About implicit bias

Junior (College 3rd year) ・Psychology ・APA ・55 Sources

Implicit bias refers to views or prejudices that might influence an individual's actions, perceptions, and decisions in an unconscious manner (Girvan, 2015). It is sometimes referred to as latent social cognition. These biases are made up of both favorable and unfavorable judgements and can be activated involuntarily and without an individual's awareness or intentionally (Lieber, 2012). Implicit biases have been discovered to be distinct from other types of prejudices that an individual may choose to conceal for the sake of societal and civil decorum. However, implicit prejudices cannot be discovered through self-examination (Gill & Oganesyan, 2015). The implicit associations that different people possess in their subconscious have the ability to cause them to develop feelings attitudes about other individuals in the society based on different physiognomies such as ethnicity, appearance, age, and race (Lassiter & Ballantyne, 2017).

The development of these associations does often take place over the course of a lifespan and begin at a very early age following the disclosure to direct or indirect stereotype information (Blake & Gannon, 2012). In addition to the early life involvements, the mass media and parenting styles are also considered as other potential factors which contribute to the development of implicit bias among individuals in the society (Hatzis, 2013). In order to effectively demonstrate how implicit biases do often develop among different individuals, it is important to determine some of the important characteristics of this type of bias (Girvan, 2015). Based on the fact that everyone with a commitment to impartialities such as judges do often possess them, it will be therefore important to note that implicit biases are pervasive.

Even though the implicit and explicit biases are related, they can be differentiated through mental constructs, they are not mentally exclusive thus can reinforce each other (Gill & Oganesyan, 2015). The implicit bias are malleable. The human brains are incredibly complex. Therefore the implicit associations which individuals possess can be gradually unlearned through the application of a variety of anti-biasing techniques (Puddifoot, 2015). Discrimination and implicit bias are serious problems in the workplace. Within an organization, discrimination has been able to prevent the minorities and other people being discriminated against not to advance within their organizational hierarchy (Spencer, Charbonneau & Glaser, 2016). The resulting situation leads to demonstration of pre-existing structural inequality and creation of race and gender-based pressures in the place of work. Following the civil right movement of the 1960’s and 1970’s, people have progressively circumvented overt prejudice as a result of fear and social condemnation (Scherer & Lambert, 2012). In that case, the implicit bias and discrimination have become less overt (Tetlock & Mitchell, 2014).

Discrimination is the process which involves handling or intending to treat somebody disparagingly as a result of particular characteristics which are protected by law. The Equal Opportunity Act 2010 of the United States of America sets out eighteen possible personal characteristics that make the discrimination in the workplace to be unlawful (Lassiter & Ballantyne, 2017). The employment discrimination can, therefore, be described as an unfair treatment of employees based on prejudices. The employees are always protected from different forms of discrimination at all stages of the employment (Krieger & Fiske, 2016). Some of the possible forms of discriminations in the workplace include; the recruitment process which involves how the various job positions are publicized and interviews are held, being subjected to prejudicial terms and conditions of employment, and being deprived of training opportunities, promotion, transfers, performance pay and other types of employment-related remunerations (Scherer & Lambert, 2012). In some cases, the discrimination can be exhibited through being unfairly retrenched, demoted or dismissed (Gill & Oganesyan, 2015).

Some of the most common factors which contribute to the development of discriminative actions against an individual in the workplace include the negative perceptions and stereotypes about a certain group of people (Tetlock & Mitchell, 2014). Therefore, this will lead to the creation of unfair perceptions about what people with certain types of personal features are able or not able do (Hatzis, 2013). A good example of discrimination can be based on the fact that a company can refuse to employ somebody on the basis of their stage of development since they are of the opinion that the individual is too old to learn new skills (Puddifoot, 2015). The types of workplace discriminations have been found to be dependent upon sexual orientation, religion, pregnancy, disability, age, equal pay compensation, race, and ethnicity (Spencer, Charbonneau & Glaser, 2016). There are various discriminatory policies, traditions, ideas, and laws which exist in many countries and institutions around the globe, including the regions where discrimination is generally looked down upon (Spencer, Charbonneau & Glaser, 2016).

To describe the basis of the development of discriminative acts against certain groups of individuals in the society, there are two theories which can be used; labeling theory and game theory (Tetlock & Mitchell, 2014). The labeling theory takes form as mental classification of the minorities and the use of stereotypes (Lassiter & Ballantyne, 2017). The theory describes the stereotypes in the society as a form of deviance from the norm, which eventually can lead to internal depression and societal stigma that can be observed as an aspect of discernment. It helps in providing the basis that can be used to distinguish between the essential principle of totalitarianism and social equality (Tetlock & Mitchell, 2014).

