AI-deas

OpRaise (opportunities and potential risks of AI in supporting evaluation) aims to transform higher education assessment by establishing an evidence-based framework for integrating AI into academic evaluation processes.

The AI for Cultural Heritage Hub (ArCH) will deploy the convening power of Cambridge’s distributed network of collections to create a secure workspace and Community of Practice to analyse cultural heritage data securely with AI tools.

The Womb to World project is seeking to develop cheaper, less invasive and more accurate AI-assisted tests that can be used throughout the conception to childhood journey. We want to improve the accuracy of early diagnosis of women’s health conditions, personalise fertility and IVF outcomes – and support the transition to parenting.

This project will use the latest advances in AI to better understand brain health and disease. It will explore the environmental, social and neurological factors at play, to develop responsible AI-driven tools that help clinicians predict, diagnose and treat brain diseases and mental health disorders.

This project aims to develop new AI methods to understand and address these challenges to improve equity and inclusion. It will develop new ways to support people with language and communication difficulties.

This project aims to investigate how local authorities in England are using AI to make decisions about issues such as placemaking, land use and mobility, and sustainable water supply systems to create public value

This work will provide up to date, relevant and robust information for researchers and decision-makers working on climate and biodiversity conservation – opening up the possibility for more targeted and effective solutions to some of our world’s most pressing climate and biodiversity challenges.