Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges

This report outlines the potential of AI tools in schools and colleges, and charts a path for the future that maximises the benefits and minimises the risks.

There are three categories of AIEd tool being used in schools and colleges today: learner-facing (eg adaptive learning platforms), teacher-facing (eg automated assessment tools, or advanced teacher dashboards) and system-facing (eg analysing data from across schools to predict school inspection performance).

The UK has a competitive advantage in education technology and artificial intelligence, but without government support and public funding this advantage risks being lost. Despite its huge potential, AIEd is underdeveloped. Our analysis identified only £1m of public funding for AIEd R&D since 2014 (far less than spending in comparable sectors such as healthcare). There are demand and supply-side market failures preventing development and maturity of AIEd, which government intervention can address.

The quality and effectiveness of AIEd must also be improved, through generation of better and more consistent evidence, coordination by government, and more impactful collaboration between schools and college, companies and academia.

Although challenges for the ethical and responsible use of artificial intelligence and the sharing of data are common to many sectors, schools and colleges present a distinct combination of properties and considerations. The sharing of data needs to be governed in a manner that realises benefit for the public, and AIEd must be used ethically and responsibly.

AIEd’s potential and risks is reflected in the views of parents. 61% of parents anticipate that AI will be fairly or very important to the classroom of the near future. However, many are fairly or very concerned about consequences of determinism (77%), accountability (77%) and privacy and security (73%).

Recommendations

Growing AIEd: How can we help the sector grow and scale?

  • Upstream public funding for AIEd R&D through Innovate UK. This funding should prioritise ‘teacher-facing’ and ‘system-facing’ tools, which are currently underexplored despite their high potential.
  • Downstream support to help growth and adoption of the most promising AIEd tools in UK schools and colleges.

Improving AIEd: How can we improve the quality and effectiveness of AIEd tools?

  • Government should mobilise schools and colleges to form an EdTech test-bed to enable companies to test AIEd in real settings.
  • Form a clear point of government leadership through which to coordinate support for AIEd.
  • Closer collaboration between schools and colleges, AIEd companies and research – with companies providing clearer incentives for teachers to engage.

Governance of AIEd: How do we govern data, opportunities and challenges around AIEdd?

  • The Government should publicly declare an ambition to create a system of responsible education data sharing by 2030.
  • The bodies responsible for governing AI and data should dedicate time and resource to considering the consequences of these technologies for education.
  • When using AI for algorithmic decision making in education the ten questions described in the report should be considered.

An Education System that Learns: How can we help our schools and colleges to learn and evolve (just as we expect students to learn and evolve)?

  • Public bodies responsible for exams across the UK should launch an ‘AIEd Assessment Challenge Prize’ to identify new methods for broadening the scope of assessment reliably.
  • Government bodies overseeing accountability systems across the UK should explore how insights from AIEd assessment tools and human expertise can be combined as part of a ‘collective intelligence’ through pilots in schools and colleges.

Authors

Toby Baker

Toby Baker

Toby Baker

Mission Manager, A Fairer Start

Toby worked with local governments to develop and pilot improvements to services that support young children and families.

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Laurie Smith

Laurie Smith

Laurie Smith

Head of Foresight Research, Discovery Hub

Laurie leads on strategic foresight for Nesta.

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Nandra Anissa

Nandra Anissa

Nandra Anissa

Intern, Explorations team

Nandra was a research intern in the Explorations team

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