Robots and AI: utopia or dystopia? part one
I did a recent post on Paul Mason’s new book, Postcapitalism, which argued that the internet, automation, robots and artificial intelligence were creating a new economy which could not be controlled by capitalism. According to Mason, new forces are at work that were replacing the old class struggle between capital and the proletariat, as Marx saw it, with a network of communities. Technology and the network would lead to a post-capitalist (socialist?) world that could not be stopped
I disagreed that the new technology would replace the ‘old forms’ of class struggle or for that matter regular and recurrent economic crises under capitalism would dissipate towards a high productivity, low working day as capitalism ‘withered away’.
But this debate has encouraged me to do something that I have been wanting to deal with in more detail for some time. Namely, what are the implications of these new technologies for capitalism? In particular, are robots and artificial intelligence set to take over the world of work and thus the economy in the next generation and what does this mean for jobs and living standards for people? Will it mean socialist utopia in our time (the end of human toil and a superabundant harmonious society) or capitalist dystopia (more intense crises and class conflict)?
It’s a big subject. So let me first make a few definitions. By robots, I mean machines that can replace human labour through the use of computer programmes that direct the movement of machine parts to carry out tasks, both simple and increasingly complex.
The International Federation of Robotics (IFR) considers a machine as an industrial robot if it can be programmed to perform physical, production-related tasks without the need of a human controller. Industrial robots dramatically increase the scope for replacing human labour compared to older types of machines, since they reduce the need for human intervention in automated processes. Typical applications of industrial robots include assembling, dispensing, handling, processing (for instance, cutting), and welding – all of which are prevalent in manufacturing industries – as well as harvesting (in agriculture) and inspecting of equipment and structures (common in power plants).
Industrial robotics has the potential to change manufacturing by increasing precision and productivity without incurring higher costs. 3D printing could generate a new ecosystem of companies providing printable designs on the web, making everyday products endlessly customizable. The so-called ‘Internet of Things’ offers the possibility to connect machines and equipment to each other and to common networks, allowing for manufacturing facilities to be fully monitored and operated remotely. In health care and life sciences, data driven decision-making, which allows the collection and analysis of large datasets, is already changing R&D, clinical care, forecasting and marketing. The use of big data in health care has led to highly personalized treatments and medicines. The infrastructure sector, which had no gain in labour productivity in the last 20 years, could be greatly enhanced by, for example: the creation of Intelligent Transportation Systems, which could massively increase asset utilization; the introduction of smart grids, which could help save on power infrastructure costs and reduce the likelihood of costly outages; and efficient demand management, which could dramatically lower per-capita energy use.
Which of these emerging technologies have the greatest potential to drive improvements in productivity? McKinsey Global Institute (MGI) (2013) reckon that ‘technologies that matter’ are technologies that have the greatest potential to deliver substantial economic impact and disruption in the next decade. Those that make their list are rapidly advancing (e.g. gene-sequencing technology); have a broad reach (e.g. mobile internet); have the potential to create an economic impact (e.g. advanced robotics) and have the potential to change the status quo (e.g. energy storage technology). MGI estimates that the economic impact of these technologies – derived from falls in their prices and their diffusion and improved efficiency – to be between $14 and $33 trillion per year in 2025, led by mobile internet, the automation of knowledge work, the internet of things and cloud technology.
John Lanchester in a brilliant essay summed this up (Lanchester): “Computers have got dramatically more powerful and become so cheap that they are effectively ubiquitous. So have the sensors they use to monitor the physical world. The software they run has improved dramatically too. We are, Brynjolfsson and McAfee argue, on the verge of a new industrial revolution, one which will have as much impact on the world as the first one. Whole categories of work will be transformed by the power of computing, and in particular by the impact of robots.”
By artificial intelligence (AI), is meant machines that do not just carry out pre-programmed instructions but learn more new programmes and instruction by experience and by new situations. AI means in effect robots who learn and increase their intelligence. This could happen to the point where robots can make more robots with increasing intelligence. Indeed, some argue that AI will soon surpass the intelligence of human beings. This is called the ‘singularity’ – the moment when human beings are no longer the most intelligent things on the planet. Moreover, robots could even develop the senses and form of human beings, thus being ‘sentient’.
