Understanding the mechanics that cause conflict and identifying multi-scale population areas that are at risk of conflict
The defence and security sector is increasingly facing a myriad of trans-national and trans-genre conflicts on a global scale, where the patterns in violence and underlying relationships are shifting rapidly. The directly- and indirectly-related data concerning these conflicts is overwhelming. By utilising network theory this project aims to leverage this data into identifying multi-scale population areas that are at risk of conflict.
Explaining the science
Conflict, or the threat of it, is often caused by contentious interactions between groups. This project’s research utilises the latest developments in complex networks and spatial interaction theory by Sir Alan Wilson to model the effect of multiplexed regional-global interactions.
Of immediate interest to defence and security operations is the ability to automate the identification of future conflict areas (from a region to within a city) for high fidelity analysis and policy/action advice. Of long-term interest is the ability to understand the dominant interaction forces that give rise to conflict.
This work will complement existing defence and security intelligent data systems to:
- Automate identification of future conflict areas to improve consistency and reduce expenditure
- Improve understanding of causal mechanisms by quantifying interaction effects
- Transform network theory into military actionable tasks.
This work has potential for application across a wide range of defence and security contexts in forecasting conflict and determining their geographic relations.
BBC video interview with Dr Weisi Guo, ‘How AI could unlock world peace’
The piece details existing research being conducted into the forecasting of conflict, including this project. The piece identifies three things that will improve conflict forecasting: new machine-learning techniques; more information about the wider causes of conflicts and their resolution; and theoretical models that better reflect the complexity of social interactions and human decision-making. The piece goes on to propose that an international consortium be set up to develop formal methods to model the steps society takes to wage war.
BBC article with Dr Weisi Guo, ‘Can mapping conflict data explain, predict and prevent violence?’.
Dr Weisi Guo – Honorary Professor at University of Warwick & Professor of Human Machine Intelligence at Cranfield University
Sir Alan Wilson – Director, Special Projects
Researchers and collaborators
Gerardo Aquino – Research Associate
Dr Jim Madge – Senior Research Software Engineer
Source: Alan Turing Institute