Strategic Priorities Fund - AI for Science, Engineering, Health and Government

Lead Research Organisation: The Alan Turing Institute
Department Name: Research

Abstract

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Planned Impact

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Publications

10 25 50
 
Description There are four principal research domains for the AI for Science and Government (ASG) programme - digital twins, health, the criminal justice system, and AI for Science. Its main achievements are (1) the development of ML and other data analytic methods for greater efficiency across government, scientific practice and industry; (2) creating a diverse set of research collaborations including non-academic - examples of which are provided below. ASG's third (3) overarching achievement is that its research activities have secured over £19m in additional funding.

Digital twins - Urban digital twins have produced two main computer suites - QUANT and SPENSER - which provide a national capability for the deployment urban analytics in planning which enable exploration of a variety of future scenarios using state-of-the-art modelling and simulation capabilities at cost in a cutting edge, secure environment. Complex Systems Engineering has produced original digital twin systems for the advancement of 'smarter' engineering products of value to government, scientists and industry. Examples of achievements and innovative collaborations include developing with Proctor & Gamble multi-phase flow systems in oil, gas and rapid consumer goods distribution; digital twinning for predicting wind response in bridges (in collaboration with Highways England); and creating digital twins for safe building construction (collaboration with University of Tokyo).

Health - Aims include to deploy AI and data science as the foundations for precision medicine which improve patient outcomes and lower costs. Considerable progress has been made, collaborating with HDR UK, with clinicians, and building on previous research for the Cystic Fibrosis Trust, in extending into dementia, cardiology and breast cancer. For instance, the collaboration with NHS Scotland to develop the SPARRA v4 tool has created state-of-the-art machine learning algorithms and extensive feature engineering which improve predictive performance, whilst ensuring reproducibility and scalability of the entire analytical workflow by pre-empting thousands of avoidable admissions by targeting the highest risk patients with fewer patients than under SPARRAv3. The project also achieves knowledge transfer by workshops that train NHS ISD staff in modern ML methods.
Criminal Justice System. Research has focused on the application of AI and data science in the system's various agencies, including the police, with achievements recorded in modern slavery (applying ML to track demand to help meet the UN Sustainable Development Goal 8.7) and models for predicting police demand and supply in collaboration with Durham Constabulary.

AI for Science. Through collaborations with UK research councils, projects have produced important methods for the rapid analysis of, for example, 3-D images from cryo-electron microscopes. The ability to process data at speed and scale is opening new research questions and the possibilities of new science. Alongside scientific tools and methods, individual projects have scientific achievements in specific fields such as environmental sciences' effort to monitor despite different scales and quality of data for monitoring break-up of icebergs, seal populations or deforestation.
Exploitation Route The uses of the urban models that are part of digital twins are being discussed with the Ministry of Housing, Communities and Local Government with a view to being made available nationally. In Health, the algorithms for AI-led medical diagnosis and prognosis are being used by the clinicians of the Cystic Fibrosis Trust. The projects in complex systems engineering are being carried out jointly with such industrial partners as Rolls Royce, Proctor & Gamble, Highways England. A project on the deployment of police resources is being carried out with the West Midlands Police and there are further collaborations with the Metropolitan Police. AI for Science projects are all collaborative with other research councils and their institutes, for example. The projects are all designed by discipline-specific scientists to develop tools and advanced methods that will enable their scientific field to achieve greater outputs; and each project has a challenge through which these AI techniques are developed. Consequently, the outcomes help scientific disciplines and the application community. For example, in developing AI tools for integrating big data across different disciplines, working with WWF, the tools for aggregating different kinds of data, in this case text-based planning applications and visual images of drawings also in applications for planning, the project will have value for conservation scientists and local government planning offices. Similarly, project work that develops tools for combining satellite and social data (partnering with ONS) is of immediate use to those who contributed to the case study which focuses on the impact of tree planting schemes in East Africa, but of course will have use ultimately for a larger range of environmental scientists and government planners around the work who will have access to the results of this research.
Sectors Aerospace, Defence and Marine,Chemicals,Communities and Social Services/Policy,Construction,Digital/Communication/Information Technologies (including Software),Energy,Environment,Healthcare,Government, Democracy and Justice,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology,Transport

URL https://www.turing.ac.uk/research/asg
 
Description The findings are being deployed in central and local government, industry and science research institutes. The data from individual projects provides a full inventory. However, to summarise examples of impact on non-academic audiences in government, law enforcement and industry are below to illustrate the range of audiences benefiting from ASG research. They indicate how the research output is shaping the practices of many practitioners who benefit from understanding what AI can facilitate in their work in very concrete ways. It also indicates the ongoing relationships that are being developed through this public engagement. Government: the National Infrastructure Commission invited the researchers producing Digital Twin SPENSER and other components to provide evidence on transport capacity for UK cities for the National Infrastructure Assessment (NIA), published in July 2018. The NIA makes recommendations for how the infrastructure needs and priorities of the country should be addressed. Government are required to formally respond to the recommendations made in the NIA. The evidence led to the assertion in the NIA that transport networks are close to capacity in many UK cities and the recommendation that investing in urban transport can support productivity and quality of life. Impact from this work is a direct contribution to the shaping of future infrastructure priorities. In all cases, the application of these research methods is instrumental in developing capabilities in user organisations. These partnerships are the basis of new research networks with this ASG supplying methods and analytics and partners offering data and new research challenges. Law enforcement: the modelling police supply and demand PI was invited to present to the UK Home Office on 'Policing and Crime Data Analytics'. The presentation provided a summary of ongoing data science & policing projects to the UK Home Office crime analysis group. Around 20 people attended in person, with additional staff dialling in to view the presentation remotely. As a result of this activity, the Home Office plans to send analysts to visit the University of Leeds to discuss these projects in further detail and identify areas for future collaboration. Industry: Digital twins in aeronautics researchers presented their work at the Effective Quadratures Data-Centric Engineering Workshop at Rolls-Royce, Bristol. Twenty engineers from the Rolls-Royce plc attended an Effective Quadratures (see www.effective-quadratures.org) Data-Centric Engineering workshop. This event was held at Rolls-Royce in Bristol. The objective of this workshop was to show case the latest methods in our open-source code Effective Quadratures and get their feedback. Their feedback indicated that it was useful in enabling Rolls Royce engineers to apply tools to their own engineering applications and to understand in detail where the current state of the 'art' of digital twinning and the emerging interdisciplinary field of data-centric engineering is.
First Year Of Impact 2019
Sector Aerospace, Defence and Marine,Chemicals,Communities and Social Services/Policy,Construction,Digital/Communication/Information Technologies (including Software),Energy,Environment,Healthcare,Government, Democracy and Justice,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology,Transport
Impact Types Societal,Policy & public services