But before we get into science (or science fiction?), let us consider first things first. If robots and AI are fast on their way, will this mean a huge of loss of jobs or alternatively new sectors for employment and the need to work fewer hours?
In recent work, Graetz and Michaels looked at 14 industries (mainly manufacturing industries, but also agriculture and utilities) in 17 developed countries (including European countries, Australia, South Korea, and the US) They found that industrial robots increase labour productivity, total factor productivity, and wages. At the same time, while industrial robots had no significant effect on total hours worked, there is some evidence that they reduced the employment of low skilled workers, and, to a lesser extent, also middle skilled workers. Full paper here .
So in essence, robots did not reduce toil (hours of work) for those who had work, on the contrary. But they did lead to a loss of jobs for the unskilled and even those with some skills. So more toil, not less hours; and more unemployment.
Two Oxford economists, Carl Benedikt Frey and Michael Osborne, looked at the likely impact of technological change on a sweeping range of 702 occupations, from podiatrists to tour guides, animal trainers to personal finance advisers and floor sanders. Their conclusions were frightening: “According to our estimates, about 47 percent of total US employment is at risk. We further provide evidence that wages and educational attainment exhibit a strong negative relationship with an occupation’s probability of computerisation…. Rather than reducing the demand for middle-income occupations, which has been the pattern over the past decades, our model predicts that computerisation will mainly substitute for low-skill and low-wage jobs in the near future. By contrast, high-skill and high-wage occupations are the least susceptible to computer capital.’ Lanchester summed up their conclusions: “So the poor will be hurt, the middle will do slightly better than it has been doing, and the rich – surprise! – will be fine.”
Lanchester makes the point in his essay that the robotic world could lead, not to a ‘post-capitalist’ utopia but instead to a ‘Pikettyworld’ “in which capital is increasingly triumphant over labour.” And he quotes the huge profits that the large techno companies are making. “In 1960, the most profitable company in the world’s biggest economy was General Motors. In today’s money, GM made $7.6 billion that year. It also employed 600,000 people. Today’s most profitable company employs 92,600. So where 600,000 workers would once generate $7.6 billion in profit, now 92,600 generate $89.9 billion, an improvement in profitability per worker of 76.65 times. Remember, this is pure profit for the company’s owners, after all workers have been paid. Capital isn’t just winning against labour: there’s no contest. If it were a boxing match, the referee would stop the fight.”
But looking at the profits of companies that have seized the value created by labour in the new sectors is not necessarily a guide to the health of capital as a whole. Is capitalism as a whole having a new lease of life as a result? After all, overall investment growth is very low in the current long depression and productivity growth as a result also. See my posts on productivity and investment.
Robots do not do away with the contradictions within capitalist accumulation. The essence of capitalist accumulation is that to increase profits and accumulate more capital, capitalists want to introduce machines that can boost the productivity of each employee and reduce costs compared to competitors. This is the great revolutionary role of capitalism in developing the productive forces available to society.
But there is a contradiction. In trying to raise the productivity of labour with the introduction of technology, there is process of labour shedding. New technology replaces labour. Yes, increased productivity might lead to increased production and open up new sectors for employment to compensate. But over time, a capital-bias or labour shedding means less new value is created (as labour is the only form of value) relative to the cost of invested capital. There is a tendency for profitability to fall as productivity rises. In turn, that leads eventually to a crisis in production that halts or even reverses the gain in production from the new technology. This is solely because investment and production depend on the profitability of capital in our modern mode of production.
So an economy increasingly dominated by the internet of things and robots under capitalism will mean more intense crises and greater inequality rather than super-abundance and prosperity. In my next post on this subject, I’ll consider whether the world of robots making robots with ever-increasing intelligence – and perhaps eventually no human labour employed – would end the law of value and recurrent crises under capitalism.