Using behavioural data to understanding community well-being - An AI approach

  • Harris, Lasana (PI)
  • Woodcraft, Saffron (CoI)
  • Lu, Saite (CoI)

Project Details


This project explores whether government agencies can use behavioural data--administrative and other data that records the activities and acts of community members--to gain additional insight into place-based community well-being. Closed-circuit television feeds, parking charges, noise complaints; these are a sample of the rich data sources government agencies can leverage to better understand community wellbeing and respond to challenges and gauge the resiliency in the face of increasing global challenges. The project focusses on two major strands:
(1) a demonstration of the utility of using already collected administrative data from two local councils in London to better understand community well-being, and;
(b) the creation of a network of stakeholders interested in using behavioural data to understand communities.

Currently, there are many indices of community well-being, but they all rely on self-report survey data or economic measures. Our novel approach focusses on behavioural data to fill gaps in understanding community well-being; it is not the creation of yet another index. Behavioural data is currently widely used in the private sector to understand consumer behaviour. Given the budget reduction faced by many government agencies and the large cost of collecting data, our approach represents a cost-effective way to leverage a valuable public resource that currently sits on government servers. Finally, this project will actively explore the ethical concerns surrounding behaviour data use by convening a sub-group on the ethics of behavioural data use. This sub-group will craft guidelines and best practice standards to guide both our research and behavioural data use by government in the future.

The project received £120K
Funder: British Academy and Nuffield Foundation
Collaboration with University College London and University of Cambridge
Short titleAI for community behaviour modelling
Effective start/end date1/04/2231/12/24

Collaborative partners

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 11 - Sustainable Cities and Communities


  • behaviour AI
  • community well-being

Research Centres

  • Data and Complex Systems Research Centre


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