Displaying items by tag: va tech college of engineering
Researchers use environmental justice questions to reveal geographic biases in ChatGPT
A U.S. map shows counties where residents could (blue) or could not (pink) receive local-specific information about environmental justice issues. Photo courtesy of Junghwan Kim via Virginia Tech.
Key findings indicate limitations of AI, suggest improvements
David Fleming is a communications specialist at Virginia Tech.
BLACKSBURG — Virginia Tech researchers have discovered limitations in ChatGPT’s capacity to provide location-specific information about environmental justice issues. Their findings, published in the journal Telematics and Informatics, suggest the potential for geographic biases existing in current generative artificial intelligence (AI) models.
ChatGPT is a large-language model developed by OpenAI Inc., an artificial intelligence research organization. ChatGPT is designed to understand questions and generate text responses based on requests from users. The technology has a wide range of applications from content creation and information gathering to data analysis and language translation.
A county-by-county overview
“As a geographer and geospatial data scientist, generative AI is a tool with powerful potential,” said Assistant Professor Junghwan Kim of the College of Natural Resources and Environment. “At the same time, we need to investigate the limitations of the technology to ensure that future developers recognize the possibilities of biases. That was the driving motivation of this research.”
Utilizing a list of the 3,108 counties in the contiguous United States, the research group asked the ChatGPT interface to answer a prompt asking about the environmental justice issues in each county. The researchers selected environmental justice as a topic to expand the range of questions typically used to test the performance of generative AI tools. Asking questions by county allowed the researchers to measure ChatGPT responses against sociodemographic considerations such as population density and median household income.