AI for Science and Society
AI has the potential to transform the ways in which other scientific disciplines work and to deliver great societal benefits through a range of applications that can help tackle major challenges the world is facing today – from climate change and global health to ensuring the prosperity of nations in a shifting geopolitical and economic landscape.
In fundamental science and engineering disciplines, data-driven analysis, modelling, simulation, and prediction can be used to understand biological, physical, and natural processes, design new materials, design and engineer new artefacts, products, and services; here, AI is already being successfully applied in areas such as computational physics, biology, chemistry, and geoscience - accelerating discovery and enabling new research methods that help reduce the effort required to gather research data, run experiments, and test theories.
In the arts, humanities, and social sciences, we can use new AI technologies to explore documents, images, archives, but also to analyse human behaviour, from individuals to organisations and entire societies, and to create new forms of creative practice and artistic expression.
In the biomedical domain, AI has the potential to underpin new diagnostics, therapeutic methods, drug development and trialling methods, and to help understand the spread of diseases and optimise the provision of health and social care.
However, the application of AI techniques to these domains requires a deep understanding of each context of use, and close collaboration with experts in each respective field. At Edinburgh, we have made great strides at establishing research clusters, centres, and major projects with external partners that bring multidisciplinary teams to advance the use of AI in each of these domains, from health and finance to engineering, climate science, agriculture and the humanities.
Our vision for applied AI is based on nurturing these cross-disciplinary collaborations and developing new and innovative ways of doing research, driven by an ambition to solve challenges in each domain of application and ensuring AI research is deeply embedded in the context within which it will be used.
For this purpose, we have embarked on a long-term programme of growing awareness of AI techniques across all disciplines, supporting and growing existing interdisciplinary AI initiatives, and acting as champions for public and private investment in the applications of AI, which will require substantial support to realise their future potential over and above the effort that will be needed to push the boundaries of foundational AI and its technical innovations.
Another important ingredient of this vision is our focus on data, which acts as the “lingua franca” of applied AI research, and the University is unique in its commitment to creating, acquiring, and providing real-world data assets for research and innovation.
Our capability to engage in trusted data research, building on a wealth of experience in terms of information governance, cybersecurity, and data ethics expertise enables us to unlock research and innovation opportunities from ever-increasing opportunities to generate and utilise research data.
We expect that many future opportunities for applying AI to solve major scientific and societal challenges will be unlocked by combining data from different domains, e.g. health and climate or finance, but embed a responsible and ethical approach in all of our data-driven AI research to ensure it is safe and beneficial for society.