Supporting a sustainable future with AI research
The use of AI can advance human flourishing, but only if these risks are well-managed. We aim to position ARU as a leader in higher education, advocating for the safe, sustainable and ethical use of AI.
Projects
New perspectives on AI in higher education
Researchers: Dr Zareen Bharucha, Deepthi Bathini, Prof Sally Fowler Davis, Dr Philippa Calver, Dr Lakshmi Babu Saheer, Kate Baker, Dr Rhyddhi Chakraborty, Simon Chubb, Dr Ami Crowther, Jolene Cushion, Matt Flesher, John Gibson, Maryla Hart, Dr Lara Houston, Dr Stefano Magariello, Dr Victoria Rajpaul-Maguire, Annabelle Michael, Harry Orchard, Dr Sarah Royston, Dr Sebastian Smart, Dr Sarah Gradidge
Impacts on learning
In simple terms: AI-assisted learning is not always effective. Research shows it can limit students’ creativity and critical thinking, so we need to mitigate this.
Outcome: Greater focus on teaching approaches that help students use AI appropriately while maintaining their own cognitive development.
AI’s societal footprint
In simple terms: AI tools are known to replicate bias and (particularly racial and gender) stereotypes embedded within their training data, so we need to address this.
Outcome: Greater emphasis on fairness and inclusive design in AI tools and datasets and transparency about their limitations.
AI research and development
In simple terms: Researchers have identified signs of deception, self-preservation and automated replication among advanced AI models, so we need to guard against this.
Outcome: Stronger oversight and ethical frameworks guiding the development of advanced AI systems.
AI's environmental footprint
In simple terms: AI systems have hidden energy use, resource demands (including water) and carbon cost, and we need to explore these, along with the challenges that AI poses to ARU’s commitment to reach net zero emissions by 2045.
Outcome: Better public understanding and stronger sustainability policy around emerging technologies, and updates to ARU’s operational plan.
Climate behaviour research
In simple terms: It's important to understand how emotions such as fear, hope or dread shape public support for climate policies, creating datasets suitable
for AI modelling.
Outcome: Better prediction tools for designing effective, socially supported climate strategy.
ARU Arm AI Lab – building future AI infrastructure and innovation
Researchers: Dr Oliver Faust, Prof Marcian Cirstea
In simple terms: We require energy-efficient, Arm-based computing for researchers developing safe ‘green AI’ applications at both the edge and in the cloud, while offering a shared platform where academics, students and external partners can build innovative AI solutions.
Outcome: More sustainable AI development, stronger environmental modelling capability, and an enhanced role for ARU within the Cambridge AI ecosystem through a high value strategic partnership that strengthens ARU’s innovation, research profile and commercial impact.
Find out more about our Arm AI Lab, which opened in March 2026.