How Stereotypes Bias Memory

Author: Emily Marler, PhD
Editor: Kristen Lindauer, PharmD, BCPS, AAHIVP

Introduction

Stereotypes, or negative generalized beliefs or expectations, bias memory in many different ways.¹ Specifically, research has explored how stereotypes bias source monitoring, which refers to the process of determining the origins of our memories, knowledge, or beliefs.² A source monitoring error occurs when one incorrectly identifies the source of a memory, which is one of the most common types of memory errors.² While source monitoring errors based on stereotypes represent the brain’s ability to make energy-efficient decisions automatically and with little to no resources, they can be harmful.

Stereotypes often represent negative generalizations about a group of people and can be used to condone discrimination and prejudice.³ In the context of eyewitness testimony, source monitoring errors can also result in miscarriages of justice by convicting folks of crimes they did not commit.⁴ Therefore, it is imperative to be aware of how stereotypes can bias memory. This article will discuss how stereotypes bias source monitoring, focusing on stereotypes relating to gender, sexual orientation, race, and age.

Gender

Gender stereotypes bias memory by increasing the likelihood that participants will incorrectly identify the source of a particular statement as one confirming a gender stereotype.⁵ For instance, in a study by Marsh and colleagues (2006), participants read a list of masculine, feminine, and neutral statements that were spoken by either Chris or Pat (note: the names are purposefully gender-neutral, so participants cannot identify gender before learning the statements).

• Example masculine statement: “I belittled a coworker in a meeting’
• Example feminine statement: “I made a centerpiece for the dining table”
• Example neutral statement: “I am very easy going”

After reading the statements, participants were told that Chris is male and Pat is female. Then, participants saw the same statements again and identified who, Chris or Pat, made the statement, or whether the statement was brand new. Results showed that participants were more likely to attribute the masculine statements to Chris, identified as male, and the feminine statements to Pat, identified as female, when they forgot the origin of the statement. These results indicate that participants rely on gender stereotypes when retrieving information from memory.

Sexual Orientation

In the same experiment that found gender stereotypes bias source monitoring, the researchers also found that this effect could be reversed by divulging the sexual orientation of the statement makers.⁵ For instance, when told Chris is a homosexual man, participants were more likely to mistakenly determine that Chris made feminine statements compared to masculine statements. When told Pat is a homosexual woman, participants were also more likely to incorrectly state that Pat made masculine statements. These findings indicate that sexual orientation may also bias source monitoring, in a way that is consistent with homosexual stereotypes, but inconsistent with gender identity. 

Race

Race stereotypes bias source monitoring in similar ways as gender and sexual orientation. For instance, Mitchell (2001) conducted a study examining source monitoring based on race and crime. Participants read one of two stories describing a crime: one story pertained to a Black carjacker and the other a White carjacker. They found that racist White participants committed significantly more source monitoring errors compared to non-racist White participants when reading about the White carjacker. That is, they were more likely to incorrectly identify the source of the carjacking to be the Black character as opposed to the White character. These results indicate that when an event is inconsistent with a certain stereotype (e.g., that Black folks are more likely to commit crimes than White folks), folks are more likely to incorrectly attribute the perpetrator of a crime to someone whose race matches their stereotype.⁸

Age

Age stereotypes also influence source monitoring. Kuhlmann et. al (2016) recruited older (60-84) and younger (17-26) adults to complete an experiment assessing source monitoring. Participants read statements that were either stereotypical of an older adult (e.g., relating to strong familial ties, organizing finances, health and fitness concerns, etc.) or stereotypical of a younger adult (e.g., poor finances, no concerns about health and fitness, active friendships and sexual relationships). Afterward, participants were told that one of the speakers was 70 years old and the other speaker was 23 years old. When participants could not remember the source of the information, they were more likely to incorrectly guess that the stereotypical older adult statement was made by the 70-year-old and the stereotypical young adult statement was made by the 23-year-old. This effect was pronounced in older adults with poorer source memory compared to older adults with better source memory. Therefore, when forgetting the source of information, participants are more likely to rely on age stereotypes, particularly in older adults with poor source memory.⁹

Now What?

