Campbell Watson, a key figure at IBM Research, is pioneering the integration of artificial intelligence (AI) in Earth sciences, with a focus on climate modeling and environmental impact reporting. Watson’s career trajectory shifted dramatically from accounting to atmospheric science, driven by a passion for understanding the Earth system. Today, his work includes advanced atmospheric modeling, which is critical to understanding climate change dynamics, according to IBM Research.
From accounting to atmospheric science
Originally an accountant, Watson’s dissatisfaction with his job led him to return to academia and study atmospheric science. His interest in Earth systems was partly inspired by his love of surfing, which he learned as a child in Melbourne, Australia. This hobby remained a constant throughout his life, influencing his academic and professional pursuits.
AI and geospatial modeling
At IBM Research, Watson leads a team working with NASA to develop geospatial models for climate change and weather prediction. These models are essential for environmental and social governance (ESG) reporting and help companies track and report their environmental impacts, including greenhouse gas emissions.
The Watson team uses large language models (LLMs) to improve ESG reporting. They improve these models to handle specific language and abbreviations widely used in sustainability reporting, with the goal of improving the efficiency and accuracy of environmental data processing.
AI Challenges and Innovation
One of the key challenges facing the Watson team is training AI models to effectively interpret tabular data. This is work that is generally not suitable for an established LLM. They are working on model alignment to improve AI’s understanding of the complex data relationships critical to accurate environmental reporting.
Working with NASA, the Watson team developed Prithvi WxC, a universal AI model for weather and climate that leverages data from a variety of satellites. This model represents a significant advance in geospatial data analysis and provides insights that can benefit multiple scientific domains.
Leadership and future direction
As a lab leader, Watson focuses on ensuring projects are scalable and impactful. He emphasizes the importance of translating research findings into practical applications that benefit partners and communities. Watson’s leadership style has developed through experiences both within and outside of professional work, including unique projects such as live coding performances that combine art and science.
Watson’s work demonstrates the potential of AI in solving global sustainability challenges. He aims to leverage cutting-edge technologies to advance our understanding of the Earth’s climate system and pave the way for more informed environmental decisions.
Image source: Shutterstock