The ability to discriminate an individual on the basis of implicit bias is a fundamental skill in the human development and employment settings (Price & Payton, 2017). Based on the fact that people are able to be taught in their early stages of development that some objects are safe while others are bad, to distinguish between good and bad, preferable and not preferable, and beautiful from ugly, it this case people are able to categorize items and label them, so to other human beings. According to Spencer, Charbonneau & Glaser (2016), implicit bias can be defined as interpersonal hidden or unconscious mental processes which have substantial bearing o on discrimination. Different research studies have indicated that the various types of discriminations which stem from the implicit biases are growing more pervasive in the workplace and the roles that they play in the disparate treatment cases are developing and evolving.

Additionally, Price & Payton (2017) argue that implicit bias is an evolving form discrimination which is able to create limitations in the employment opportunities for minorities groups based on their races and ethnicity. Implicit bias is not limited to a given geographical or national borders (Gill & Oganesyan, 2015). Based on the findings by the Implicit Bias and Philosophy International Research Project, very many people all over the world have the ability to hold different sorts of implicit bias. Therefore, the issues related to discriminations are not confined to the United States of America along but is it a global concern as witnessed in many international human right treaties (Tetlock & Mitchell, 2014). Implicit bias has been determined to form a neutral part of the human behavior that helps people to categorize people on the basis of perceptions (Lieber, 2012). These associations and categories lead to the development of the stereotypes. People resort to automatic reliance on these stereotypes to understand and judge others (Gill & Oganesyan, 2015).

One of the most problematic sides of implicit bias is the fact that it is able to develop behavior which deviates from an individual’s affirmed or recognized beliefs and values. Even though the cases of old-fashioned or explicit racism are declining in many workplaces around the world, racism, gender and ethnic discrimination, and disparities in employment persist (Krieger & Fiske, 2016). The attitude of racism do often linger but are difficult to detect since they are often unconscious. The main reason why many people are not able to recognize that they discriminate based on the fact that their discriminatory actions do often stem from their implicit biases.

Lassiter & Ballantyne (2017) were able to outline some of the possible reasons for the possible rise in implicit bias in the workplace. First, many companies in the United States of America and all over the world have embraced the use of more team-oriented and less hierarchical approach in the evaluation of the employees. Secondly, the subjective nature of the team-oriented approach has created serious problems with the solo effects (Tinkler, 2012). For example, the employees from the minority groups are evaluated by the colleagues from the majority groups (Price & Payton, 2017). In a situation where there is only one employee from the minority group, the stereotypical assumptions of the minority employee by the majority peers do often seem more pronounced (Tetlock & Mitchell, 2014).

Even though the implicit bias has been observed to be pervasive, the solution to attenuate it may not be complicated. According to Scherer & Lambert (2012), the implicit bias is automatic, it is like a blink of the eye racism which can lead to unintentional discriminations. In a situation whereby the implicit biases are made up of weak automatic responses, the conscious attention may play a significant role in their elimination (Holroyd, 2012). Allowing people to consciously think and feel can make them create a reasoned response which can lead to the decrease in the cases of implicit bias in the society and workplace. According to the study conducted by Lee (2017), it was developed that even though the implicit biases and stereotypes are often universally believed to be the sources of negative mechanisms of discriminations in the workplace, it is important to take into consideration that every person has their stereotypes and biases of others and the fight against implicit bias in the workplace can only progress when everyone in the society honestly acknowledges their blind spots.

The study conducted by Hermanson (2017) on the major causes of discriminations in the workplace found out that the implicit bias and negative stereotypes have promoted the formation of unconscious mental shortcuts in the workplace that largely promoted the formation of many cases of discriminatory employment decisions. The findings were supported by the study conducted by Tinkler (2012) where the 6000 resumes assigned to stereotypically Caucasian and African American names were distributed to 1300 employers. The findings from this study indicated that resumes with stereotypically assigned Caucasian names received more callbacks, registering sixty-five percent callbacks, than those with African American names. Additionally, the study conducted by Blake & Gannon (2012) found that many managers for both governmental and nongovernmental corporations received high job ratings and starting salaries since they were from the male gender. Even though the implicit bias can be used to identify and understand the less visible forms of discriminations in the workplace settings, the theory seems to be incompatible with two frameworks, disparate treatment, and disparate impact, which enhance the development of employment discrimination (Holroyd, 2012).

