Our University AI Principles
The University has created and shared seven principles on the use of AI in education.
The principles aim to shape an approach which ensures that all students are supported to develop the AI skills which they need to thrive at University and beyond.
- Critical human-centred AI literacy prepares students with the skills and qualities for life and work as graduates
Students should graduate with the ability to critically understand, evaluate and question AI within their discipline, and the skills to use AI appropriately. - Human academic judgement remains central
Teaching and assessment should develop and foreground academic and critical skills so that students can make responsible decisions about their academic work. Decisions about teaching, assessment and academic standards rest with academic staff and exam boards. - Pedagogic approaches should evolve in response to AI
Teaching and assessment should intentionally focus on the development of human judgement, creativity and critical thinking, recognising the changing role of AI in academic and professional practice. - Assessment approaches must evolve in response to AI to remain valid, fair and meaningful
The University will prioritise assessment approaches that continue to evidence intended learning outcomes in an AI-rich environment, recognising that this may require change rather than preservation of existing practices. - Equity, accessibility and inclusion matter
AI-related approaches should not advantage some students over others, nor rely on hidden assumptions about access, confidence, prior experience or ethical positioning in relation to AI use. - Experimentation is expected and supported
Staff and students should feel able to explore and trial new approaches, with proportionate support and risk awareness. - Transparency and academic integrity are shared responsibilities
Expectations around AI use should be clear to staff and students, and integrity should be supported primarily through assessment design and education.