Class
Article
College
Emma Eccles Jones College of Education and Human Services
Department
English Department
Faculty Mentor
Crissa Levin
Presentation Type
Poster Presentation
Abstract
Anger race bias is the tendency to misidentify expressions of emotion, specifically anger, in Black or racially ambiguous faces (Hutchings & Haddock, 2008). Hutchings & Haddock (2008) found that Black faces are more likely to be perceived as angry by people high in implicit bias. Since January 1st, 2015, 119 unarmed Black males have been shot and killed by police (Washington Post, 2020). When police officers perceive a threat, they are more likely to shoot, and mistaking expressions such as fear for anger causes the perception of increased threat that can lead to inaccurate responses such as excessive force (Correll et al., 2010). Accurate perception of emotion, therefore, is necessary in order to react correctly. The purpose of this study was to investigate if anger race bias could be reduced through emotion identification training. The current study used photos of faces from the Chicago Face Database to train participants on the emotions of neutral, fear, and anger. Participants identified emotions on a series of Black, White, LatinX, and Asian faces on pre-and post-test measures. Two weeks following the post-test, participants were invited to complete a follow-up test to determine their retention of the training. We found that participants who were in the experimental group accurately identified more facial expressions on average, than participants in the control group. This shows that there is feasibility in developing emotion recognition trainings to be implemented in police settings to potentially decrease anger race bias.
Location
Logan, UT
Start Date
4-7-2022 12:00 AM
Included in
Detecting Accurate Emotions in Faces
Logan, UT
Anger race bias is the tendency to misidentify expressions of emotion, specifically anger, in Black or racially ambiguous faces (Hutchings & Haddock, 2008). Hutchings & Haddock (2008) found that Black faces are more likely to be perceived as angry by people high in implicit bias. Since January 1st, 2015, 119 unarmed Black males have been shot and killed by police (Washington Post, 2020). When police officers perceive a threat, they are more likely to shoot, and mistaking expressions such as fear for anger causes the perception of increased threat that can lead to inaccurate responses such as excessive force (Correll et al., 2010). Accurate perception of emotion, therefore, is necessary in order to react correctly. The purpose of this study was to investigate if anger race bias could be reduced through emotion identification training. The current study used photos of faces from the Chicago Face Database to train participants on the emotions of neutral, fear, and anger. Participants identified emotions on a series of Black, White, LatinX, and Asian faces on pre-and post-test measures. Two weeks following the post-test, participants were invited to complete a follow-up test to determine their retention of the training. We found that participants who were in the experimental group accurately identified more facial expressions on average, than participants in the control group. This shows that there is feasibility in developing emotion recognition trainings to be implemented in police settings to potentially decrease anger race bias.