Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems

John  Ainsworth; Claudio Angione; Kate  Ardern; Katie  Atkinson; Samuel  Ball; Ben Barr; Ben  Bridgewater; Iain E. Buchan; Camila  Caiado; Helen  Cole; Hannah Davies; Nigel  Davies; Hedley C.A.  Emsley; Alejandro F. Frangi; Marta  Garcìa-Fiñana; Hilary  Garrett; Carole Goble; Mike  Harding; Iain  Hennessey; Matt   Hennessey; Warren  Heppolette; Andrew  Hill; Thomas  House; Jim  Hughes; Owen   Johnson; Dan Joyce; Axel  Kaehne; Louise C. Kenny; Jo  Knight; Chris  Kypridemos; Tom  Lawton; Gary  Leeming; Jims  Marchang; Anthony   Marson; Glen  Martin; Simon  Maskell; Mark  Mon-Williams; Georgina  Moulton; Annemarie  Naylor; Farnaz  Nickpour; P-J  Noble; Boguslaw  Obara; Annalisa Occhipinti; Kay  O’Halloran; Séamus  O’Neill; Reema  Patel; Munir  Pirmohamed; Roberta Piroddi; Rowan  Pritchard Jones; Alan  Radford; Emily  Rempel; Sarah  Rodgers; Malcolm G. Semple; Sally   Sheard; Alex  Singleton; Matthew  Sperrin; Tjeerd  van Staa; Rob  Tabb; Lauren E. Walker; Paul Watson; Phil   Waywell; Becca  Wilson; John Wright; Xingna  Zhang

Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems

John Ainsworth
, Claudio Angione
, Kate Ardern
, Katie Atkinson
, Samuel Ball
, Ben Barr
, Ben Bridgewater
, Iain E. Buchan (Editor)
, Camila Caiado
, Helen Cole
, Hannah Davies
, Nigel Davies
, Hedley C.A. Emsley
, Alejandro F. Frangi
, Marta Garcìa-Fiñana
, Hilary Garrett
, Carole Goble
, Mike Harding
, Iain Hennessey
, Matt Hennessey

Warren Heppolette , Andrew Hill , Thomas House , Jim Hughes , Owen Johnson, Dan Joyce , Axel Kaehne , Louise C. Kenny , Jo Knight , Chris Kypridemos , Tom Lawton , Gary Leeming , Jims Marchang , Anthony Marson, Glen Martin , Simon Maskell , Mark Mon-Williams , Georgina Moulton , Annemarie Naylor , Farnaz Nickpour , P-J Noble , Boguslaw Obara , Annalisa Occhipinti, Kay O’Halloran , Séamus O’Neill , Reema Patel , Munir Pirmohamed , Roberta Piroddi , Rowan Pritchard Jones, Alan Radford , Emily Rempel , Sarah Rodgers , Malcolm G. Semple, Sally Sheard, Alex Singleton , Matthew Sperrin , Tjeerd van Staa , Rob Tabb , Lauren E. Walker , Paul Watson, Phil Waywell, Becca Wilson , John Wright, Xingna Zhang

Research output: Book/Report › Other report

Abstract

This paper sets out an opportunity for the UK to develop a world-leading infrastructure for data-driven public service innovation that feeds, and is fed by, science and engineering at national and civic scales, sustainably and with public trust.
The disruptive model is a national grid of civic learning systems where public services continuously improve their value and productivity with artificial intelligence (AI) assistance at population, provider and person levels, as shown in Figure 1. 6 In this civic AI model, data is foundational–collected, analysed, and acted upon in learning loops to continuously improve service delivery and outcomes.

Original language	English
Place of Publication	Online
Publisher	Northern Health Science Alliance
Number of pages	13
Publication status	Published - 24 Jan 2025

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https://www.thenhsa.co.uk/app/uploads/2025/03/National-Grid-of-Civic-Learning-Systems-NHSA-and-partners.pdfLicence: Unspecified

Cite this

Ainsworth, J., Angione, C., Ardern, K., Atkinson , K., Ball , S., Barr, B., Bridgewater , B., Buchan , I. E. (Ed.), Caiado , C., Cole , H., Davies, H., Davies , N., Emsley , H. C. A., Frangi , A. F., Garcìa-Fiñana , M., Garrett , H., Goble, C., Harding , M., Hennessey , I., ... Zhang, X. (2025). Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems. Northern Health Science Alliance. https://www.thenhsa.co.uk/app/uploads/2025/03/National-Grid-of-Civic-Learning-Systems-NHSA-and-partners.pdf

@book{0d7262b5eabb426a834e299ca407348b,

title = "Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems",

abstract = "This paper sets out an opportunity for the UK to develop a world-leading infrastructure for data-driven public service innovation that feeds, and is fed by, science and engineering at national and civic scales, sustainably and with public trust. The disruptive model is a national grid of civic learning systems where public services continuously improve their value and productivity with artificial intelligence (AI) assistance at population, provider and person levels, as shown in Figure 1. 6 In this civic AI model, data is foundational{\textendash}collected, analysed, and acted upon in learning loops to continuously improve service delivery and outcomes.",

