Robot 2

Automation will reshape the industrial landscape, change the nature of work as we know it and drive up the number of people facing permanent unemployment. Faced with the possibility of mass unemployment – could taxing the robots be the answer? Rohit Talwar, Steve Wells and Alexandra Whittington from Fast Future, put their heads together and consider this thorny question. 


It would be reckless for governments not to explore the danger of rising technological unemployment over the next decade, and how to fund either a higher total unemployment benefit bill or the provision of some form of guaranteed basic income and/or guaranteed basic services.

Britain’s ruling Conservative Party is loath to acknowledge the possibility of rising unemployment due to automation. The hope is that encouragement of free markets and lower corporate tax rates will drive business growth and employment, and unemployment costs will be met through revenues from corporate and individual taxes coupled with VAT.

In contrast, the rising number of young members in the opposition Labour Party are concerned about the impact on their future – spurred on by already high levels of youth and graduate unemployment. They are keen to ensure Britain doesn’t go into the kind of decline we saw with Greece and Spain.

In response, Labour has been mooting the idea of ‘robot taxes’ to finance the cost of adult retraining, education transformation and unemployment provisions. The argument is that robots should be taxed because they will be considered as something that creates value for the owner, like property, and if firms are cutting headcounts, then they are likely to be making higher profits. Furthermore, the belief is that those who will receive the benefits will spend that money with the firms who paid the robot taxes.

What would robot taxes pay for?

Rohit Talwar believes that the primary purpose should be to address the societal consequences of job automation. So, the most obvious application would be to fund unemployment benefits or guaranteed incomes and services.

Alongside unemployment costs, there is a strong argument that a significant proportion of the revenue from robot taxes should be channeled directly into public education.  This would create a positive role for robots in society, which would be to pay for public schools and universities, and perhaps even a new approach to education which develops the whole person, not just the ‘future worker’.  These would include life skills (cooking, health and household management), interpersonal skills (listening, leadership, writing) and self-awareness (mindfulness, meditation, mental health strategies).  The underlying principle is that we should use the value of automation to benefit society and prevent future problems.

When and who?

Steve Wells suggest that we could see these taxes in place by 2030 in many industrial nations.

South Korea, Japan and Singapore might be among the first to implement some form of automation taxation mechanism.

China is saying little right now, but it has the capacity to enact policy rapidly should the need arise. Whereas, India is likely to be a late adopter due to the overt and hidden political power of the super-corporates.

Estonia, Finland, Sweden, Denmark, Iceland, and Germany are likely to be among the first to revamp their tax systems in Europe.

But the US could well be among the last to go down this route and might conceivably not do so at all without a fundamental change in its governance and electoral systems.

How might such taxes work in practice?

 Alexandra Whittington suggests that the going in point should be to evolve a more flexible approach to creating income to fund future public services. Algorithms could take account of factors such as expenditure on training and retraining current and former employees, the support given by firms to start-ups, the level of employment created further down the value chain, and the amount of tax paid by the firm’s employees.

Perhaps an evaluation of a business’s broader impact on society could also factor into the level of taxation applied to its profits.

The key here is modeling a variety of different approaches to see which produces the fairest and most transparent system. This may well evolve over time as the controlling AI algorithm learns about what behaviours it engenders in firms to try and reduce their tax bill.

Artificial intelligence is creating the tools that are driving the pace of automation and the prospect of increased unemployment. Equally, AI tools could also be used to design and develop new approaches to taxation that could help us address the societal consequences of technological disruption and ensure a very human future for all.

Rohit Talwar, Steve Wells and Alexandra Whittington are from Fast Future which publishes books from future thinkers around the world exploring how developments such as AI, robotics and disruptive thinking, could impact individuals, society and business and create new trillion-dollar sectors. Fast Future has a particular focus on ensuring these advances are harnessed to unleash individual potential and ensure a very human future. See: