Artficial intelligence (AI) is a subject growing exponentially in interest, funding, and controversy. It has become a tool paramount for improving the efficiency across many organisations and is even beginning to replace entire worklows. AI has shown both benefits and drawbacks, from driving economic growth in many countries to potentially hindering social mobility. Specifically, the UK is a country proven to be well-versed in the motions of AI development through having the third largest AI market in the world, after the US and China, with the sector being greater than any other country in Europe (UK Government,2025). Nevertheless, due to the evolution and successful commercialisation of AI in the UK, there is growing concern of its inevitable impacts on the local economy and its citizens. Therefore, the UK government must take significant measures to ensure the use of AI only contributes to national growth rather than social regression. This would include the focus on AI integration into society, frequent inspection of AI activities, and intervention of AI to support displaced citizens.
Integration of Artificial Intelligence
Firstly, technological change continually demands new ways of integrating into society, and the UK must support innovation by safely interweaving the complexity of AI into public afairs. This refers to ensuring digital literacy through moderated AI usage in academic curricula, business operations, and larger campaigns. For example, there are arrangements in place for AI adoption in the UK’s Digital Inclusion Action Plan, which aims to ensure that all citizens have access to the skills and infrastructure needed to beneit from emerging technologies (for, 2025). By collaborating with the private sector and civil society, the government looks to deliver long-term systemic change to ensure that everyone can participate in the digital society and economy.
While the idea of adopting AI can also add to the dynamism of the UK economy, it brings risks from over reliance, excessive automation, and misuse such as deepfakes, which can undermine public trust and disrupt industries. To protect domestic sectors, companies could prioritise human collaboration with AI and invest in training employees to work efectively with its systems. Yet overcoming barriers such as the skills gap, high costs, and uncertain ROIs will also depend on stronger regulatory guidance and targeted support for both large irms and SMEs (TechUK, 2025).
Turning to education, the use of AI has proliferated in UK schools, often being employed to complete assignments and create entire bodies of coursework, particularly through generative models. Many reports consider this unguarded access to such AI models as the beginning of anti-intellectualism in the younger generations, where increasing dependence on improving AI models has produced results that are often repetitive and lacking in originality. Nonetheless, it is important to emphasise that AI tools can execute complex actions and process otherwise inaccessible or dificult information, making them valuable for incorporation into educational settings. The concern lies in how to ensure AI integration works effectively and in moderation.
As a result, the UK government must carefully consider how to respond to the inevitable integration of AI into society. For the public, this means fostering AI literacy and encouraging moderation in its use. For businesses, it requires ensuring employees receive proper training and support, while still recognising the advantages of responsible AI use. For schools, it involves promoting AI as a tool for organisation and assistance rather than for content creation.
Inspection of Artificial Intelligence
Next, certain measures must be taken such as periodical audits, to ensure that systems are regularly tested for bias and kept aligned with principles of fairness. Independent oversight from government bodies, academic and independent research organisations like dedicated think tanks play an essential role in this process. This is because they can externally identify potential sources of bias before they take root. Notable examples in the UK include the Ada Lovelace Institute and Institute for Fiscal Studies. By reinforcing accountability through recurring evaluations, such audits provide both transparency and public trust, while safeguarding against outcomes that could otherwise perpetuate discrimination.
For example, UK government agencies could require independent audits of AI systems in areas like welfare, policing, and recruitment, examining outcomes across protected groups and publishing results to ensure accountability (CDEI review, 2023). A dedicated AI assurance regulator – in collaboration with bodies such as the ICO – could enforce corrective measures and maintain a public register of audited systems.
Such measures are necessary, since AI in sectors like recruitment have already showed risks: Amazon in 2018 abandoned an AI hiring tool after it discriminated against CVs mentioning ‘women’ (BBC, 2018), presenting how historical biases in training data can produce unfair outcomes. To mitigate such issues, ‘human-in-the-loop’ approaches embed ethical judgement at key stages and convert raw data into responsible datasets (Peradze and in, 2025).
In summary, through a coordinated approach of government regulation, independent research, and human oversight, AI systems can operate transparently, especially in sensitive sectors.
