Today, the Digital Poverty Alliance (DPA) launched its much-anticipated report, Rethinking Education with Generative AI, at Parliament. This publication examines the transformative potential of Generative AI in education, alongside the risks it presents for children and young people experiencing digital poverty. The report offers actionable recommendations to harness AI technologies equitably and responsibly, ensuring they help bridge the digital divide rather than exacerbate it.
Generative AI is rapidly reshaping education, offering opportunities to personalise learning, enhance outcomes, and support educators. However, without deliberate policies and resources, these advancements risk deepening existing inequalities. For the 1 in 5 children in the UK living in digital poverty – defined as lacking access to suitable devices, reliable internet connectivity, and essential digital skills – the barriers are considerable. This report seeks to empower these students, ensuring that advancements in Generative AI create pathways for inclusion rather than exclusion.
Drawing on extensive research, including surveys, case studies, and expert discussions, the report highlights critical policy gaps and inequities. It underscores the urgent need for comprehensive teacher training, equitable access to technology, and a national framework to prepare students for an AI-driven future.
Elizabeth Anderson, CEO of the Digital Poverty Alliance, commented: “Generative AI has the potential to transform education by personalising learning and supporting the sector in innovative ways. But without coordinated efforts to address digital poverty, these advancements could leave disadvantaged students further behind. This report emphasises the need for comprehensive AI training for teachers and students, alongside equitable access to technology. Tackling these challenges ensures Generative AI becomes a tool for empowerment, bridging gaps rather than widening them.”
The report also explores the risks associated with Generative AI, including societal biases reinforced by limited datasets, concerns over data privacy, and the potential over-reliance on AI at the expense of independent problem-solving skills. However, the findings highlight the significant opportunities these technologies present, particularly for learners with Special Educational Needs and Disabilities (SEND) and those for whom English is a second language. By enabling tailored learning experiences and reducing teacher workloads, Generative AI can create more time for face-to-face teaching, enhancing educational outcomes across the board.
The Rethinking Education with Generative AI report calls on policymakers, educators, and industry leaders to address these challenges directly. Key recommendations include:
- Clearly signposting the importance of Generative AI education to prepare young people for the workforce through public messaging and guidance.
- Incorporating responsible Generative AI use into the National Curriculum with unified, age-appropriate literacy skills aligned with UNESCO guidelines.
- Collaborating with experts, young people, teachers, and parents to shape effective guidance and policies.
- Reviewing assessment methods to ensure they remain relevant in light of Generative AI’s capabilities.
- Establishing a unified national approach to avoid inconsistent AI literacy and implementation across schools.
- Providing formal training for teachers on using Generative AI and recognising risks like deepfakes.
- Differentiating teaching about Generative AI from teaching with it, with clear policy support for both.
- Funding safe and secure Generative AI tools for schools and educating students on privacy implications.
- Ensuring equitable access by funding one-to-one devices for disadvantaged learners.
- Regularly reviewing guidance to keep pace with technological advancements and emerging needs.
The Digital Poverty Alliance invites all stakeholders to join this vital dialogue, working together to shape a future where AI-driven education is accessible, inclusive, and empowering for all.