Climate, Security and Migration: Using Advanced Distributed AI Models

Discussing opportunities and challenges of using artificial intelligence technologies in the policy decision-making process

The Paris Agreement is a milestone, and all parties should take concrete actions to fulfill their commitments. Institutions and processes must be adapted for tomorrow's changes and equipped to take up all the challenges of climate change. There is a shared responsibility to prepare for climate impacts on security and migration. By 2030, more than 60% of the world's poor will live in fragile and crisis contexts. Assessing and anticipating climate risks in the most fragile situations should be a priority.

There is an urgent need for scientific knowledge and tools to provide the necessary information to enable us to move beyond reactive postures and develop proactive strategies. Can we forecast security challenges within specific geographical regions? Can we anticipate future migration flows? Can we further develop early warning systems that will aid in humanitarian preparation?

This conference will give insight into challenges and opportunities regarding the growing impact of climate change on cultural conflict, and describe new tools designed to enhance existing early warning systems, identify changes in natural processes such as droughts and floods, and anticipate potential impacts on socio-economic stability.

The speakers will include representatives from the UN and the European Commission, as well as experts on computer modeling working on preventive social simulation technology. Additionally, leaders of a global consortium of scholars and research centres using distributed artificial intelligence technologies to develop computational models that can simulate the social (as well as the physical) effects of climate change, and produce policy-relevant insights to guide decision-making about the use of resources to proactively promote peace, will give insight on the climate-peace-war nexus. 

More information and registration.