Artificial intelligence in the classroom is not new.
Educators have used the technology to grade homework, assist with translations and develop interactive games to improve young children’s academic and social skills.
But the arrival of new, more accessible and sophisticated AI tools, such as ChatGPT, has raised public awareness — as well as concern — about the powerful role that AI will play in the future of education.
How to properly manage that power — from personalized learning and instantaneous feedback, to limiting bias within AI programs — was the topic of conversation Thursday during “Advancing Education with Responsible AI,” the second in a series of panel discussions as part of the UB | AI Chat Series.
“AI is changing the world as we speak,” said Venu Govindaraju, UB vice president for research and economic development, and director of the National AI Institute for Exceptional Education at UB, which the National Science Foundation (NSF) funded with $20 million in January.
A SUNY Distinguished Professor of computer science and engineering, Govindaraju noted that UB has for decades been a “powerhouse in artificial intelligence.” The university’s influence, both locally and globally, will continue to grow as its research enterprise expands, and as faculty members continue public outreach like Thursday’s event, he said.
Hosted by Grand Island Central School District (GICSD), whose superintendent Brian Graham noted the importance of embracing new technology in education, the panel featured UB scholars Rachel Hageman Blair, Kenneth Joseph and Jinjun Xiong, and GICSD teacher Mary Howard.
Suzanne Rosenblith, dean of the Graduate School of Education, moderated the discussion.
Xiong, a SUNY Empire Innovation Professor of computer science and engineering, directs UB’s Institute for Artificial Intelligence and Data Science. He said generative AI, such as ChatGPT, is software that is capable of generating high-quality text, images and other content based on the data it was trained on.
He explained how it can be used as a tool for speech language pathologists to augment and personalize lesson plans, providing them with more time to spend working individually with students — one of the main goals of the National AI Institute for Exceptional Education.
Generative AI, he said, “has a lot of promise to transform our education” system.
Hageman Blair, associate director for education in the UB Institute for Artificial Intelligence and Data Science, said AI has tremendous potential to increase STEM (science, engineering, technology and math) literacy among elementary school students. It could also help reduce inequities in the education system, she said.
“We see that in the students from schools that may not have the resources to have exciting experiments going on,” said Hageman Blair, an associate professor in the Department of Biostatistics in the UB School of Public Health and Health Professions.
Joseph, an assistant professor in the Department of Computer Science and Engineering, said it’s imperative to ensure that AI tools do not contain bias. He also stressed that society must continue to invest in education, and that AI should not be used to replace teachers or cut costs.
“Technology has historically exacerbated these issues, but it doesn’t have to,” he said.
Howard, author of “Artificial Intelligence to Streamline Your Teacher Life: The ChatGPT Guide for Educators,” is a sixth-grade English Language Arts and science teacher. She is excited to use AI to augment her lessons and provide students with personalized learning plans.
“There’s where I think it comes in to help teachers in a much more dramatic way,” she said.
Following the discussion, graduate students presented their research with posters and demonstrations.
Alexander Stone, a PhD candidate advised by Govindaraju, discussed a generative AI program he is co-developing for speech language pathologists. It works by creating flashcards that are customized to individual students’ learning levels and preferences.
The flashcards can be used in minimal pair therapy, which consists of two words that sound alike to highlight a speech sound to a student.
Changjae Lee, a PhD candidate advised by Xiong, explained a new tool he is co-developing, called MLModelScope. It is designed for non-computer scientists who are interested in utilizing AI technology to improve their work or business.
It functions by comparing different AI software so users can find the best platform for their needs. For example, one platform might be better for scanning images, while another excels at analyzing and summarizing text.
The UB | AI Chat Series, which began last month when SUNY Chancellor John B. King Jr. visited UB, will continue over the next two years, featuring faculty-led and moderated discussions that explore how UB researchers from a wide variety of academic disciplines are harnessing artificial intelligence for the betterment of society.