Will governments tax companies for using chatbots?
There is a storm coming – and that storm is artificial intelligence (AI). AI software will power smart or even superintelligent machines and robots that could impact every aspect of life on the planet.
Although we cannot wholly predict the path, severity or impact of the storm – we do know it’s coming, and we do need to start preparing now.
Here we explore 10 key questions to help the reader get their head around the whole subject of taxing the ‘bots.
1. What’s the background to this debate?
The big issue here is the likely extent to which 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.
On the one hand, we know smart technologies such as AI, blockchain, Big Data, cloud computing, hyperconnectivity, 3D/ 4D printing, smart materials and synthetic biology are developing at an exponential rate. Individually and when combined, they will have an impact from automated warehouses and autonomous cars to computerised drug discovery and the diagnosis of Alzheimer’s disease ten years before the symptoms show - it's already happening.
However, and crucially, we don't know how far and how fast AI and these other disruptive technologies will spread. Furthermore, we don't know how many jobs they will take out, we don't know how society will respond (e.g. the Uber backlash), we don't know the extent to which firms will retain people when they automate, we don't know how fast the new sectors will grow, and we don't know how many new jobs they will create. In practice we are pretty clueless.
2. Why do we need to act now?
What we do know is that jobs are already going, more will follow and it would be a reckless government that didn't think about how to address the challenges.
We already know that to compete in the emerging global economy, we need to change the nature and focus of education at all levels and prepare adults for roles in the new sectors – which will mainly be higher skilled as the “bots” will most likely do the rest. So, it’s reasonable to at least explore the scenario of rising technological unemployment over the next decade.
Realistically, this means we’d need to fund either a higher total unemployment benefit bill or the provision of some form of guaranteed basic income and / or guaranteed basic services. In this scenario, fewer people working means they are likely to be paying less overall income tax which means we have to fund the revenue shortfall somehow - that’s assuming we want to maintain the current level of public service provision whilst also covering the higher unemployment costs.
3. What is the UK doing?
Britain’s ruling Conservative Party is loath to acknowledge the possibility of rising unemployment due to automation. By encouraging business growth, they believe that unemployment costs will be met through revenues from corporate and individual taxes coupled with VAT.
Labour, however, has already 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.
4. What would the taxes be used for?
The primary purpose should be to address the societal consequences of job automation. For example, funding unemployment benefits or guaranteed incomes and services. However, it is difficult to believe that any tax raised could be permanently and transparently ring-fenced by government for one use or another. Is there evidence to show that fuel duty is ploughed back into highway maintenance, for example?
In the UK, Labour has already been mooting the idea of “robot taxes” to finance the cost of adult retraining, education transformation and unemployment provisions.
There is also a strong argument that robot taxes should be channelled directly into public education - paying for public schools and universities. The hope is that this would prevent a backlash from the people whose jobs are lost to automation, and create enough money to revamp an outdated education system into a forward looking one that teaches the knowledge and skills which will be in demand in 2030 and beyond, when most jobs as we now know them are absorbed by robots and algorithms.
A robot tax could help pay for a new approach to education which develops the whole person, not just the 'future worker'. The underlying principle is that we should use the value of automation to benefit society and prevent future problems.
5. Is it really likely to happen?
A number of governments have started to think about the human consequences of automation – exploring everything from new approaches to adult education to encouraging the creation of start-ups. Canada, Finland and Germany have also been experimenting with different forms of guaranteed or universal basic income (UBI). The intention is to learn about them before they are required. Such experimentation seems eminently sensible as an input to any nation’s debate on the topic.
At a broader tax policy level, across the world, rapid automation must be seen as one very important driver of change to nations’ tax collection regimes. Hence it becomes critical to explore different possible scenarios to understand the likely spending requirements and revenues under a range of different conditions. Governments can then examine both their spending priorities and possible revenue instruments.
6. Who will be the pioneers?
It seems unlikely that any government would introduce these kinds of measures within the next 2-5 years, but by 2030 the possible pace of change means they could well be commonplace in many industrial nations. Countries that are embracing automation and the digital era in all its forms such as South Korea, Japan and Singapore might be among the first to implement some form of automation taxation mechanism.
