SBP: Collaborative Research: RUI: Expansion and Infrastructure Development of the Chicago Face Database

This project expands and diversifies the Chicago Face Database – a source for high-quality facial stimuli freely available for scientific research. The database is utilized extensively by the research community to study phenomena of interest to a variety of fields, including psychology, computer science, and economics. Human faces offer a rich source of information and are critically important as people navigate the social world.

Babies enter the world ready to orient and attend to human faces. By adulthood, humans learn to prioritize the features that allow for the rapid categorization of others by sex, age, and race. People infer a large number of psychologically meaningful attributes about others based on facial features.

Effectively studying face processing and its downstream effects on human behavior requires high-quality, valid stimuli. This project expands, enhances and makes available such stimuli to researchers. By improving the Chicago Face Database, this project promotes better scientific practices, helps researchers test new and different questions, pursues basic science questions, and trains historically underrepresented students in the sciences.

The Chicago Face Database currently includes digital images of over 800 Asian, Black, Latinx, multiracial, and White Americans and South Asian Indians. It also includes important ratings and physical measures of the faces. The Chicago Face Database was designed to fill a significant research need: providing high-quality and diverse face stimuli to researchers at no cost.

Since being released in 2015, the Chicago Face Database has been downloaded over 8,000 times and cited over 1,400 times, affirming its value to the scientific community. The current project expands and diversifies the Chicago Face Database to include 200 additional images of people photographed in China and Japan, update the subjective ratings of the faces, provide more comprehensive measurements of the faces, and design new web-based tools for accessing the resource and facilitating stimulus selection.

In accomplishing these goals, the project addresses basic science questions related to the cross-race recognition deficit, a psychological phenomenon whereby people show better recognition for faces belonging to their own race than to other races. In addition, a high-impact, hands-on mentoring program is offered to historically underrepresented students pursuing computer science.

The students receive professional development coaching and individualized mentoring as they work closely with a computer scientist in the development of the web-based tools.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.