Dear all, Upon inheriting the Looking Glass from our predecessors, we identified a number of key issues. Firstly, there were simply not enough articles being published, due both to a lack of submissions from the school community and limited responsiveness from the previous Academic Team. Secondly, the Looking Glass had not been advertised or explained effectively enough to the wider school community. As a result, we plan to implement a more consistent and engaging stream of articles on the Looking Glass. As part of this initiative, we are looking to recruit a select group of keen writers from across the lower school who would be willing to produce one high-quality piece of writing, discussion, or media each month for publication on the Looking Glass. We believe this will be hugely beneficial both to the school community, which will gain access to a wider range of opinions and viewpoints, and to prospective writers, who will be able to reference their experience contributing to the Look...
Note: The following essay by Mehdi Ali L6 (20alim1@students.watfordboys.org) placed in the top 5% of entries in the Future Thought Leaders 2026 Essay Competition.
If machines and artificial chatbots can now perform not only manual tasks but also cognitive reasoning once only attributed to humankind, who should reap the benefits of the postmodern technological revolution, and who should bear its costs? As artificial intelligence and robots receive record levels of investment, what happens when machines replace workers? From self-checkout tills to generative AI in professional services and predictive AI evolving in the stock market, the 21st century has seen a shift in the factors of production, with growing investment in capital substituting for labour. In response, some economists and policymakers have proposed a form of “robot tax”: an indirect form of taxation levied on firms that restructure and increasingly digitalise their factors of production and divest from the labour force. Proponents argue it would protect employment and fund social welfare, whilst critics argue that it would come with the opportunity cost of lost productivity and innovation. While labour displacement and concerns for inequality are legitimate, a broad tax on ‘robots’ would increase the risk of inhibiting productivity in the workplace, where low productivity is already a prevalent issue in the UK, as well as lowering long-run living standards. As an alternative, the UK government and the Department of Education should consider increasing public investment in education with a larger focus on artificial intelligence, which can be achieved through emphasis on STEM subjects and digital skills. Consequently, there may be productivity growth, complementing automation by raising the marginal product of labour and enabling a comparative advantage.
One economic argument advocated by classical economists against introducing a robot tax concerns productivity. Automation is a form of capital deepening: firms substitute capital for labour when the marginal product of capital exceeds its relative cost. As outlined in The Wealth of Nations (1776), Smith outlines classical growth theory, where increases in capital intensity raise labour productivity and, over time, real wages. The UK has suffered from a persistent productivity slowdown since the 2008 financial crisis, at just 0.3% per year between 2008 and 2019, compared to 2.0% annually pre-2008 (ONS, 2023) commonly attributed to the fiscal austerity undertaken by David Cameron’s coalition government. Repeating the same mistake by taxing robots during the AI boom would increase the opportunity cost of adopting productivity-enhancing technologies,
thereby discouraging investment. If firms face higher post-tax costs for automation, they may delay or reduce innovation, lowering total factor productivity (TFP) which is already growing less than 0.5% annually since 2008. This risks a decline in gross capital accumulation, as investors would be incentivised to invest internationally where pro-productivity legislation is embraced. In turn, if the rate of capital depreciation exceeds new investment, this may lead to a net decline in the productive capital stock. This reduces capital per worker, lowering productivity and weakening the economy’s future productive capacity, seen as an inward shift of the PPF and a fall in LRAS. Lower net investment can also generate a negative Keynesian accelerator effect, as reduced spending by firms decreases income, employment, and future consumption, which would further contribute to an inward shift of AD. In essence, the “Laffer-type” logic is relevant here: beyond a certain point, higher taxation reduces the tax base itself. A robot tax may therefore undermine the very growth that funds public services (government failure).
The long-run consequences extend beyond immediate investment flows. It is important to note the increasing risk of losses in international competitiveness in an increasingly globalised and interconnected economy. Opponents argue the risk of the UK imposing a unilateral robot tax is that countries such as the United States provide subsidies for semiconductor manufacturing and AI research, such as the “US CHIPS Act", which allocates $52 billion in subsidies, incentivising investors to reallocate accordingly. Multinational firms compare expected after-tax returns across jurisdictions. Given the mobility of capital relative to labour, the incidence of such a tax could partially fall on workers through lower wages or reduced employment opportunities. Given that FDI inflows into the UK fell by over 30% between 2016-2021 (UNCTAD) and assuming ceteris paribus, capital taxes can be distortionary when capital is internationally mobile and operating within an open market framework. If other economies accelerate productivity growth through AI while the UK slows its capital accumulation, relative living standards will diverge. Over time, this implies a structural inward shift of the UK’s LRAS relative to trading partners. Ironically, this would strongly imply AI can indirectly harm workers, not aid them.
Beyond static efficiency losses, a robot tax may compromise efficiency by restricting the rate of new job growth. Conversely, historical trends do not support this. The British Industrial Revolution eliminated many artisanal jobs but opened doors to a plethora of new sectors, including manufacturing and services. Digital technology emerging from the end of the “.com” boom led to a shift from clerical work to employment in software, logistics, and digital marketing. From a Schumpeterian perspective, opponents argue that robots stimulate “creative destruction” via innovation and ultimately create economic activity. While short-run frictional unemployment may rise, labour markets adjust through wage flexibility, occupational mobility, and new skill formation. A robot tax risks freezing the economy in its current structure, protecting declining occupations at the expense of emerging industries, thereby reducing both dynamic and allocative efficiency.