Intervention of Artificial Intelligence
Despite the measures taken to embrace AI and ensure it stays within regulation and compliance, the UK labour market continues to feel the impact of companies favouring its perceived ‘cost-effective’ and ‘lexible’ nature over human workers. It is simply inevitable that with the rise of innovation and technology, employment rates will luctuate, especially among the working class where automation increasingly replaces their roles. So, how can individuals displaced by AI technologies – such as automation or algorithmic systems – access support and restore social mobility?
To support this socioeconomic shift, a fund should be established to compensate those left without work. A modest automation levy could help internalise the negative externalities of job loss, known famously as the ‘robot’ tax. To elaborate, the term refers to a potential scenario where to alleviate the economic burden of those relegated to unemployed status because of AI, periodical taxation of AI companies should naturally be implemented – potentially alongside existing corporate taxes. This is because as AI companies increase in number, such technological advancement will reshape the UK’s world of work faster than the workforce can be trained.
That said, the ‘robot tax’ has faced criticism, with some arguing that it could be perceived as a penalty on innovation. However, this simply reflects the transformative power of the AI industry and its role in responding to the external costs it can create.
Legally and practically, a robot tax in the UK could be implemented by recognising AI and robotic systems as economic actors whose deployment generates value. Companies that replace labour with autonomous systems pay this levy, which would be hypothecated to fund social programmes for displaced workers and include the tax in existing corporate structures. Clear legal deinitions of what constitutes a ‘robot’ or AI system would be essential for enforceability (Ahn,2024). Such an intervention could address the socioeconomic challenges of automation, so AI irms can still scale steadily while contributing to support social equity.
Conclusion
Ultimately, to ensure societal balance in the UK amid the growing use of AI, a three-pronged approach of integration, inspection, and intervention is essential. Integration aims to embed AI safely into society to maximise its beneits. Inspection ensures accountability by auditing AI outcomes. Intervention tackles the social and economic consequences of automation, such as workforce displacement. Together, these strategies give the UK a clear path to safeguard fairness, protect vulnerable communities, and uphold social equity as AI reshapes society.
By Astrid King
References:
UK Government (2025). Artiicial Intelligence. [online] Business.gov.uk. Available at: https://www.business.gov.uk/campaign/grow-your- techbusiness-in-the–uk/artiicial-intelligence/ for, D. (2025). Digital Inclusion Action Plan. [online] GOV.UK. Available at: https://www.gov.uk/government/calls-for-evidence/digital-inclusionaction- plan/digital-inclusion-action-plan
TechUK (2025). Major barriers to AI adoption remain for UK businesses, despite growing demand, new report reveals. [online] Techuk.org. Available at: https://www.techuk.org/resource/major-barriers-to-ai-adoptionremain- for-uk-businesses-despite-growing-demand-new-reportreveals.html
GOV.UK (2020). Review into Bias in Algorithmic decision-making. [online] GOV.UK. Available at: https://www.gov.uk/government/publications/cdeipublishes-review-into- bias-in-algorithmic-decision-making/main-reportcdei-review-into-bias-in- algorithmic-decision-making
Lytton, C. (2024). AI hiring tools may be iltering out the best job applicants. [online] Bbc.co.uk. Available at: https://www.bbc.co.uk/worklife/article/20240214-ai-recruiting- hiringsoftware-bias-discrimination
BBC (2018). Amazon Scrapped ‘Sexist AI’ Tool. BBC News. [online] 10 Oct. Available at: https://www.bbc.co.uk/news/technology-45809919
Peradze, E. and in (2025). How HITL Annotation Powers Responsible AI in 2025. [online] Humans in the Loop | Continuously better models using a human-in-the-loop. Available at: https://humansintheloop.org/howhumans-in-the-loop-powers- responsible-ai-through-data-annotation/
Ahn, M.J. (2024). Navigating the future of work: A case for a robot tax in the age of AI. [online] Brookings. Available at: https://www.brookings.edu/articles/navigating-the-future-of-work-a- casefor-a-robot-tax-in-the-age-of-ai/