The Current Research

The current research study is based partially on the study conducted by Mori & Uchida (2015). Nevertheless, this study is composed of different methodological improvements and theoretical advances. Even though Mori & Uchida (2015) were able to make available the preliminary evidence that organizational characteristics played influential roles in creating discrimination in the workplace, this research study will offer a critical analysis of the significance of implicit prejudice in the promotion of discrimination in the workplace. Based on the study by Fevre, Grainger & Brewer (2013), many forms of discriminations that result from the organizational settings are often attributed to the experimenter demand.

Even though the study by Mori & Uchida (2015) used the Implicit Association Test (IAT) to determine the implicit measure of attitude, Verneau, La Barbera & Del Giudice (2016) found this method to be controversial therefore leading to the development of suspicions over the results obtained. To address these criticisms, this study employed a more intelligent and realistic manipulation of organizations. Based on the study by Mori & Uchida (2015), the participants were told to specifically and directly hire people from a given racial group, such as the Whites. In this study, the alteration was more restrained. The rationalization for the cases of discernment was developed via the demographics of the managerial boards of different companies. The idea was supported by the study conducted by Farnsworth, Guzior & Malani (2011) which found that the ability of a given company to tolerate workplace discrimination depended with the homogeneousness of the executive board.

The application of a new implicit quantity of attitude, Affect Misattribution Procedure (AMP), that uses the expressive priming to discover the implicit bias helped in improving the effectiveness of this study. Compared to the IAT, the AMP is not reliant on reaction times to detect the bias hence sidestepping any methodological issues which may affect the IAT (Hazlett & Berinsky, 2017). Additionally, this study applies a modern theoretical framework to determine how implicit biases lead to discrimination in the workplace. Even though the study by Mori & Uchida (2015) tried to demonstrate how implicit bias could lead to discrimination in the workplace, it did not outline the process which enabled this to take place. This research study expanded on their work through the application of JS theoretical framework to explain the actual process through which implicit bias could lead to discrimination in the workplace. The core hypothesis of this study is that the diversity of an organization can foster discrimination by justifying the expression of implicit bias. According to Hazlett & Berinsky (2017), people with pre-existing prejudices will often freely express them in an organization that tolerates discrimination.


H1: The participants will be able to make more discriminatory decisions on hiring in a situation whereby the Company only has White employees compared to when it has both the White and Black employees.

H2: There is a close relationship between the implicit bias and the organizational characteristics; only the participants who possess strong implicit biases will discriminate when it is allowed in the company, for example when the organization is all White.

H3: There will be an interaction between the implicit prejudice and the nature of the organization; only those participants with strong implicit prejudices will show biases when the organization allows discrimination.



The participants for this experiment were 100 (57 females and 43 males) students from the University of Santa Monica, in the United States of America. They were recruited through the online participation pool of the university and were awarded course credits for their participation. In the study, only the White participants were included since the race of the participants was not the major focus of this research study, but could influence the overall results.

Experimental Design

The experiment involved a 2 x 2 design. The demographics of the executive boards of the company was between the subject variables. In this study, the participants were shown images of the company executives which either depicted them as racially mixed or all Whites. The race of the applicants was within the subject variable. In this case, the participants were shown an equal number of Black and White applicants.


The Inbox Task

The inbox task is a workplace simulation which was obtained from the research study by Ogura (2013). The whole process was conducted in a computer. All of the materials which were obtained from the inbox task are contained in the Appendix. during the simulation process; the participants were first provided with information about the fictional company under study. Some of the information included was; description of the history of the company, pictures, and bios of the executive board, and an explanation of the current financial situation of the company. After going through the description of the company, the participants were allowed to take up the role of Todd Folgers, who was the Chief Financial Officer of the company.

The participants were then instructed to reply to all of the daily emails which were contained in his or her (the gender of Baldwin Folgers was not specified) inbox. In the process of replying to these emails, the participants were required to make a lot of decisions on their own. Some of the decisions which they were to make included; deciding on the wages for the new employees, approving requests for the employee's trips to different conferences and approving their vacation requests. The main focus of this study was focused on the decision made by the participants on the basis of hiring recommendations. The first decision which the participants were to make required them to select their preferred candidate who was to replace a retiring member of the upper-level management.

They were to select the candidate after being provided with the dossiers of the eight potential applicants who had been referred for the job. All of the dossiers are included with the inbox materials in the Appendix. in the records; there was information about the educational background, prior work experience, gender, race, and hobbies. Out of the eight applicants, two of them had inferior qualifications. They were used as a manipulation check to determine whether the participants were paying attention to the task they were assigned. The attentiveness of the participants was determined if they were able to rank the two applicants with inferior qualifications last. The participants rated each applicant on a 5-point scale ranging from 1 (should not have been referred) to 5 (excellent referral). After that, they ranked the candidates from the best (position one) to the worst (position eight) qualified for the position.