Together, these studies indicate that folks rely on stereotypes when they forget the source of information. While this may seem innocuous, relying on stereotypes can be harmful and result in negative evaluations and treatment of folks from historically excluded backgrounds.^3,4,6

Due to the severity of harm that stereotypes can bring, it is imperative to consider how to combat stereotypes and lessen the occurrence of source monitoring errors. Anderson et al. (2015) have one recommendation: learn about the difference between “remember” and “know” judgments when determining memory. “Remember” judgments refer to specific, detailed memories “that can be mentally re-lived”, and “know” judgments are “based on feelings of familiarity” rather than actual remembrance.⁷ After training participants to know the difference between remember and know judgments, participants were asked to evaluate a woman leader based only on what they remember reading about the candidate, as opposed to details they are familiar with, to reduce the likelihood of relying on stereotypes when making their evaluations. Anderson et al. (2015) found that, after training, participants with low implicit bias only showed increased evaluations for the woman leader. However, participants with high implicit bias demonstrated decreased evaluations of the woman leader after training.

The implications of these results are twofold:

1. Challenging our memories of events based only on what we remember happening can help eliminate the likelihood of relying on stereotypes to fill in memory gaps, and
2. We can achieve this by challenging our implicit biases. Implicit bias refers to automatic processes that influence decision-making and judgment and include stereotypes, attitudes, assumptions, and motivations.

Therefore, it is equally as important to challenge and monitor our own implicit biases as it is to challenge our memories. There are several ways we can do so, including:

1. Checking one’s biases and challenging them regularly in both business and personal life,
2. Creating safe spaces to acknowledge and discuss implicit biases and experiences with them,
3. Making space for cultural humility when interacting with folks of various backgrounds, and
4. Becoming educated by seeking out classes or relevant information on recognizing and challenging biases.¹⁰

In doing so, we can reduce the harm to folks from historically excluded groups based on stereotypes.

References

1. Fyock, J., & Stangor, C. (1994). The role of memory biases in stereotype maintenance. British Journal of Social Psychology, 33(3), 331-343.
2. Johnson, M. K., Hashtroudi, S., & Lindsay, D. S. (1993). Source monitoring. Psychological Bulletin, 114(1), 3.
3. Dovidio, J. F., Hewstone, M., Glick, P., & Esses, V. M. (2010). Prejudice, stereotyping and discrimination: Theoretical and empirical overview. Prejudice, Stereotyping and Discrimination, 12, 3-28.
4. Roberts, K. P., & Blades, M. (1998). The effects of interacting in repeated events on children's eyewitness memory and source monitoring. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition, 12(5), 489-503.
5. Marsh, R., Cook, G., & Hicks, J. (2006). Gender and orientation stereotypes bias source-monitoring attributions. Memory, 14(2), 148-160.
6. Anderson, A. J., Ahmad, A. S., King, E. B., Lindsey, A. P., Feyre, R. P., Ragone, S., & Kim, S. (2015). The effectiveness of three strategies to reduce the influence of bias in evaluations of female leaders. Journal of Applied Social Psychology, 45(9), 522-539.
7. Martell, R. F., & Evans, D.P. (2005). Source-monitoring training: Toward reducing rater expectancy effects in behavioral measurement. Journal of Applied Psychology, 90, 956–963. doi:10.1037/0021-9010.90.5.956
8. Mitchell, E. B. (2001). Justice is in the eye of the beholder: The role of implicit racial stereotypes on source-monitoring decisions and assessments of punishment. California State University, Long Beach.
9. Kuhlmann, B. G., Bayen, U. J., Meuser, K., & Kornadt, A. E. (2016). The impact of age stereotypes on source monitoring in younger and older adults. Psychology and Aging, 31(8), 875.
10. Schiavo, R. (2024). Challenging implicit bias: a call for action. Journal of Communication in Healthcare, 17(4), 311-313.

Author Bio

Emily Marler is a teaching professor at the University of Missouri St. Louis. She attended Southern Illinois University Carbondale for her Bachelor’s degree in Psychology and Saint Louis University for her Master’s degree and Ph.D. in Experimental Psychology with a specialization in Cognitive Neuroscience. In her downtime, Emily enjoys walking her dogs and watching questionable 80’s movies.

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