Healthcare data meets AI in UW-Eau Claire honors course

“Artificial intelligence is very relevant to my major and my career goals, so I thought it would be in my wheelhouse,” says the actuarial science major from Jackson.

“I’d had some exposure to AI models during an internship, and big data sets are what my future is going to be about. I plan to work in the insurance industry, more property and casualty over the health insurance lane, but AI modeling is relevant for sure,” Collins says.

Collins says he appreciates the way courses in the Cosby Honors College deliver high-level complex topics like AI and machine learning in a way that invites students across many majors to take an interest.

“It’s important that all students gain some understanding of AI,” Collins says. “It will be a part of so many job sectors — we should all have at least a starting point of understanding how it works and get past the general mystery about it.”

Delivering on the promise of an honors degree

Bhattacharyay worked with Dr. Heather Fielding, director of the Cosby Honors College, to develop a course on AI designed for science and nonscience majors.

Modern medicine has become highly reliant upon data, and Bhattacharyay says that AI is increasingly used to provide critical analysis and solutions in areas like genetics, disease tracking and treatment prediction modeling.

“The advent of ‘Big Data’ has created significant opportunity to use machines to learn from this data to better predict treatments and, in turn, deliver improved patient outcomes,” he says.

“We all have a stake in in the future of AI, and healthcare is part of all of our lives,” Bhattacharyay says about the appeal of this course, which counts as a general science liberal education credit for non-STEM majors in the Cosby Honors College.

Fielding says the course has filled to the maximum 26 students both times it has run so far, and it is a chance for honors students at all levels to learn about the chemistry behind the science, and the use of the Bluglold Supercomputing Cluster in analyzing the data.

“Sudeep has managed to make this complex topic accessible to a wide range of students,” Fielding says.

“Our courses all are rooted in a discussion-based pedagogy, so many non-STEM students who might never otherwise take a course from someone like Sudeep are learning this timely topic in a scientific way from one of our leading computational chemistry instructors — it’s a very rich experience.”

Student takeaways for AI in their futures

For some students, Bhattacharyay’s dive into AI and healthcare data in Honors 118 builds on previous experience using or general knowledge of AI modeling. This was true for Collins, who says he registered for the class “knowing maybe more about AI than the average student.”

“In my summer internship with an insurance firm last year, there was a guy working on a special project merging AI into some of their systems,” Collins says.

Collins was able to talk to him about the work quite a bit, observing how machine learning works with big data in insurance, and better understanding how it works in general. He believes that more students need that baseline understanding of AI as they move into many careers in the world today.

“A lot of students think of AI as just a better search engine than Google,” he says. “It can work like that, but it’s more important to understand how it learns, how it is pulling and using data, and why it’s wrong sometimes in making predictions.”

Along with introducing basic functions of machine learning, the class was also designed as a springboard to important discussions about the ethical concerns around artificial intelligence, an aspect of the course Collins says he appreciated.

“One of the later assignments asked us all to read a paper on CRISPR [an advanced gene-editing technology] and get an idea of what recent technological innovations might mean for the future of possibilities within that field. We were each to pose two questions about hypothetical outcomes,” Collins says.

Collins says his group came up with wide-ranging discussions around topics of potential impact from such an AI use case. They touched on government oversight, equality, self-identity, ableism and simply “what it means to be human.”

Bhattacharyay and Fielding both say they were impressed with the critical thinking at work in class sessions like the one Collins describes. It leads, they say, to the exact type of thoughtful considerations needed as AI plays more of a role in higher education and beyond.

“We are optimistic about the good that AI can do,” Bhattacharyay says. “We are also cautious about potential negatives, so we look for ways to maintain ability to steer the course.”

“Given the data-driven nature of our healthcare system and the foundational chemical science behind it, this course emphasizes the need to uphold ethical standards and critically analyze potential biases in health-related predictions,” Bhattacharyay says.

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Learn more about the Mark Stephen Cosby Honors College on its webpage.

If you have questions about Honors 118: Chemical Computing and AI in Healthcare, contact Dr. Sudeep Bhattacharyay.