The Experimental Manipulations

In this study, the first independent variable involved the demographics of the executive board of the company. The images of the members of the company’s executive were included in the organization’s informational materials. A White condition involved a situation whereby all of the executive members are Whites while in the mixed condition, the members of the executive included both the Blacks and Whites. The second independent variable was made up of the race of the applicants. Three of the candidates were Blacks, and three were Whites out of the six applicants with superior qualifications. Their qualifications were well balanced to ensure that only race could be used to differentiate them.

The Affect Misattribution Procedure

The implicit racial bias was determined using the Affect Misattribution Procedure (AMP) that was developed by Payne & Lundberg, (2014). This procedure depends on the test taker misattributing an affective reaction towards one stimulus (for example the Blackface) onto a second, neutral stimulus (for example a Japanese pictograph) to determine the levels of their attitudes towards the initial stimulus. All of the participants were provided with images of White faces, Black faces or a control made of the gray box.

The participants were then expected to judge whether the neutral images were pleasant or unpleasant. The scores of AMP were determined through the computation of the difference in how many times the participants were able to classify the pictures preceded by faces of the Blacks as pleasant as compared to the images preceded by the White faces. The levels implicit bias of the participants were determined by the number of the pictographs primed by White faces that they found to be pleasant. In this case, the higher the number of such pictographs, the higher the level of implicit bias possessed by the participant. Appendix contains an example of the pictographs and faces used in the Affect Misattribution Procedure (AMP).

The Attitude towards Blacks Scale

The influence of implicit bias in the development of racial discrimination was determined by using the Attitude towards Blacks scale (ATB). The ATB scale is composed of seven items which are measured on a 7-point Likert scale, for example, “Discrimination against the Blacks in no longer a problem in the United States of America.” a complete list of the questions used for this procedure are included in Appendix.


The experimental section of the study took place in the laboratory containing twelve computers. Each of the participants was assigned to a computer which they used for receiving instructions from the experimenter. This took place after they had read and signed the consent form. They were informed that the study was set to determine how the style of decision making had potential influences on the decisions made in the workplace. In this situation, they first completed a workplace decision task followed with a series of measures which were designed to evaluate their decision-making style. The participants completed all of the experimental requirements on their computers. Following the completing of the inbox task, the participants took the Affect Misattribution Procedure (AMP). Finally, they completed the Attitudes towards Blacks scale (ATB). The items found in each scale were randomized to prevent the creation of the order effects. All of the measures were channeled into one of the computers in the laboratory. Following the completion of all of the measures, the participants were questioned and excused.


Based on the predictions put across by the hypothesis 1 (H1), the composition of the management of the company would adversely affect the level of implicit bias portrayed by the participants. Precisely, those participants presented with a White company were anticipated to award lower scores to the Black applicants as compared to those who were provided with a mixed company. The testing of this hypothesis (H1) involved the application of a Random Coefficient Model (RCM) whereby the within-subject (Level 1) slope for the race of the applicant (0= Black Applicant; 1= White Applicant) was predicted by the subject demographic (Level 2) variable (0= Mixed Company; 1= White Company). The whole analytical process took place on two separate variables. The first variable was the rank that was given to the individual participant.

Lower number indicated that the participant was highly ranked and hence observed to be more qualified for the job. The second variable relied on the ratings given to each applicant. In this case, higher number indicated that the applicant had superior qualifications. During the test of this hypothesis, a significant 2-way interaction between the demographics of the company’ executive and the race of the applicant based on the applicant ratings was determined (b= 0.15; t (98) = 3.57; p< 0.05). To develop a clear relationship between the two variables, the difference between the average score of each applicant was computed. The approach was important in collapsing the applicant race variable into a single score hence facilitating easy reporting of averages.

Thereafter, the score obtained was used to report averages for all of the hypothesis testing involving the ranking of the applicant. Positive and negative scores shown stronger preference for the White and Black applicant respectively. In support for the previous predictions, there was a strong preference for the White applicants in a company whose executive is composed of many White members (M= 1.92; SD= 1.54). To determine the significant level of implicit bias among the various participants, a one-sample t-test was computed on the differences in rankings in this condition from 0, t (48) =8.69, p<0.05. From the results, it was determined that there was no formed implicit bias in a situation whereby the company was mixed (M= -0.18; SD=1.43). In this situation, the one sample t-test shown that the level of bias in a mixed demographic condition was not meaningfully diverse from 0, t (52) =0.90; p=0.37.

