Assessing the Malleability of Trait-Based Face Judgments

Chua, Kaowei, New York City NY

Investigators

Abstract

This award was provided as part of NSF's Social, Behavioral and Economic Sciences (SBE) Postdoctoral Research Fellowships (SPRF) program and SBE's Social Psychology program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Jonathan Freeman at New York University, this postdoctoral fellowship award supports an early career scientist investigating the malleability of trait attributions from faces. People are able to quickly and automatically abstract information from faces, including broad trait information such as whether a face seems trustworthy or not. This process has long assumed to be due to some innate mechanisms, with developmental evidence showing that there is strong consensus about whether a face looks trustworthy or dominant from a very young age. These judgments of trustworthiness have potentially serious downstream consequences, such as hiring decisions, electoral success, and the assignment of the death penalty. This project is focused on exploring the extent to which our trait judgments, specifically centered around trustworthiness, could be acquired and affected by implicit associations between face information and positive and negatively valenced behaviors. The primary aim of this research is to test the malleability of trait impressions from faces in response to information involving associated positive and negative behaviors. To address this research question, this project aims to 1) Examine whether an arbitrary face feature can be associated with positive or negative behaviors, resulting in a subsequent shift in evaluation of faces that contain that feature. Across a number of different measures such as payment in an economic trust game, implicit priming measures, and mousetracking, this project aims to test the extent to which newly learned features and their associations are integrated with the natural trustworthiness of faces to affect evaluations of trustworthiness; 2) Test whether a similar implicit learning paradigm could impact propotypical representations of trustworthy and untrustworthy faces. In this aim, people will participate in a training wherein faces that have features typically denoted as trustworthy associated with negative behaviors and faces that are typically demed as untrustworthy are predominantly associated with positive behaviors; 3) Determine whether implicit learning mechanisms can result in the formation of stereotypes for completely novel categories of faces. This project takes an integrative approach that incorporates the findings from the perceptual learning literature about implicit learning and maximizing the efficacy of associative learning into the realm of social face perception and the effects of conceptual knowledge on perception. This research potentially provides a novel understanding of the malleability of trait impressions and might elucidate the cognitive mechanisms behind the formation of stereotypes. This approach would test the current understanding of trait impressions and the notion that they might be innate, fixed, and do not require experience or a social learning component. The results of this research, particularly the line of research investigating the effects of counterstereotyping on our pre-existing conceptions of trustworthiness, could be used to inform interventions targeted on reducing implicit race and gender bias. 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.