author = "John Ainsworth and Claudio Angione and Kate Ardern and Katie Atkinson and Samuel Ball and Ben Barr and Ben Bridgewater and Camila Caiado and Helen Cole and Hannah Davies and Nigel Davies and Emsley, \{Hedley C.A.\} and Frangi, \{Alejandro F.\} and Marta Garc{\`i}a-Fi{\~n}ana and Hilary Garrett and Carole Goble and Mike Harding and Iain Hennessey and Matt Hennessey and Warren Heppolette and Andrew Hill and Thomas House and Jim Hughes and Owen Johnson and Dan Joyce and Axel Kaehne and Kenny, \{Louise C.\} and Jo Knight and Chris Kypridemos and Tom Lawton and Gary Leeming and Jims Marchang and Anthony Marson and Glen Martin and Simon Maskell and Mark Mon-Williams and Georgina Moulton and Annemarie Naylor and Farnaz Nickpour and P-J Noble and Boguslaw Obara and Annalisa Occhipinti and Kay O{\textquoteright}Halloran and S{\'e}amus O{\textquoteright}Neill and Reema Patel and Munir Pirmohamed and Roberta Piroddi and \{Pritchard Jones\}, Rowan and Alan Radford and Emily Rempel and Sarah Rodgers and Semple, \{Malcolm G.\} and Sally Sheard and Alex Singleton and Matthew Sperrin and \{van Staa\}, Tjeerd and Rob Tabb and Walker, \{Lauren E.\} and Paul Watson and Phil Waywell and Becca Wilson and John Wright and Xingna Zhang",

editor = "Buchan, \{Iain E.\}",

year = "2025",

month = jan,

day = "24",

language = "English",

publisher = "Northern Health Science Alliance",

}

Ainsworth, J, Angione, C, Ardern, K, Atkinson , K, Ball , S, Barr, B, Bridgewater , B, Buchan , IE (ed.), Caiado , C, Cole , H, Davies, H, Davies , N, Emsley , HCA, Frangi , AF, Garcìa-Fiñana , M, Garrett , H, Goble, C, Harding , M, Hennessey , I, Hennessey, M, Heppolette , W, Hill , A, House , T, Hughes , J, Johnson, O, Joyce , D, Kaehne , A, Kenny , LC, Knight , J, Kypridemos , C, Lawton , T, Leeming , G, Marchang , J, Marson, A, Martin , G, Maskell , S, Mon-Williams , M, Moulton , G, Naylor , A, Nickpour , F, Noble , P-J, Obara , B, Occhipinti, A, O’Halloran , K, O’Neill , S, Patel , R, Pirmohamed , M, Piroddi , R, Pritchard Jones, R, Radford , A, Rempel , E, Rodgers , S, Semple, MG, Sheard, S, Singleton , A, Sperrin , M, van Staa , T, Tabb , R, Walker , LE, Watson, P, Waywell, P, Wilson , B, Wright, J & Zhang, X 2025, Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems. Northern Health Science Alliance, Online. <https://www.thenhsa.co.uk/app/uploads/2025/03/National-Grid-of-Civic-Learning-Systems-NHSA-and-partners.pdf>

TY - BOOK

T1 - Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems

AU - Ainsworth, John

AU - Angione, Claudio

AU - Ardern, Kate

AU - Atkinson , Katie

AU - Ball , Samuel

AU - Barr, Ben

AU - Bridgewater , Ben

AU - Caiado , Camila

AU - Cole , Helen

AU - Davies, Hannah

AU - Davies , Nigel

AU - Emsley , Hedley C.A.

AU - Frangi , Alejandro F.

AU - Garcìa-Fiñana , Marta

AU - Garrett , Hilary

AU - Goble, Carole

AU - Harding , Mike

AU - Hennessey , Iain

AU - Hennessey, Matt

AU - Heppolette , Warren

AU - Hill , Andrew

AU - House , Thomas

AU - Hughes , Jim

AU - Johnson, Owen

AU - Joyce , Dan

AU - Kaehne , Axel

AU - Kenny , Louise C.

AU - Knight , Jo

AU - Kypridemos , Chris

AU - Lawton , Tom

AU - Leeming , Gary

AU - Marchang , Jims

AU - Marson, Anthony

AU - Martin , Glen

AU - Maskell , Simon

AU - Mon-Williams , Mark

AU - Moulton , Georgina

AU - Naylor , Annemarie

AU - Nickpour , Farnaz

AU - Noble , P-J

AU - Obara , Boguslaw

AU - Occhipinti, Annalisa

AU - O’Halloran , Kay

AU - O’Neill , Séamus

AU - Patel , Reema

AU - Pirmohamed , Munir

AU - Piroddi , Roberta

AU - Pritchard Jones, Rowan

AU - Radford , Alan

AU - Rempel , Emily

AU - Rodgers , Sarah

AU - Semple, Malcolm G.

AU - Sheard, Sally

AU - Singleton , Alex

AU - Sperrin , Matthew

AU - van Staa , Tjeerd

AU - Tabb , Rob

AU - Walker , Lauren E.

AU - Watson, Paul

AU - Waywell, Phil

AU - Wilson , Becca

AU - Wright, John

AU - Zhang, Xingna

A2 - Buchan , Iain E.

PY - 2025/1/24

Y1 - 2025/1/24

N2 - This paper sets out an opportunity for the UK to develop a world-leading infrastructure for data-driven public service innovation that feeds, and is fed by, science and engineering at national and civic scales, sustainably and with public trust. The disruptive model is a national grid of civic learning systems where public services continuously improve their value and productivity with artificial intelligence (AI) assistance at population, provider and person levels, as shown in Figure 1. 6 In this civic AI model, data is foundational–collected, analysed, and acted upon in learning loops to continuously improve service delivery and outcomes.

AB - This paper sets out an opportunity for the UK to develop a world-leading infrastructure for data-driven public service innovation that feeds, and is fed by, science and engineering at national and civic scales, sustainably and with public trust. The disruptive model is a national grid of civic learning systems where public services continuously improve their value and productivity with artificial intelligence (AI) assistance at population, provider and person levels, as shown in Figure 1. 6 In this civic AI model, data is foundational–collected, analysed, and acted upon in learning loops to continuously improve service delivery and outcomes.

M3 - Other report

BT - Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems

PB - Northern Health Science Alliance

CY - Online

ER -

Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems

Abstract

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