Chong Pak
Clemson University, SC·Psychology
Driver-assist systems and artificial intelligence promise to make hard tasks easier, but they do not help everyone equally. Automation improves performance for some people and makes it worse for others.
- Fields
Psychology
Engineering
- Topics
attention control
working memory
human-autonomy teaming
- Grants
- 1 known grant, through Jul 2028
What they work on
- Determine how individual differences in working memory and attention control (the ability to focus and resist distraction) relate to how well people perform with automated systems, using newly developed, validated attention control measures.
- Identify which cognitive tasks or processes an automated system replaces in a human-autonomy team, and test how this depends on the attention control level of the human user.
- Derive automation design principles from attention control theory, aiming for systems that improve human performance for users at all levels of attention control.
More about the research
Understanding why matters. If these tools help only some users, they could create a new digital divide, in which some people get all the benefits while others are harmed.
Why it matters
Semi-autonomous vehicles, AI assistants and other automated tools are spreading into work and daily life. This work could help designers build systems that support everyone rather than only people with strong attention control. Design recommendations grounded in attention control could reduce the risk that automation widens performance gaps between users and leaves some people worse off.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Areen Alsaid
University of Michigan-Dearborn, MI·Engineering
Develop a framework for how driver trust transfers between automation levels and driving contexts, using survey studies that also assess the role of environmental factors.
Ziran Wang
Purdue University, IN·Engineering·Early-career
Determine how visual attention, spoken language and physical actions reveal a vehicle occupant's cognitive state during interaction with automation, using behavioral sensing.
Jane Huang
University of Notre Dame, IN·Computer Science
Design human-centered interfaces that help teams supervise autonomous drone swarms in time-critical tasks such as disaster response, using cognitive work analysis and iterative user-centered design.
The school
Clemson University: 19 labs on PI Pages, $339M a year on research, 297 research doctorates a year.
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