Even though hypothesis 1 (H1) was also tested through the application of the ratings of the participants as the dependent measure, the results obtained from this test did not support H1 since the difference in how the candidates were rated in relation to the experimental conditions could not be determined (b= 0.25; t (98) =1.18; p=0.24). The hypothesis 2 (H2) was of the prediction that the implicit racial attitude and discrimination of the participants could be demonstrated by the degree of bias in the inbox task. The applicability of H2 was measured through the application of ATB. In this case, it was determined that there would be the formation of a three-way interaction whereby the level of implicit bias of the participant, the demographic composition of the executive board of the company and the race of the applicant would lead to the prediction on how much the participants were able to discriminate.

The implicit bias could be used to predict the occurrence of discrimination against the Black applicants when the management of the company is made up of Whites. Nevertheless, it could not be used for predicting the level of discrimination in a mixed company (containing both Blacks and Whites).the RCM was used in the testing for the applicability of H2. It was conducted on Level 1 slope for the race of the applicant (0= Black applicant; 1= White applicant) hence leading to the prediction of Level 2 slope contained between the subject variables. The three-way relationship between the measure of the implicit bias on racism, race of the applicant and the demographic environment of the company was not expressively tested (b= 0.03; t (97) =0.43, p=0.67), hence failing to prove the applicability of H2.

In a more advanced manner, there was no meaningful correlation between the explicit and implicit determinants of the biases r (100) =0.06, p=54. The application of the AMP was able to determine the implicit racial attitudes of the applicant, an observation that was predicted by hypothesis 3 (H3). In this case, there was the formation of a three-way interaction between the levels of implicit bias of the applicant, demographic composition of the executive board of the company and the race of the applicants. All of these three variables jointly played a role in determining the levels of discriminations as displayed by the participants. Following the computation of the RCM, the three-way relationship between the race of the applicant, demographic condition of the company and the AMP was found to be significant (b= 0.18; t (96) =2.30; p<0.05).

To clearly demonstrate the relationship between these three variables, the difference in score between the average ranking of the White and Black candidates was computed. The result led to the condensation of the race of the applicant variable into one score which could be easily reported. Positive and negative scores showed a stronger preference for the White and Black candidates respectively. Figure 1 shows the interaction between these variables. Form Figure 1, it can be denoted that AMP could provide for the prediction for the rankings of the candidates in the company composed of the White executive members but failed to show the same results in the company executive composed of both the Black and the White members. From the results, it is justifiable to note that the participants based their actions on their biases in a situation where the demographics provided a rationalization.


The results of the study indicated that there is a significant relationship between the demographics of a company and the level of implicit bias which later leads to discrimination. In most of the workplaces with diverse composition of members of the executive, there are little cases of discrimination since there are low levels of implicit bias against individuals from a specific ethnic group, gender, race or physical body appearances (Roberson & Parks, 2014). From the study, it is justifiable to note that the participants were more likely to discriminate in a situation whereby the executive members of the company were all White as compared to a situation whereby the executive members were from both the White and Black racial group. The results from this study agree with the findings from the research work conducted by Jolls & Sunstein, (2016).

From that study, it was established that one of the major factors that lead to the development of implicit bias among different individual is the environment from which they were raised (Banks, Eberhardt & Ross, 2016). Furthermore, the study showed that there are higher probabilities of discriminating against a Black individual if he or she is in a company which is largely dominated by the Whites. Similarly, the likelihood of discriminating a woman in a workplace which is dominated by male gender is very high as compared to a company where there is a balanced representation of both of the genders (Crow, Fok & Hartman, 2015). Based on the fact that the explicit bias could be largely influenced by the social attractiveness concerns of the participants which made it be an inaccurate determinant of prejudice as indicated by (Sekaquaptewa et al., 2013), the study could only determine the relationship between the implicit bias of the participants and their abilities to discriminate against the applicants.

The main purpose of this study was to show how the composition of a company can interact with prejudice of a person, leading to the formation of implicit bias that causes discrimination in the workplace. According to the study conducted by Zhu (2013); Regan & Hamstra (2012) and Lee et al., (2012), it was established that manipulation of the company using two criteria such as through demographics and portrayal of its leadership could effectively lead to the development of discriminative actions against different employees within a given organization. The findings of this study were found to agree with the study conducted by Song et al., (2013) and Vreven (2016) which demonstrated that in an organization where discrimination is allowed, most of its employees would be from almost one ethnical, gender or racial group.

