AI for good

Q&A: COMPUTER SCIENTIST FENG JIANG SHARES HOW HER STUDENTS ARE USING MACHINE LEARNING TO BENEFIT SOCIETY.

By Dan Vaccaro

By now, most people know that generative artificial intelligence tools can create essays and illustrations. But for Feng Jiang, Ph.D., associate professor of Computer Science at Metropolitan State University of Denver, AI’s greatest potential lies in its ability to solve real-world problems.

Jiang, who has done extensive research on the use of AI across multiple disciplines, is guiding her students as they use the technology to benefit society. Students in her machine-learning class and research group have developed projects around face recognition, medical imaging and agriculture data. One group even created a virtual lab assistant to help students who are blind navigate science labs.

RED caught up with Jiang to pick her brain about the rise of intelligent machines.

What makes AI so adaptable to different disciplines?

AI can adjust and improve itself over time as it encounters new data, which makes it possible to adapt and find new applications in diverse fields. I believe as AI research progresses, we will see even broader usage and impact across more disciplines.

What’s the difference between AI and machine learning?

AI is a broader concept that covers all the theory and techniques for developing machines or tools that have human intelligence. Machine learning focuses on developing algorithms that allow machines to learn from data and improve their performance on a particular task without being explicitly programmed. Machine learning is a subset of AI.

Tell us about your most recent project involving AI or machine learning.

My students and I developed a virtual lab assistant tool based on Amazon Alexa. We collaborated with MSU Denver Chemistry Professor April Hill and the Colorado Center for the Blind. The tool is designed to guide blind students or students with vision impairments to perform chemistry lab work independently through voice control. We published a paper on the tool, titled “An Artificial Intelligence Tool for Accessible Science Education,” in the Journal of Science Education for Students With Disabilities.

Which AI developments are you excited or worried about over the next five years?

Five years can be a long time in AI history. I believe we will see a lot of advancements in all traditional application areas such as health care, robotics, automation and data analysis. The rapid development also comes with challenges around ethical decision-making, labor replacement and liability problems. To take full advantage of AI technology, government, industry leaders and researchers must work together to build robust standards and guidelines for AI development.

This Q&A has been edited for brevity and clarity.