Our Future of Britain initiative sets out a policy agenda for governing in the age of AI. This series focuses on how to deliver radical-yet-practical solutions for this new era of invention and innovation – concrete plans to reimagine the state for the 21st century, with technology as the driving force.
Contributors: James Browne, Alexander Iosad, James Scales
Chapter 1
AI has the potential to significantly boost students’ academic performance through three key channels.
It could enhance the quality of teaching through AI co-pilots for teachers, which could help with lesson planning, student assessment and data analysis. For example, AI-powered platforms for schools, such as Century Tech, already analyse student data to help teachers address student weaknesses in a more targeted way.[_]
It can free up teacher time to focus on more interactive learning by automating repetitive tasks such as grading assignments and tracking attendance. Teachers are beginning to use AI algorithms in edtech tools to grade students’ work faster.[_]
And it has the power to increase students’ ability to absorb lesson content through AI tutor bots, which could tailor personalised content and provide real-time feedback. AI edtech startups have been at the forefront of building chatbot-style learning where an AI tutor imitates a human teacher. It prompts questions, provides on-demand support and gives instant formative assessments. Some edtech tools developed AI speech recognition for tutoring students.[_]
AI-enabled higher educational attainment could significantly improve the United Kingdom’s economic outlook and the public finances by increasing the future productivity of the UK’s workforce and boosting economic growth.
AI learning tools remain relatively new, so there is a dearth of in-depth academic studies and long-running, large-scale pilot programmes to robustly assess their impact on learners.
In this paper, a companion to The Economic Case for Reimagining the State, we attempt to quantify the costs and benefits of rolling out an AI-enabled education programme in the UK. This programme would set up the foundational infrastructure for AI to have the maximum effect on student attainment. It includes a digital learner ID to seamlessly integrate all educational information on one platform, AI-enabled edtech tools for students and an AI co-pilot for teachers – all enabled by widespread use of tablets and staff training in digital skills and AI competencies.
Overall, we find that:
AI could boost educational attainment levels by around 6 per cent through a combination of improving average attainment of individual students and by enabling more students to progress to higher levels of education.
Such effects will take time to feed through to the labour market but the potential gains are substantial. By boosting the productivity of the future workforce, AI-enabled education could raise GDP by around 6 per cent in the long run and add more than 0.1 per cent to growth per year for over 40 years.
We estimate the cost of rolling out AI-enabled education to the UK’s 26,500 schools would require investment in: a) new digital infrastructure including new edtech tools and a digital learner ID for each student; b) teacher training in the new technology; and c) ongoing investment in AI-enabled hardware for students and teachers. Overall, we estimate the programme would involve an initial setup cost of £0.4 billion and cost around £1.2 billion per year in today’s prices to maintain (or 0.04 per cent of GDP per year).
The speed with which an AI-enabled education programme could be rolled out will depend on the government’s commitment. We take the experience of rolling out virtual-learning environments during the pandemic as instructive and assume an ambitious rollout plan: two years for technology development, a year for testing and a year for full-scale implementation.
The fiscal benefits of an AI-enabled education programme should far outweigh the costs in the long term. We estimate the programme would lead a reduction in annual public-sector borrowing of 2 per cent of GDP after 50 years and a cumulative reduction in public-sector net debt of 30 per cent of GDP over the same timeframe. However, given the lags between improving the educational attainment of students and those students entering the labour force, the scheme does take time to break even. Over the first ten years, the scheme would add 0.3 per cent of GDP to the UK’s debt position, but from that point on it would begin paying for itself – breaking even by 2042 and continually improving the public finances. By 2050, the cumulative benefits of the scheme would exceed its costs by a ratio of 2.7, and by 2070, this ratio would have risen to 7.7 and would still be rising.
All of the above figures are based on an assessment of AI’s capabilities as they are today, but the technology is not static. If instead we assume the technology continues to improve so that it raises educational attainment by 10 per cent (versus 6 per cent in the base case) then AI could boost GDP by a further 4 per cent in the long term and reduce the debt burden by a further 10 per cent of GDP after 50 years. This upside scenario is by no means implausible and highlights both the upside potential of investing in AI-enabled education now and the importance of designing the programme in a way that it can continually incorporate improvements in AI over time.
This paper draws on the best available evidence from a wide range of sources to provide an initial assessment, but we recommend that the UK government adopts an outcome-based funding approach to rolling out the programme nationwide.[_]
We begin this paper by reviewing the existing evidence on AI to gauge its potential impact on educational attainment, then explore how higher educational attainment could boost GDP growth. From there we examine the potential costs of rolling out an AI-enabled education programme nationwide, review the overall costs and benefits of such a programme, and conclude by looking to the future to see how advances in AI technology could change the cost-benefit analysis over time.
Read the full paper here. This is one of four companion papers to The Economic Case for Reimagining the State.