In this case, if there are some employees who are from the perceived minority groups, the probability of them being discriminated against would be very high. The implicit bias has the ability to cause disadvantageous effects on both of the employees and the organization at large (Stagg et al., 2013). In many situations, just as illustrated with the findings from the study, the implicit bias can pose a lot of challenges on the diversity and inclusion initiatives which the company tries to implement (Sawchuk, 2014; Sitzman, 2016; Zhu, 2012). The issue can be demonstrated in a situation whereby the company is pushing for diversity in its employees for the purpose of creating an all-inclusive image, but the hiring manager has an unconscious bias against the hiring of employees from different ethnical or racial group.

The approach will not only create a problem for the job seekers of that company but the company at large since it will fail to display inclusivity in its operations, a factor which is not good for business (Zhu, 2012). Different research studies have shown that many hiring managers who discriminate against their employees and job applicants, who are not from their preferred ethnical or racial groups, have negatively developed stereotypes, unfamiliarity and selfishness traits against the disadvantaged groups (Stagg et al., 2013; Wagner & Frost, 2013).

The hypotheses of the study were important in illustrating how the participants were able to engage in discriminatory actions when it was justified by the organization. According to the results obtained from the study conducted by Kelly, Young & Clark (2013), it was established that different employees of various organizations are to significantly portray more discrimination actions when both the demographics and the communications of the company indicate that discrimination is acceptable. The analytical studies on the effects of implicit bias by Malos (2017) and Gill (2014) had shown that there are multiple features which exist in a given organization that can interact with each other, therefore leading to exponentially significant effects on discrimination.
Even though the conditions and characteristics of the company may have played a vital role in determining the level of discrimination in a given workplace, the degree of discrimination would be largely determined through the examination of the pre-existing prejudices and implicit biases that an individual possess against a certain group of people. The significant relationship between the implicit and the explicit bias in a given workplace could be demonstrated through the analysis of the characteristics of the company such as communication and demographics (Cunningham & Macrae, 2013). In a situation whereby there was no clear indication that the company under investigation provided room for discriminatory actions against a given group of individuals, there was no significant correlation between the implicit bias and the discrimination of the employees and other job seekers.
Seemingly, following the justification of the discriminatory actions by the company, the degree of the implicit bias of the employees could be in the determination of the extent of how they discriminated the other employees (Duguid & Thomas-Hunt, 2015). This relationship can also be used in the determination of the degree of explicit bias among different employees in an organization. According to the study conducted by Cadinu, Latrofa & Carnaghi (2013), it was determined that there are very many people who apply the implicit bias to discriminate against the other people in the same workplace, not because they would have any financial gain but because the action makes them feel happier than before.
One of the potential reason behind the formation and development of implicit bias in a workplace is based on the fact that the aspiration to uphold homogeneous groups which are developed by the demographic alteration that was created from an honest ideology the minority groups such as the Blacks would not be happy in the company (Lorenzi-Cioldi, 2016). This type of belief has been proven by the study conducted by Simon, Glassner-Bayerl & Stratenwerth (2013) to exist independently within a prejudiced attitude. The desire by different individuals to create their groups which would make them develop a sense of belonging has been documented in the field of psychology and illustrated by (Keller, 2014; O'Connell, Bowden & Ferriell, 2017 and Williams & Spencer-Rodgers, 2013).
Therefore it can be used as a rational alternative for explaining the results that were obtained from this research study. Even though there are very many research studies that have indicated that there are several relationships between the implicit bias and the increase in the number of discriminatory cases in the workplace, there are still some research studies which have tried to prove that there is no such direct linked between these two variables. According to Madon et al., (2016), it can be deduced that the implicit bias cannot often lead to discriminatory actions in the workplace since the occurrence of discernment is a creation of the human mind which can be avoided if the affected individuals try to cope with the situation rather than lamenting every time. Even though Madon et al., (2016) did not illustrate how this can be applicable, their argument was faced with a lot of hurdles by its ability to hold water.
According to the results, there was an active link between the determinants of levels of implicit bias and the eligibility of the White applicants in a White dominated workplace. To argue against the possibility of the occurrence of direct association between the inherent bias and the discriminatory actions in the workplace, it would be justifiable to note that if the participants favored the White candidates out of the desire for the development of homogeneity in the company (Krull & Silvera, 2013). Therefore it possible that even those participants with low levels of implicit bias would prefer the White candidates in a White demographic organization. In this case, it is defensible to note that the actions which were taken by the participants were driven by the implicit bias rather than the need to maintain homogeneousness in the company.
The results of the study have significant methodological and theoretical suggestions. The importance of this study is based on the fact that it helps in demonstrating the possible relationship which might occur between the implicit bias and discriminatory actions in the workplace (Lerman & Sadin, 2014). As shown in this research study, there were justifications that the occurrence of implicit prejudices towards the Blacks led to discriminatory actions during the hiring process (Eyssel & Hegel, 2012). Therefore, the findings from this research study agree with the study conducted by Bell & Burkley (2014) that was able to illustrate the efficacy of implicit bias as the predictor of human behavior in a given environment such as the workplace.
Even though both the explicit and implicit prejudices could be used to determine the behavior and an individual, the AMP and implicit biases provided for the best framework that could be used in predicting the behaviors of an individual that can eventually lead to discriminatory actions in the workplace. In that case, this research study can be used to demonstrate the nature of the discriminatory actions in the workplaces (Dodson, 2013). Discrimination in the workplace can be considered to be self-reinforcing. For example, if the workplace is predominantly dominated by the White employees, there could be a justification that the levels of discrimination are as a result of the existing racial composition in that given company. The diversity of the workplace can be considered to be self-perpetuating.
This nature of diverseness of the workplace can be used in demonstrating the importance of inclusivity, not only as an approach of bringing new perspectives to the workplace but as a method of creating fairness in the hiring process hence reducing the cases of discrimination (Simon, Glassner-Bayerl & Stratenwerth, 2013). Additionally, the approaches by different companies which can be used to determine that they are in support of discriminatory actions in the workplace are dangerous hence it is important for all of the companies around the world to be mindful of any step that they take which can be used to show that they are in support of any discriminatory action (Dodson, 2013).


