To Caleb Everett, language is one of the greatest differentiators that allows our species to think and communicate far more efficiently than any other.
But with more than 7,000 languages (and countless dialects) used around the world, Everett’s early research was limited to comparing only a handful at a time. Then, about a decade ago, researchers started publishing massive databases collecting the sounds and structures used in thousands of languages.
Everett was fascinated, but the professor of anthropology didn’t know how to sort it all, so he decided to learn how to code to conduct more rigorous data analysis.
Before long, Everett could write just a few lines of code and pore through the databases he once considered impenetrable.
“That was the eureka moment for me. The data analysis that once would’ve taken me months took just a few minutes,” said Everett, senior associate dean for faculty affairs at the University of Miami College of Arts & Sciences.
Everett’s revelation is but one example of a long and growing list of research being conducted in the College of Arts & Sciences that uses the power of artificial intelligence (AI), machine learning, and big data to better understand the brain. Across the College, researchers are using those tools to decipher how brains establish their first connections, process sensory information, develop mental disorders, and lose focus.
“There’s a need to understand these tools,” said Odelia Schwartz, associate professor and director of undergraduate studies for computer science. “In today’s world, people in any field should have more knowledge about how these models work because it’s become so influential.”
Aaron Heller, associate professor in the Department of Psychology and director of the Cognitive and Behavioral Neuroscience Division, has also increased his use of data-powered research throughout his career.
When Heller and a colleague expanded a study that looked at whether people who moved around more frequently each day had lower levels of stress and depression, they tracked hundreds of people and collected far more contextual information. Synthesizing all those data points without using advanced algorithms “would literally be impossible,” Heller said. “No human could sit down and scour through that.”
Fields like cognitive neuroscience have also relied on computational tools more often to unravel the complexities of brain function. Amishi Jha, professor of psychology and director of contemplative neuroscience for the UMindfulness Initiative, focuses on the brain’s attention system. Her recent work explores mind-wandering: off-task thoughts that arise during activities.
“While we may think modern life is to blame for our distractibility, it’s actually an ancient problem," Jha said, pointing to mindfulness meditation, backed by cutting-edge science, as a potential solution.
Mingbo Cai, assistant professor of psychology, describes his research as bridging human neuroscience and machine learning.
One of his ongoing projects is trying to understand how infants are able to perceive the three-dimensional environment around them (identifying objects and distances) before they’re even able to speak. “To understand intelligence, we need to look at when it starts, but there is a limit on how much we can answer by observing infants,” he said.
As with any emerging technology, the widespread use of AI has led to questions about the nature of the science itself. Alison Springle, assistant professor of philosophy, says we’re at a complicated crossroads.
On the one hand, AI-powered systems have exhibited all kinds of problems, from “black box” deep learning models that act in ways that even their creators don’t understand to “algorithmic injustices” that create biased models because the data used to train them largely exclude people from certain racial, demographic, and geographic backgrounds. Too often, Springle said, people mistake the resulting problems as originating from the AI rather than reproducing biases inherent in the way scientists have conducted research and collected data in medicine and other fields.
“It serves to distance us from very real problems in a weird way,” she said. “It addresses these very serious problems of injustice, but in a way removes them like, ‘It’s in the AI,’ as opposed to, ‘It’s in the users.”
Schwartz also has concerns, but she’s encouraged that scientists are now being forced to grapple with them. When submitting papers to AI conferences, researchers are now being asked about ethical considerations. “It’s good to make sure people are thinking about the implications of their work,” she said.
Springle believes the University can serve as a clearinghouse for those kinds of questions. She and her colleagues in the Department of Philosophy are trying to start a series of conferences exploring the philosophy of science, and they hope to create a formal center focused on that field.
This is an excerpt from the feature article in the fall issue of the College of Arts & Sciences’ magazine.
© 2026 University of Miami College of Arts and Sciences
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