The WeatherPod AI Special, Episode 2: Trustworthy Artificial Intelligence

The WeatherPod
The WeatherPod
The WeatherPod AI Special, Episode 2: Trustworthy Artificial Intelligence

In this special AI Episode, hosts Alan Thorpe and David Rogers invite Amy McGovern into the studio to discuss the meaning of “trustworthy AI”.

Amy is Director of the National Science Foundation AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography – or AI2ES for short.

She’s also a Professor at Oklahoma University’s School of Computer Science and School of Meteorology.

Working under the University of Oklahoma’s leadership, AI2ES brings together researchers in AI, atmospheric science, ocean science, and risk communication. The thinking is that accelerated AI research in the environmental sciences can improve understanding of the rapid changes taking place in weather patterns, oceans, sea level rise, and disaster risk.

Amy’s research focuses on developing and applying machine learning and data mining methods for real-world applications, with a specific interest in high-impact weather.

Much of this work involves weather analytics or physical data science and she and her students are developing physics-based trustworthy AI methods as well as explainable AI. Their aim is to apply their work to high-impact weather phenomena, including tornadoes, hail, severe wind events, flooding, drought, and aircraft turbulence.

A key aim is to help build a diverse and flexible science, technology, engineering, and mathematics workforce. Amy’s thinking is that diversity will bring new ideas to the forefront, while flexibility is crucial to dealing with rapid changes in technology. To help this process, Amy and her team have developed outreach projects to encourage students to pursue STEM careers.

This work aside, Amy also directs the Interaction, Discovery, Exploration and Adaptation – or IDEA – Lab at Oklahoma University. The Lab’s focus is on developing and applying data science, AI and machine learning techniques for high-impact real-world applications.