The attitudes and stereotypes which different people develop as a result of implicit bias can lead to discriminatory actions in the workplace. The most discriminated against are the people who are from the perceived minority or disadvantaged groups in the society. For example, it has often been observed that some White people believe that the Blacks do not have anything substantial to offer in the workplace. With such stereotyping ideas, the likelihood of discriminating the Blacks, either in the workplace or during the job interview, is very high. Such discriminatory actions have been identified to be the main cause of glass ceiling among these minority groups and women in the workplace.
These negative effects of implicit bias in the workplace have led to the need to develop the most appropriate approach which can be used combat it. Many companies around the world are in the recent days trying to ensure that their workforces are as diverse as possible. To ensure the diversity, the hiring teams of those companies do ensure that they hire only qualified employees regardless of their gender, ethnical or racial orientation. Becoming an all-inclusive company is also another reason which pushes these company to become diverse, a factor that is good for business. The study conducted by Simon, Glassner-Bayerl & Stratenwerth (2013) shown that workforces composed of people from different racial and ethnical groups were more productive as compared to those composed of one major racial or ethnical groups.
A healthy relationship among the employees in a given workplace is a very important factor which will determine the productivity of each employee. The constant application of prejudiced attitudes to judge fellow employees is not an effective way to determine their capabilities but rather an approach that can make them develop unhealthy relationship amongst themselves. Implicit bias is an international issue which is not confined to a specific nationality. Therefore it is a global phenomenon that can affect both the employees and the employers from any part of the world. Based on the fact that the nature of the human beings is focused on some appearance preconceptions, this problem will only continue to grow in importance.  