Whilst China is saying little right now it has the capacity to enact policy rapidly should the need arise. Whereas, the overt and hidden political power of the Indian super-corporates means it would be a very late adopter.
In Europe, nations such as Estonia, Finland, Sweden, Denmark, Iceland and Germany are likely to be among the first to revamp their tax systems in this way.
In Silicon Valley many are arguing in favour of robot taxes, but the US is likely to face strong resistance to such changes. Indeed, it 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.
7. What are the practicalities?
The aim should be to evolve a more flexible approach to creating income to fund future public services. The basis of corporate taxation could become even more complex with systems applying AI to large multi-variable data sets to establish a tax liability based on the sector, revenues / profits per employee, the number of people employed, and geographic location.
Perhaps evaluation of a business’s broader impact on society could also factor into the level of taxation applied to its profits – such as the actual level of human employment, local and national social responsibility, environmental impact – so that tax paid is based on the outcomes of a business’s operation across a range of different domains.
At the operational level, it could be costly and complex to implement and opponents will look for any shortcomings to cast it off as a failure.
Some measure of net added value could also be considered. For example, a firm may train its employees so well that they go on to higher paying jobs elsewhere or to generate employment and tax revenues by starting their own business. How might their taxation be assessed relative to a firm who invests little in people development and whose staff cannot find jobs elsewhere when made redundant. In the UK, the PAYE system is a government mechanism by which employers collect tax from employees and transfer it to the tax authorities. This could be used to calculate credits for application against a business’s corporation tax liability.
An interesting scenario to explore would be the possibility that AI could create the opportunity for governments to recover public spending commitments pro-rata from every tax payer and corporation in the country - purely based on individual incomes or business revenues. In the worst-case scenario this could mean firms posting a loss because they failed to make a profit after paying their fair share for running the country.
The key here is modelling a variety of different approaches to see which produces the fairest and most transparent system.
There are precedents we can learn from. For example, the UK pharmaceutical industry has paid a levy based on revenue or capital employed on its supplies to the NHS with a series of allowable and dis-allowable expenses. Whilst this approach has been designed as a mechanism to control profits on medicine supplies to the NHS (while seeking to reward investment in R&D) a similar approach could be taken with companies and the level of automation they employ, versus their “investment” in people.
8. What are the possible risks?
This is going to be hugely controversial and unpopular with a lot of politicians, businesses, commentators, accountancy firms, certain news media and economists. It is already being cast as unbridled socialism, communism or Marxism by many proponents of low taxes and free markets. However, at present, no viable alternatives are being put on the table.
At the operational level, it could be costly and complex to implement and opponents will look for any shortcomings to cast it off as a failure. The prevailing corporate mind-set is often to base multinational operations in lower tax markets, so competition for the hosting of multinational organisations could intensify without global agreements. Inevitably, many will look for ways to minimise their tax payments and a range of advisory services and schemes will spring up to help firms do so. Failure to implement a viable system or a workable alternative could have disastrous consequences for governments, leading to potential reductions in public service provision and even the failure of some economies.
9. What are the potential benefits?
A solution will be required if unemployment does rise and government revenues decline because of lower personal tax and VAT income. Whilst robot taxes may not be the ultimate answer, and better solutions might emerge, it is the only clear policy idea that is even being mooted today for what is an increasingly pressing societal issue. Ultimately, the notion of taxation based on automation could prove to be a catalyst for more socially responsible “carrot and stick” approaches to corporate tax.
Maybe the application of increasingly sophisticated AI could be the critical enabling technology to providing a fair and transparent system with no potential for avoidance or manipulation by individual firms. Indeed, AI could one day give us even smarter tax systems that none of us can even imagine today. Perhaps the fully automated corporation or Decentralised Autonomous Organisation (DAO) of the future may see its prime directive to serve humanity as a whole and maximise its contribution to society.
10. Let’s get started?
The first stage must be to run some serious computer simulations of different scenarios for the pace of automation and the impacts on employment in different countries around the world. These could be used as input to the development of economic models to explore the funding requirements of different public service strategies and how they might be met.
AI is creating the tools that are driving the pace of automation and the prospect of increased unemployment. But, AI 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.