Believe it or not, a motion to the European parliament recommends that autonomous robots be deemed “electronic persons”. The motion for resolution suggests that self-learning robots, those that make independent decisions and interact freely, be held to have an “electronic personality”.
The proposals in the 2017 motion aren’t as bizarre as it might seem because companies are ‘legal persons’. Such a status means businesses can be held responsible for damages and can insure against such costs. Giving the same status to robots before they become ubiquitous in the workplace and elsewhere would allow likewise.
Even so, about 150 experts in science, law, ethics and other fields slammed the recommendations as “inappropriate”, “ideological” and “non sensical” in a petition to the European Commission. A core complaint was that deeming robots as ‘persons’ would absolve from liability the humans behind a malfunctioning robot.
The legal status accorded to robots is one of countless political issues policymakers must resolve ahead of an expected leap in automation driven by gains in artificial intelligence and robotics. The biggest political challenge would be if the automation likely during the ‘fourth industrial revolution’ were to cause massive unemployment – and a huge number of jobs are thought to be at risk. A just-released OECD study says that 46% of jobs in 32 developed countries are likely to be “significantly affected” by automation over the next 20 years. Other (but not all) studies offer similar forecasts.
Economically, automation will make sense, especially in ageing societies where shrinking workforces put upward pressure on wages. Boston Consulting Group, for instance, says that automation, once installed, cuts manufacturing costs by up to 20%. Robots and algorithms will thus boost productivity and, hence, long-term living standards.
At a political and social level, however, the ramifications of automation could be fraught. Robots and algorithms are poised to destroy countless low- and semi-skilled jobs. While they will create jobs, these jobs are likely to be of the type (higher- and lower-paying ones) that hollow out the middle class. The social safety nets in place to limit any populist backlash against automation appear inadequate to cope with any lasting increase in unemployment and inequality. The pressure is on policymakers to find better solutions than those offered so far to stop political disgruntlement nullifying automation’s economic benefits. It could be this era’s defining political challenge.
Some caveats. A lasting rise in joblessness due to automation is just speculation – it may never happen. Warnings about automation are perennial – John Maynard Keynes, for instance, warned in 1930 of “technological unemployment” (only to see a collapse in demand eradicate jobs). The mistake the pessimists usually make is to underestimate the number of jobs that advances create – and that could happen again. ‘Moravec’s paradox’ – the insight from Hans Moravec (and others) in the 1980s that low-level manual skills are harder to robotise than high-level thinking skills – will limit robotic advances and deployment to some extent. (The paradox essentially says it’s easier to design a robot to play chess rather than kick a ball.) Many service jobs are immune, even if robots might help these occupations. The challenge for policymakers, though, is that the upcoming automation threatens to be unprecedented in terms of scale and speed. While the rise of robotics and artificial intelligence herald a more prosperous longer term, fewer opportunities and reduced financial security for voters could jolt politics in unpredicted ways in the nearer term. Policymakers can see the dangers of the ‘gig’ economy. They have time to find solutions.
Another ‘Engels’s pause’?
The first industrial revolution was pivotal in western history because innovations such as the textile loom and the steam engine transformed Europe from a rural and agrarian society into a manufacturing and urban civilisation. Living standards soared over the long term.
The trouble was the struggles of workers and a rise in inequality in the shorter term. In 2007, Robert Allen of Oxford University described the growth of profits as wages stagnated from 1800 to 1840 as the “Engels’ pause”. Engels refers to Friedrich Engels who, with Karl Marx, authored The Communist Manifesto in 1848, three years after Engels wrote The condition of the working class in England. The pair documented the capacity of capitalists (the bourgeoisie) to upheave the social order and gave birth to a political philosophy that triggered incalculable consequences.
While not expecting the revival of such an extreme ideology, many people warn that automation could usher in more inequality to further radicalise politics – and profits are around a record share of GDP even before robots and algorithms upheave labour markets. The most high-profile pessimist might be Mark Carney, the Bank of England governor. In April, Carney warned of rekindled interest in Marx and Engels’s critique of capitalism. “If you substitute platforms for textile mills, machine learning for steam engines, Twitter for the telegraph, you have exactly the same dynamics as existed 150 years ago when Karl Marx was scribbling The Communist Manifesto,” he cautions.
Many politicians are already airing socialist solutions to counter widening inequalities that work against economic efficiency. Jeremy Corbyn, the UK Labour Party and opposition leader, pledges to (re)nationalise utilities and boost taxes on the wealthy. Bernie Sanders, the US senator and a former Democrat presidential candidate, proposes higher taxes on the wealthy, protectionist trade policies, restrictions on the Federal Reserve’s ability to set monetary policy, and guaranteed employment for all, policies favoured by many other Democrats.
Such pro-labour proposals have audiences because forecasts about a massive wave of automation are common. The International Federation of Robotics predicts another 1.7 million industrial robots will be installed by 2020 to add to the 1.8 million in place in 2016 with corresponding increases in robot density per worker. McKinsey Global Institute said last year that by 2030 about 30% of hours worked globally could be automated and up to 800 million people might be displaced.
Poorer-paying jobs that require only basic education, especially clerical ones, are often said to be most at risk. A White House report in 2016 estimated that 83% of US jobs paying less than US$20 an hour could be automated compared with only 4% of jobs paying more than US$40 an hour.
Wider truth
A poll in the US by Pew Research Center in 2017 found that 72% of respondents worried about an unequal future where robots and algorithms replace workers, while only 33% welcome such developments. Solutions have flowed to salve such concerns that studies show tend to foment populism. A just-released analysis, for instance, by economists at Italy’s Bocconi University of automation’s influence in 15 European democracies from 1993 to 2016 found “robot shock increases support for nationalist and radical” parties.  
The most uncontroversial response to automation is retraining. Over the 20th century, the US flourished because it educated its workforce to seize opportunities created by electricity, automobiles and other innovation. From 1910 to 1940, the number of 14- to 17-year-olds attending high school rose from 18% to 73% while those completing high school soared from 9% to 51%. Governments everywhere need to be just as active in coming years because no country is “genuinely ready” for automation, Swiss tech company ABB said in April when compiling an ‘automation readiness index’.
Today’s concerns are brewing when economies are at full employment – the US jobless rate, for instance, fell to an 18-year low of 3.9% in April. Policymakers especially fret about a future where automation coincides with an economic slump because retraining efforts would fall short. They worry that radical solutions would be needed to avert a political crisis.
One proposal from Bill Gates, among others, is a tax on robots that replace humans. In theory, such a tax would slow automation by boosting its cost while raising money to retrain the displaced. But a robot tax discourages innovation, which means it would slow productivity gains, and doesn’t directly help those superseded by robots. The European Commission, for one, rejects the idea.
Another controversial solution is ‘universal basic income’, a proposal pushed by Silicon Valley household names and left-leaning or populist parties such as the Australian Greens and Italy’s anti-establishment Five Star Movement. Under the scheme, the government pays everyone a ‘living’ wage. Even as governments in Europe test the concept, critics cite its cost, question why the rich would merit a payment, warn of the disincentive to work, and worry about the social cost of turning much of society into a welfare community.
In the US, another proposal pushed by prominent Democrats including Sanders is a ‘federal jobs guarantee’. The self-explanatory proposal resurrects the original legislation that was watered down to become the Full employment and balanced growth act of 1978 (Humphrey-Hawkins). Challenges with jobs for all include the policy’s cost, its failure to halt rising inequality, the ‘crowding out’ of private sector employment, the question of what workers employed by the government would do and its enforceability. The enforceability angle includes that even Humphrey-Hawkins was at cross-purposes with the Fed’s drive in the 1980s to prioritise fighting inflation over reducing unemployment. Jobs for all would put the Fed in the same bind.
Amid the debates around automation and even before it causes massive job losses, wider insights about politics becomes apparent. Algorithms and robots – whether or not the European parliament deems them persons – point to greater government interference with market forces. Thus they would be another blow to neoliberalism and apply pressure on policymakers to install a replacement economic model.
Number of installed industrial robots per 10,000 employees in manufacturing 2016
Source: World Robotics 2017
By Michael Collins, Investment Specialist, Magellan Asset Management

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