ISE PhD student offers human systems perspective at MIDAS Future Leaders Summit
ISE graduate student Dane Morey (PhD ’23) had a chance to “reframe the conversation” on human-automation interactions at the Michigan Institute for Data Science (MIDAS) Future Leaders Summit held at the University of Michigan campus in April.
The event, featuring a theme of “Responsible Data Science and AI,” offered 30 graduate and post-doc students from 19 prominent U.S. universities a chance to present their research to peers from across the country.
He says most of the talks took place on the first day of the three-day conference, “which made it really great to facilitate networking and discussion ongoing throughout the summit.”
Morey’s talk was titled “From Responsibility to Resilience: Supporting RE-framing by Conveying Algorithm Misalignment.” He says his presentation centered around cognitive systems engineering and the need to support frontline workers who interact with data science tools.
“It’s our responsibility to bring in and include those people as part of the solution,” Morey says, “not only from a data science perspective.”
Morey says he was one of only two attendees at the conference with a human factors background. He says he found the audience to be very receptive to his topic and he appreciated the opportunity to learn about research being conducted at other universities.
“This happened to be a perfect venue for me for formulating what has been crystallizing a lot of the thought that has been going through my mind for a while,” Morey says. “I was really grateful for the opportunity.”
Morey says his research is focused not only on the need to bring people into the conversation but also how to do so. “My research explores design techniques to visualize the computations and outputs of AI algorithms for frontline practitioners,” he says, “so that they can simultaneously understand what the algorithm is doing, why it is doing what it is doing, and when the algorithm is misaligned to the world.
“A good chunk of people deserves, not just fairness, but also equity,” he says, adding that algorithms sometime impede equity. “The data science community still focuses on data science solutions.”
Still, he says, “There’s a lot of cause for optimism. Data scientists spend years mining solutions to have a positive impact on larger systems. They’re going to need help from ISEs and cognitive systems engineers moving more structured applications to data science. There are lots of opportunities to work together.”
Dr. Tanya Berger-Wolf, director of Ohio State’s Translational Data Analytics Institute and a professor in the College of Engineering, also served as a presenter, and as a faculty mentor at the summit.
Story by Nancy Richison