As artificial intelligence (AI) becomes increasingly integrated into our daily lives, the next significant challenges involve ensuring effective collaboration between AI systems and human users and fostering trust in this technology, say computer scientists William Yeoh and Stylianos Vasileiou at the McKelvey School of Engineering at Washington University in St. Louis.
“Going forward, it’s going to be important for humans to have an appropriate level of trust in what AI can do for them,” Yeoh said. “One way to achieve that is to have the system explain why it’s doing what it’s doing in an interactive and understandable way.”
To address these challenges, Yeoh, an associate professor of computer science and engineering, and Vasileiou, a graduate student in Yeoh’s lab, developed TRACE-cs, a novel hybrid tool that tackles the concrete problem of students’ course scheduling. The tool generates accurate explanations efficiently in a quickly digestible format — a novel advancement in the field. Vasileiou presented TRACE-cs Feb. 28 at the 2025 AAAI Conference on Artificial Intelligence.
TRACE-cs combines symbolic reasoning with the natural language capabilities of large language models to provide trustworthy, easily understandable assistance with complex decision-making tasks. TRACE-cs ensures accuracy by incorporating user verification and allowing for follow-up questions and it improves usability by prioritizing concision in explanations of recommended schedules.
Read more on the McKelvey Engineering website.
