From climate science and water sustainability to urban resilience and disaster preparedness, Artificial Intelligence has shown significant potential to inform and enable transformative action in the areas of climate, sustainability, and the environment.
For example, machine learning, graph analytics, agent-based models, and human-AI systems have shown potential with predictive understanding in earth systems science and engineering and enabled new insights in sustainability and resilience of critical functions and infrastructures.
In order to affect real change in climate, sustainability, and the environment, remotely sensed data as well as massive computer models may need to be run and the simulations archived in federal government research organizations. Furthermore, public sector organizations and local governments need to be involved as stakeholders, beneficiaries, and decision makers.
With Northeastern University’s roots in experiential learning and interdisciplinary research, the Institute for Experiential AI is well-positioned to collaborate across industry, government, and academia.