To conduct this study, we recruited 1,500 people from all 50 U.S. states in 2022 to participate in an online experiment on Prolific, a survey platform. The group was nationally representative in terms of race and ethnicity, age and gender.
We first collected data on their beliefs about the race and ethnicity, education, productivity and personality traits of people with six names picked from a pool of 2,400 workers whom we hired in an early stage of our experiment for a transcription task. Data from these individual responses made it possible for us to categorize how they perceived the candidates.
We found that the names of workers perceived as Black, such as Shanice or Terell, were more likely to elicit negative presumptions, such as being less educated, productive, trustworthy and reliable, than people with either white-sounding names, such as Melanie or Adam, or racially ambiguous names, such as Krystal or Jackson.
We were specifically studying discrimination against Black people, so we did not include names in this experiment that are frequently associated with Hispanics or Asians.
Participants were next presented with pairs of names and were told they could earn money for selecting the worker who was more productive in the transcription task. The chance that they would choose job candidates they perceived to be white because of their names was almost twice as high than if they thought the candidates to be Black. This tendency to discriminate against people with Black-sounding names was greatest among men, people over 55, whites and conservatives.
Educational attainment, the level of racial diversity in the participants’ ZIP codes or whether they had personally hired anyone before didn’t influence their apparent biases.
Rushing can cause more discriminatory behavior
Most real-world hiring managers spend less than 10 seconds reviewing each resume during the initial screening stage. To keep up that swift pace, they may resort to using mental shortcuts — including racial stereotypes — to assess job applications.
We found that requiring the study participants to select a worker within only 2 seconds led them to be 25% more likely to discriminate against candidates with names they perceived as Black-sounding. Similar patterns of biased decision-making under time pressure have been documented in the context of police shootings and medical decisions.
However, making decisions more slowly is not a panacea.
We found that the most important factor for whether more deliberate decisions reduce discrimination was a participant’s view on affirmative action — the consideration of race in a workforce or student body to ensure that their share of people of color is roughly proportionate to the general public or a local community.
White participants who opposed affirmative action were more than twice as likely to select an applicant with a white-sounding name compared with applicants perceived as Black — whether or not they had to make the simulated hiring decision in a hurry.
By contrast, giving white participants who favor affirmative action unlimited time to choose a name from the hiring list reduced discrimination against the job candidates with names they perceived as Black-sounding by almost half. The data showed that this decline had to do with people basing their decision more on their perceptions of a worker’s performance, rather than relying on mental shortcuts based on their perceived race.
We assessed the participants’ views on affirmative action by doing a survey at the end of this experiment.
Discrimination hasn’t gone away
A study published in 2021 suggested that hiring discrimination based on Black-sounding names had declined, although discriminatory practices remained high in some customer-facing lines of work, such as auto sales or retail.
Martin Abel is an assistant professor in economics at Bowdoin College and research affiliate at the IZA. Through its opinion section, Kansas Reflector works to amplify the voices of people who are affected by public policies or excluded from public debate. Find information, including how to submit your own commentary, here.