Hansol Rheem

I am a cognitive psychologist and human factors engineer. I come from a psychology background and earned my Ph.D. in Human Systems Engineering from Arizona State University. Human Systems Engineering focuses on designing technology and computerized systems that align with human capabilities and limitations (e.g., redesigning complex systems to reduce operator errors during interaction).

 
The topics I research are...

1. Human-AI Teaming: I am exploring the use of nonverbal communication to enhance collaboration in human-AI hybrid teams, aiming for the seamless coordination as can be seen in synchronized swimming. This is important because AI applications in safety-critical domains are expanding. My previous research includes collaborations with GM and Toyota, where I contributed to the design of in-vehicle displays for automated driving systems. Building on this expertise, I am now broadening my focus to AI applications more generally, including the development of a medical triage training program. This program will train participants to assess mass casualty incident victims by working alongside AI teammates.

2. Attention: I investigate how various objects capture attention, including salient-looking objects, goal-relevant objects (e.g., anything red when searching for a friend in a red t-shirt), and objects with evolutionary significance (e.g., a person displaying an angry expression). I also conduct applied research, such as simulating attention shifts when interacting with an airplane cockpit or a vehicle’s center stack display.

3. Implicit Bias: Implicit bias refers to automatic stereotypes that are triggered when we encounter people different from ourselves, potentially influencing our behavior. I study how implicit racial and gender biases affect behavior across different contexts. Using a computer mouse-tracking program, I examine how participants simulate giving and taking pleasant or unpleasant objects from faces that vary in gender and race. This approach allows me to assess how biases influence the speed and efficiency of participants’ hand movements.