AI and human embryos

This workshop brings together researchers in developmental biology, clinical medicine, humanities, social sciences and computing to explore the potential applications of artificial intelligence (AI) and machine learning (ML) to research and clinical practice involving human embryos. Sessions will explore the tools and methods that can be applied to fundamental, clinical and translational research, specific challenges in developmental biology and fertility treatment that may benefit from AI and ML solutions, and the wider legal, ethical and societal challenges for taking the technology forward safely and effectively.

This exploratory event aims to build connections across and beyond the University community to catalyse cross-disciplinary research collaborations and knowledge transfer. Brief case studies will reflect on learning and questions from existing projects, while presentations from ai@cam, Accelerate Science and Cambridge Reproduction will highlight the research infrastructure in Cambridge that can support new collaborations. The workshop will be highly participatory, and attendees are encouraged to share case studies and reflections from their own practice, as well as opportunities for collaboration and challenges they currently face. An optional Ideas Lab after lunch will enable participants to work in smaller groups to develop ideas for collaboration and funding applications.

 

Draft programme

09:30 Welcome 09:35 Introductions and icebreakers 09:50 Presentation from ai@cam 09:55 Session 1: AI in the embryo research lab 10:40 Presentation from C2D3 10:45 Coffee break 11:10 Presentation from Cambridge Reproduction 11:25 Session 2: AI in the fertility clinic 12:00 Presentation from Accelerate Science 12:05 Session 3: AI in a wider context 12:50 Wrap-up 13:00 Lunch 13:45 Optional ideas lab session 14:30 Close

If you are interested in attending this workshop, please email Christina Rozeik (coordinator@repro.cam.ac.uk). We welcome attendees from all disciplines, including those who do not yet have experience of human embryos, AI and/or machine learning in their research.

 

We are grateful for support from the School of Humanities and Social Sciences Research Framework Fund