Deciphering Clues in Human Behavior

Cognitive scientist Rick Dale could be called a detective of human behavior. He is an expert at measuring how our bodies reveal clues to our thoughts and social interactions that are otherwise invisible. These cues can be subconscious and subtle, he has found – a quick eye movement, a change in the pitch of a voice, the way we hold a computer mouse – but surprisingly meaningful. For example, they can help employers figure out who will work well together on a project, and reveal how much we do or don’t agree with a coworker. They can even give teachers clues about how well students understand classroom material.

Dale, an associate professor at the University of California, Merced, studies how a range of physical cues, like posture, eye contact, and speech, provide information about how two people interacting with each other think, feel, and relate. For example, he and his collaborators have found that when two people discuss a political topic on which they disagree, their conversational pattern changes. It becomes more rigid, with more turn-taking and less overlapping speech. How they position their bodies, leaning toward or away from one another, provides clues, too. Dale and his colleagues have shown that when people have a shared understanding, their eye movements tend to be more in sync as well. Unlike the claims of so-called body-language experts, which he says still need quantification, Dale’s findings don’t purport to reveal what each party is thinking, but rather provide information about the overall tenor of an interaction or relationship.

Part of what makes Dale’s work unique is the accessibility of the methods he uses for measuring behavior. “We are always looking for methods to quickly observe and quantify without special equipment,” he explains of his lab. In studies described above, he has used simple video cameras or audio recorders, and in others, he has tapped into an everyday object found on many of our desks: a computer mouse. With appropriate software, Dale has been able to track where and how much people move a mouse before clicking an on-screen button. When the person is presented with multiple options on the screen (e.g., in a multiple choice test), he can track how quickly and certainly the user makes a choice. More movement tends to reflect more uncertainty. That has potential use for tracking political beliefs and voting behavior.

In a related study, Dale and his collaborators “hacked” a Nintendo Wii controller so that they could measure how much a player moved it, how hard he gripped it, and how firmly he pressed a button. They found that the firmness with which the player held and pushed the remote was a “signature of decision confidence.” They showed that this can unveil not only cognitive confidence, but also how much a player has learned about a task. This research has educational implications, Dale believes. For example, the decision confidence measure could be used to assess how certain a student is about a test item, and therefore whether she has formed a solid understanding of the material or was likely guessing the correct answer.

Dale’s work could have a range of other applications in economics, politics, medicine, and beyond. For example, a psychotherapist could use the findings about conversation patterns to assess whether her patient feels an alliance with her and therefore how well the session has gone. Business leaders and coaches could evaluate how well a team is working together by examining the eye movements of its members. Dale’s innovative methods have been applied by researchers in other fields as well, for example to examine social interactions among people with autism spectrum disorders. That kind of diverse application is part of what inspires him, and it’s likely to keep him busy, as he continues to examine clues to all kinds of human interactions.


Rick Dale is a recipient of the Federation of Associations in Behavioral & Brain Sciences (FABBS) Early Career Impact Award, from the Society for Computers in Psychology. Some of the work described above was conducted in collaboration with his former students Dr. Alexandra Paxton (Berkeley), Dr. Nicholas Duran (Arizona State), and Dr. Jennifer Roche (Kent State), along with collaborators Drs. Michael Spivey and Daniel Richardson.