Improving society’s long-term sustainability with respect to limited environmental resources while ensuring health and safety is a “wicked problem,” a term coined to describe complex real-world challenges that have severe societal consequences, cannot be studied by trial and error, and do not have clear-cut solutions. Addressing this wicked problem effectively will require new artificial intelligence (AI) methods for knowledge discovery and prediction driven by convergent collaborations across multiple sectors involved in research and enterprise.
Collaborating to Tap AI’s Potential
Currently, less than 5% of available environmental observational data are used in numerical models of Earth systems. Better models that leverage additional data are essential to improving our understanding of and ability to predict atmospheric and oceanic phenomena and their impacts, as well as to assist individuals, businesses, and governments in making better decisions to reduce harm to people, livelihoods, ecosystems, and economies.
AI has demonstrated value throughout the observing, predicting, and impact modeling process, from preprocessing to postprocessing and improving forecasts. And with recent computational hardware innovations like graphics processing units (GPUs) and tensor processing units, as well as innovations in AI methods themselves, AI is poised to help us harness the power of the big-data frontier by exploiting untapped environmental observations and enhancing Earth system modeling in cost-effective ways.