Machine learning and artificial intelligence are extremely popular topics in today’s social circles. Thanks to a grant from the Data Institute of Societal Challenges (DISC) at the University of Oklahoma, Heather Bedle, Ph.D., assistant professor in the School of Geoscience, Mewbourne College of Earth and Energy, along with Chris Garneau, Ph.D., assistant professor of sociology and Martin Piotrowski, Ph.D., associate professor of sociology in the Dodge Family College of Arts and Sciences, will lead a Community of Practice to explore how machine learning and artificial intelligence can be used in conjunction with traditional statistical data analysis for social and natural sciences.
“I use a lot of machine learning and artificial intelligence in geophysics and geosciences,” Bedle said. “Recently, I’ve starting taking explainable AI methods, which I've calibrated to peer into social survey data, to try to understand the black box of the human mind. That’s why I wanted to start a Community of Practice to allow collaboration between social scientists and natural scientists.”
By using machine learning and artificial intelligence, Bedle’s team will be able to dive deep into massive datasets to discover the hidden patterns that human researchers have a difficult time finding.
“Let’s say you have a survey with 100 questions given to 2,000 people - that's 200,000 data points spread across a multitude of dimensions,” Bedle said. “Machine learning helps us find clusters and patterns in these massive datasets by analyzing the data in ways that human researchers can’t effectively do.”
The team plans to have their first event, a mixer, in the fall. The team will invite interested researchers, whether new to data science or more experienced, to present their data sets and the problems they want to solve with them to the group to begin the formation of working groups.
“Our idea is to form interdisciplinary working groups that could merge the social and natural sciences to leverage big data to solve problems. If we can pair together scientists who have data with those who can analyze data with coding and programming, then this will be a success,” Bedle said.
Learn more about DISC’s Communities of Practice.
