Guidance for generative AI in education and research
This UNESCO guidance provides a comprehensive framework for governments, educational institutions, teachers, and learners on the ethical, safe, and equitable use of generative artificial intelligence in education and research. It outlines the foundational technologies of generative AI, highlights key ethical controversies such as data privacy and copyright infringement, and proposes regulatory measures including age limits and risk assessments. Furthermore, it offers actionable strategies for co-designing educational applications that protect human agency and promote inclusion.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Policy-makers, educational authorities, institutional leaders, teachers, and researchers seeking guidance on integrating and regulating generative AI in education.
What the document contains
The document addresses the technological mechanics of generative AI, ethical controversies surrounding its use, regulatory steps for governments, policy frameworks for education and research, and co-design approaches for teaching, learning, and research applications.
Specific legally binding domestic legislation for individual member states and pre-packaged software code implementations are not provided.
- Generative AI tools are rapidly developing and outpacing national regulatory frameworks, creating urgent challenges for educational institutions.
- A human-centred approach is essential to ensure that AI enhances human agency, inclusion, equity, and cultural diversity rather than replacing human intelligence.
- Governments must implement regulatory safeguards, including data protection laws, age limits for usage, and mandatory labelling of AI-generated content.
- Educational institutions need to audit and validate generative AI tools for pedagogical appropriateness and ethical compliance before adoption.
- Teachers and researchers must be supported through training and capacity-building to critically evaluate AI outputs and use tools responsibly.
· Foreword · Acknowledgements · List of acronyms and abbreviations · Introduction · 1. What is generative AI and how does it work? · 2. Controversies around generative AI and their implications for education · 3. Regulating the use of generative AI in education · 4. Towards a policy framework for the use of generative AI in education and research · 5. Facilitating creative use of GenAI in education and research · 6. GenAI and the future of education and research · Concluding remarks · References
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
GenAI providers should be held responsible for ensuring adherence to core values and lawful purposes, respecting intellectual property, and upholding ethical practices
3.3.2. Providers of GenAI tools
screening score · 2026-10-24
Fairness
4/5Non-discrimination and equitable treatment
Develop criteria for the validation of GenAI systems to ensure that there is no gender bias, discrimination against marginalized groups, or hate speech embedded in data or algorithms.
4.1 Promote inclusion, equity, and linguistic and cultural diversity
screening score · 2026-10-24
Human Dignity
5/5Respect for the inherent worth of persons
Building on UNESCO’s 2021 Recommendation on the Ethics of Artificial Intelligence, the guidance is anchored in a humanistic approach to education that promotes human agency, inclusion, equity, gender equality, and cultural and linguistic diversity
Foreword
screening score · 2026-10-24
Privacy
4/5Protection of personal data and private life
Mandate the drafting and implementation of laws for the protection of users’ personal information and identify and combat unlawful data storage, profiling and sharing.
3.3.1. Governmental regulatory agencies
screening score · 2026-10-24
Enforcement
4/5Consequences and compliance mechanisms with real force
Classify them into strict regulations (i.e. banning AI-enabled applications or systems with unacceptable risks), special regulations for high-risk applications, and general regulations on applications that are not listed as high risk.
3.3.1. Governmental regulatory agencies
screening score · 2026-10-24