TY - GEN
T1 - Artificial Intelligence support to the paradigm shift from reactive to anticipatory action in humanitarian responses
AU - David, Walter
AU - King-Okoye, Michelle
AU - Garmendia-Doval, Beatriz
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - Climate change impact factors, drought, food insecurity, exacerbate existing vulnerabilities, with security implications as often they generate opportunities for insurgence and complicate peacebuilding efforts. Humanitarian anticipatory action is an innovative approach which systematically links early warnings to actions designed to provide protection ahead of a hazard. Leveraging authors’ experience in stabilization, this article investigates the role that artificial intelligence (AI) and modelling & simulation (M&S) can play to support early actions. As a proof of concept, the Expert.ai Cogito hybrid natural language processing and machine learning platform and the AI supported MASA SYNERGY system have been tested, to collect open sources information and to simulate the use case of deployment of unmanned aerial vehicles (UAVs), or drones, in a region affected by violence and natural disasters. Different prepositioning of cargo drones and resources can be tested and compared. In fact, a network of cargo drones set up in the optimal locations, ready to be deployed, can make a difference in establishing action plans and relief aid delivery.Scenario exercise and brainstorming have captured the value of AI and M&S to improve situational awareness and early actions prior to the onset of a shock. AI and M&S tools shows the ability to support decision making and anticipatory action by training crisis cells, verifying the impact of disaster, and testing contingency plans for significantly faster and more cost-effective responses, compared with the traditional reactive approach
AB - Climate change impact factors, drought, food insecurity, exacerbate existing vulnerabilities, with security implications as often they generate opportunities for insurgence and complicate peacebuilding efforts. Humanitarian anticipatory action is an innovative approach which systematically links early warnings to actions designed to provide protection ahead of a hazard. Leveraging authors’ experience in stabilization, this article investigates the role that artificial intelligence (AI) and modelling & simulation (M&S) can play to support early actions. As a proof of concept, the Expert.ai Cogito hybrid natural language processing and machine learning platform and the AI supported MASA SYNERGY system have been tested, to collect open sources information and to simulate the use case of deployment of unmanned aerial vehicles (UAVs), or drones, in a region affected by violence and natural disasters. Different prepositioning of cargo drones and resources can be tested and compared. In fact, a network of cargo drones set up in the optimal locations, ready to be deployed, can make a difference in establishing action plans and relief aid delivery.Scenario exercise and brainstorming have captured the value of AI and M&S to improve situational awareness and early actions prior to the onset of a shock. AI and M&S tools shows the ability to support decision making and anticipatory action by training crisis cells, verifying the impact of disaster, and testing contingency plans for significantly faster and more cost-effective responses, compared with the traditional reactive approach
KW - Artificial Intelligence
KW - simulation
KW - anticipatory action
U2 - 10.1007/978-3-031-31268-7_9
DO - 10.1007/978-3-031-31268-7_9
M3 - Conference contribution
SN - 9783031312670
T3 - Lecture Notes in Computer Science
SP - 145
EP - 162
BT - Modelling and Simulation for Autonomous Systems
A2 - Mazal, Jan
A2 - Fagiolini, Adriano
A2 - Vašík, Petr
A2 - Bruzzone, Agostino
A2 - Pickl, Stefan
A2 - Neumann, Vlastimil
A2 - Stodola, Petr
A2 - Lo Storto, Stefano
PB - Springer
ER -