Department of
Psychological and Brain Sciences

Sixteen years ago, Tim Pleskac came to PBS as a postdoctoral fellow in the lab of Distinguished Professor Jerome Busemeyer. After several other academic positions in the U.S. and abroad, Pleskac returns to Bloomington, one of three new PBS faculty hired under the “Faculty 100” initiative to “amplify IU’s success in core research areas,” among them, the topic of “human and artificial intelligence.”

As Pleskac sees it, his work “bridges the divide between human and artificial intelligence,” by using and developing computational models to understand and improve human decision making. Simply put, these models “are at some level a set of equations or computer code,” he explains, “that take information from a scene to show how that information is processed and transformed into a decision.” Their aim is to mirror in some way what goes on in a decision maker’s mind. As he describes it, “We always talk about opening the black box of the human mind. Can we open it up and say, ‘How do we take information and turn it into a response and specify the process by which information is used?’”

Yet, in addition to bridging the divide between human and artificial intelligence in this way, his work cuts across other boundaries too, from disciplinary divides to those that separate the controlled lab environment and more chaotic real-world scenarios in which human decisions take place.

Take for example, his ongoing analysis of the factors which lead to police officers’ decision to use deadly force against a suspect and how race figures into that process. While in other projects he has collaborated with clinical psychologists, neuroscientists, behavioral psychologists and others, for this project he collaborates with experts in social psychology and social cognition, so as to incorporate social dynamics into their models. “Police don’t make the decision to shoot alone. Other police who are with them are also making this decision, so I’m interested in how one person’s decision affects another.” And while people make decisions in groups in many situations, more and more they are also making decisions with the help of machines, such that one day, he believes, his work may be able to help improve these human and human-machine teams.

In these projects and others, Pleskac seeks to incorporate as much of the real-world situation into the lab experiment as possible. In the “decision to shoot” studies, for example, he and his team work with a video scenario, while police officer participants hold a modified handgun, which still “gives a kick,” as he says, when they pull the trigger. Across this and other projects, Pleskac thus seeks to achieve what he calls “translational modeling,” to translate models for understanding behavior inside the lab into models that explain behavior in real-world environments. “People have done a wonderful job modeling behavior in a controlled laboratory task,” he says. However, he would like to find out how “to take these models outside the lab, to see how far we can push them to predict behavior outside the lab,” he says.

 

 

Among other projects Pleskac is pursuing at IU is one that examines the fairness of the scientific review process for conference papers. “We’ve done a giant field experiment, looking at how reviewers rate submissions for a conference,” he explains. Among the questions, “What’s the difference between single-blind review in which reviewers know the names and affiliations of a paper’s author and double-blind review in which they do not? There’s not a lot of data about how that information changes the way decisions are made.” The results, he says, “are more surprising than we thought with only small systematic differences” between them.

Yet another project is an NSF-funded grant on how people forecast everyday events. And because “it is easy to find experts on basketball,” he is studying predictions made about NCAA basketball. “We give people different teams and ask them to predict the probability of which will be ranked higher,” he explains. “Then we systematically study how people make those judgements, how quickly, and how popular representations of those teams impact how people make those judgments.”

His interests about decision making are wide-ranging. They encompass questions about how people deliberate to form a decision, seeking to “understand all the processes that I use while I’m deliberating about making decisions: What role does attention play? How do I attend to different options? What role does memory play and how do I learn with experience and how does experience impact how I deliberate with those options?” Yet, he also looks at how the environment aids in decision making, “how it impacts people’s decisions and how we can make use of the environment to make decisions,” he says.

Pleskac comes to IU Bloomington from the University of Kansas in Lawrence, Kansas, where he was the chair and professor in the Department of Psychology. It was “a really special place,” he notes. But when he came to IU for a post-doc 16 years ago, he “fell in love with the place and the people.”

“Frankly speaking,” he adds, “IU is the heart and soul of computational modeling in psychology. So it was an awesome opportunity to be part of that and continue the growth of this area.”

“I’m really excited about Bloomington making this opportunity to bring these two areas together and ask really interesting questions about how we can use artificial intelligence to understand decision making and cognition in humans and, vice versa, how we can use what we know about human intelligence to learn about or improve artificial intelligence.”

Hear Professor Pleskac talk about his work and goals!