicles are implemented successfully: increased mobility for the elderly, many fewer accidents, lower operating costs, increased productivity when in transit, etc.

Along with these benefits, there would be significant disruptions to the labor market. Ideas around how to approach these changes were discussed in a recent report, Stick Shift: Autonomous Vehicles, Driving Jobs, and the Future of Work.¹ It discusses two questions that are central to evaluation rapid disruptions to the labor market: How fast will the technology develop? How much of an impact will it have?

Regarding the first question, and assuming that these technological hurdles are overcome,² the report notes:

If the technology is successfully developed, the rate of the adoption and popularization of autonomous vehicles will depend greatly on whether necessary infrastructure is built, and whether and how regulation responds to these advances in technology. One of the inevitable debates will be between those who wish to ensure that autonomous vehicles are safe and reliable and those who want to get them to market as soon as possible. The outcome of this debate could greatly determine how the labor market is affected. Thorough vetting of the technology, along with phased rollouts, would allow time for workers to adjust to incoming shocks, and would dampen those shocks as well.

If the government were to assume the costs of building infrastructure for self-driving vehicles instead of the companies that are selling them, it would be fair for the government to also take a pro-active approach and develop a process to adequately assess the safety of those vehicles. This would somewhat mitigate the effects on the taxi industry and on bus drivers, especially in the early years of their use.

Proponents of self-driving vehicles also often forget to mention that technology will replace individual activities of workers but not necessarily all of the activities that encompass their jobs. Truckers, for instance, perform many other activities besides simply driving:

…in the trucking industry, there are many tasks that are difficult to imagine autonomous-vehicle technology being able to manage, which may limit their adoption or consign them or the driver to a secondary role. This includes many things that truck drivers are required to know, such as how to inspect the vehicle and cargo, perform maintenance and fix emergency problems, put on tire chains and deal with unpredictable weather, refuel the vehicle safely, and carry dangerous materials safely, to name a few.

If self-driving trucks took over the trucking industry, this suggests there would be many more support jobs in the trucking industry.

The other question is more pertinent considering our assumptions. How much of an impact technology will have on society is entirely up to society. The question is then not how much of an impact will self-driving cars have on society but where does society need self-driving cars and how do self-driving cars fit with social goals? There is a convincing argument that cars — self-driving or not — should have much less of a role in cities in the future. While taxis could have a role to play in the future, for example, public transportation and good urban design should be the focus, thus eliminating much of the need for taxis. In this vein, employment in the taxi industry could decline, but in addition to more social benefits from less vehicle use, employment would increase in association with an increase in investment in public transportation.

The social aspects of occupations are also important to consider when asking whether it might be desirable to transition to self-driving vehicles:

There is also the question of more socially oriented driving jobs. Bus drivers are one example. City bus drivers preserve order and safety on buses, provide information, ensure payment, and are generally considered community members and authority figures. School bus drivers have specific responsibilities related to the safety of the children they supervise. For these reasons, it may not be desirable or necessary to replace bus drivers, completely at least, even if the buses were fully autonomous.

In this sense, the elimination of these jobs would be akin to cuts in public services, and they would also eliminate some social benefits. Social aspects of jobs are rarely considered — but they are very important.

Here, a jobs guarantee would be useful, since it is a policy that prioritizes the social aspects of jobs and since social benefits are not prioritized in the private job market. Returning to the example of bus drivers, buses could be self-driving in the future but the “driver” need not be replaced. Rather, the position could be reoriented in a purely social role.

Whether technology will bring small changes, as in the case of Uber, or large changes, as in the case of self-driving vehicles, who benefits is entirely up to society. Gains from technology can be shared broadly with the right policies — just a few of which were described here — so there is no need to inherently fear the robots. A jobs guarantee is one of those policies, and it is perhaps the most important. (And it’s gaining traction in the mainstream.) A broad coalition, focused on the appropriate use of technology and promoting a job guarantee, could keep the actual threat — those wanting to harness the benefits of technology for themselves — at bay. Whether or not robots and mass automation are around the corner, it’s good policy, too.

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.