On the other hand, proponents of a robot tax raise a serious distributional concern. Automation may contribute to increased inequality, as digitisation would structurally reform the demand for high-skilled labour while reducing demand for routine middle-skilled jobs, contributing to increasing wage polarisation. If robots substitute for labour, national income shifts from wages to profits. Within the UK, the majority of capital
ownership remains concentrated within the top 10% of households, who hold approximately 45% of total wealth (ONS Wealth Survey). This can be illustrated using the Lorenz curve and Gini coefficient framework: automation may shift the Lorenz curve further from the line of equality; the UK’s Gini coefficient stands at approximately 0.35. In this view, a robot tax could internalise a distributional externality by redistributing gains from capital owners to displaced workers, perhaps funding retraining or universal basic income.
However, this redistributing objective does not necessarily require taxing robots or technology. From a revenue and taxation standpoint, it is problematic to define a “robot tax”: whether it should be a tax on consumption or production. What is a robot? Is a spreadsheet macro a robot? Is AI-assisted legal drafting automation? An ambiguous tax base would create avoidance incentives and administrative complexity. Even if the tax were successful in nature, it would perversely encourage firms to retain low-productivity labour purely to avoid taxation, reducing allocative efficiency and creating deadweight social welfare loss. If the policy goal is redistribution, more direct instruments, such as progressive income taxation and wealth taxes, would achieve similar outcomes.
Another argument in favour of a robot tax relates to fiscal sustainability. As automation reduces payroll employment, government revenues from income tax and National Insurance contributions may fall. A robot tax could broaden the tax base in an increasingly capital-intensive economy. However, this concern may be overstated; corporate tax receipts have recently risen to over £80 billion (HMRC, 2023) despite digitalisation. Neoclassical free market economic thinking would argue as such; distorting the price mechanism comes with minimal utility gains. Rather than introducing a novel tax, reforming corporate tax to reduce avoidance, closing loopholes, and ensuring multinational firms pay tax proportionate to UK economic activity may be more effective.
Nevertheless, it is acceptable to consider the virtues of government intervention to protect the labour market and the proletariat. Automation may generate negative externalities in local labour markets, particularly in regions already experiencing increasing structural unemployment and social dislocation. In such contexts, transitional support may be warranted. Classical economic theory suggests that when a policy instrument targets the wrong margin, it produces deadweight loss. A robot tax addresses the symptom, capital substitution, rather than the underlying issue of worker adjustment and skill mismatch, with only 52% of UK adults possessing basic digital skills (Lloyds Consumer Digital Index). A superior response would target underlying market imperfections: skill mismatches, transitional unemployment, the lack of public investment in education, and policies like apprenticeship schemes. These would raise the marginal product of labour through co-operation with AI systems.
To conclude, the proposal for a robot tax does give rise to legitimate concerns, and its macroeconomic consequences would likely be counterproductive. By deterring AI investment, dynamic efficiency will decrease, and tax risks will shift the UK’s LRAS and leftwards over time, undermining not only productivity growth but also leading to a decline in living standards. In a global economy where rival nations subsidise and attract high-tech investment, unilateral capital taxation would weaken the UK’s competitive position and reduce future
export capacity. The appropriate policy response is not to impede technological progress but to shape its distributional outcomes through internalising the negative externalities via progressive taxation and subsidising education in order to maximise utility and work towards allocative efficiency. The challenge for the UK is therefore not whether to tax robots but ensuring growth is sustained along with the gains from automation.
“A prosperous economy is not one that resists innovation out of fear, but one that equips its workforce to harness it."
Bibliography:
1. Office for National Statistics (ONS) – UK Productivity Overview
https://www.ons.gov.uk/economy/economicoutputandproductivity/productivitymeasures
2. Office for National Statistics (ONS) – Wealth and Assets Survey
https://www.ons.gov.uk/peoplepopulationandcommunity/personalandhouseholdfinances/incomeandwealth 3. HM Revenue & Customs (HMRC) – Income Tax Statistics and Receipts
https://www.gov.uk/government/statistics/income-tax-statistics-and-distributions
4. HM Revenue & Customs (HMRC) – Corporation Tax Statistics
https://www.gov.uk/government/statistics/corporation-tax-statistics
5. Schumpeter, J.A. (1950) The Process of Creative Destruction. In: Capitalism, Socialism and Democracy, 3rd Edition, Allen and Unwin, London.
https://eet.pixel-online.org/files/etranslation/original/Schumpeter,%20Capitalism,%20Socialism%20and%20Democracy.pdf 6. Office for Budget Responsibility (OBR) – Public Finances Databank
https://obr.uk/data/
7. UNCTAD – World Investment Report (FDI Statistics)
https://unctad.org/topic/investment/world-investment-report
8. OECD – Productivity Statistics
https://www.oecd.org/economy/productivity/
9. OECD – Active Labour Market Policies Data
https://www.oecd.org/employment/activation.htm
10. Stanford University – AI Index Report
https://aiindex.stanford.edu/report/
11. Lloyds Bank – UK Consumer Digital Index
https://www.lloydsbank.com/banking-with-us/whats-happening/consumer-digital-index.html
12. World Bank – World Development Indicators (Labour Share Data)
https://data.worldbank.org/
13. UK Government – CHIPS and Science Act (US CHIPS Act overview)
https://www.congress.gov/bill/117th-congress/house-bill/434
14. Higher Education Statistics Agency (HESA) – STEM Enrolment Data
https://www.hesa.ac.uk/data-and-analysis
15. Department for Digital, Culture, Media & Sport (DCMS) – UK Digital Sector Economic Estimates https://www.gov.uk/government/statistics/dcms-sector-economic-estimates
16. Adam Smith (1776) – The Wealth of Nations
https://www.gutenberg.org/ebooks/3300
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