Banks, R., Eberhardt, J., & Ross, L. (2016). Discrimination and Implicit Bias in a Racially Unequal Society. California Law Review, 94(4), 1169.
Bell, A., & Burkley, M. (2014). “Women Like Me Are Bad at Math”: The Psychological Functions of Negative Self-Stereotyping. Social and Personality Psychology Compass, 8(12), 708-720.
Blake, E., & Gannon, T. (2012). Investigating the implicit theories of rape-prone men using an interpretative bias task. Legal and Criminological Psychology, 19(1), 40-53.
Cadinu, M., Latrofa, M., & Carnaghi, A. (2013). Comparing Self-stereotyping with In-group-stereotyping and Out-group-stereotyping in Unequal-status Groups: The Case of Gender. Self and Identity, 12(6), 582-596.
Crow, S., Fok, L., & Hartman, S. (2015). Moving from Bias to Discrimination: A Study of Perceptions of Homosexuals in the Workplace. Journal of Individual Employment Rights, 4(4), 319-336.
Cunningham, S., & Macrae, C. (2013). The color of gender stereotyping. British Journal of Psychology, 102(3), 598-614.
Dodson, L. (2013). Stereotyping Low-Wage Mothers Who Have Work and Family Conflicts. Journal of Social Issues, 69(2), 257-278.
Duguid, M., & Thomas-Hunt, M. (2015). Condoning stereotyping? How awareness of stereotyping prevalence impacts expression of stereotypes. Journal of Applied Psychology, 100(2), 343-359.
Eyssel, F., & Hegel, F. (2012). (S) He’s got the Look: Gender Stereotyping of Robots1. Journal of Applied Social Psychology, 42(9), 2213-2230.
Farnsworth, W., Guzior, D., & Malani, A. (2011). Implicit Bias in Legal Interpretation. SSRN Electronic Journal.
Fevre, R., Grainger, H., & Brewer, R. (2013). Discrimination and Unfair Treatment in the Workplace. British Journal of Industrial Relations, 49, s207-s235.
Gill, M. (2014). When information does not deter stereotyping: Prescriptive stereotyping can foster bias under conditions that deter descriptive stereotyping. Journal of Experimental Social Psychology, 40(5), 619-632.
Gill, R., & Oganesyan, R. (2015). The Ideal Judge: How Implicit Bias Shapes Assessment of State Judges. SSRN Electronic Journal.
Girvan, E. (2015). On Using the Psychological Science of Implicit Bias to Advance Anti-Discrimination Law. SSRN Electronic Journal.
Hatzis, N. (2013). Personal Religious Beliefs in the Workplace: How Not to Define Indirect Discrimination. The Modern Law Review, 74(2), 287-305.
Hazlett, C., & Berinsky, A. (2017). Stress-testing the affect misattribution procedure: Heterogeneous control of affect misattribution procedure effects under incentives. British Journal of Social Psychology.
Hermanson, S. (2017). Implicit Bias, Stereotype Threat, and Political Correctness in Philosophy. Philosophies, 2(2), 12.
Holroyd, J. (2012). Responsibility for Implicit Bias. Journal of Social Philosophy, 43(3), 274-306.
Jolls, C., & Sunstein, C. (2006). The Law of Implicit Bias. California Law Review, 94(4), 969.
Keller, C. (2014). Effect of Teachers' Stereotyping on Students' Stereotyping of Mathematics as a Male Domain. The Journal of Social Psychology, 141(2), 165-173.
Kelly, E., Young, A., & Clark, L. (2013). Sex stereotyping in the workplace: A manager's guide. Business Horizons, 36(2), 23-29.
Krieger, L., & Fiske, S. (2016). Behavioral Realism in Employment Discrimination Law: Implicit Bias and Disparate Treatment. California Law Review, 94(4), 997.
Krull, D., & Silvera, D. (2013). The stereotyping of science: superficial details influence perceptions of what is scientific. Journal of Applied Social Psychology, 43(8), 1660-1667.
Lassiter, C., & Ballantyne, N. (2017). Implicit racial bias and epistemic pessimism. Philosophical Psychology, 30(1-2), 79-101.
Lee, B., Peng, J., Li, G., & He, J. (2012). Regional Economic Disparity, Financial Disparity, and National Economic Growth: Evidence from China. Review of Development Economics, 16(2), 342-358.
Lee, C. (2017). Awareness as a First Step toward Overcoming Implicit Bias. SSRN Electronic Journal.
Lerman, A., & Sadin, M. (2014). Stereotyping or Projection? How White and Black Voters Estimate Black Candidates' Ideology. Political Psychology, 37(2), 147-163.
Lieber, L. (2012). The hidden dangers of implicit bias in the workplace. Employment Relations Today, 36(2), 93-98.
Lorenzi-Cioldi, F. (2016). Self-stereotyping and self-enhancement in gender groups. European Journal of Social Psychology, 21(5), 403-417.
Madon, S., Guyll, M., Hilbert, S., Kyriakatos, E., & Vogel, D. (2016). Stereotyping the Stereotypic: When Individuals Match Social Stereotypes. Journal of Applied Social Psychology, 36(1), 178-205.
Malos, S. (2017). Appearance-based Sex Discrimination and Stereotyping in the Workplace: Whose Conduct Should We Regulate? Employee Responsibilities and Rights Journal, 19(2), 95-111.
Mori, K., & Uchida, A. (2015). Paper-Based Affect Misattribution Procedure for Implicit Measurement. Psychology, 06(12), 1531-1538.
O'Connell, L., Bowden, C., & Ferriell, A. (2017). Must stereotyping be extreme to be harmful? The relationship between degree of stereotyping and prejudice. Sociological Spectrum, 17(1), 103-113.
Ogura, T. (2013). A variable selection method in principal canonical correlation analysis. Computational Statistics & Data Analysis, 54(4), 1117-1123.
Payne, K., & Lundberg, K. (2014). The Affect Misattribution Procedure: Ten Years of Evidence on Reliability, Validity, and Mechanisms. Social and Personality Psychology Compass, 8(12), 672-686.
Price, J., & Payton, E. (2017). Implicit Racial Bias and Police Use of Lethal Force: Justifiable Homicide or Potential Discrimination? Journal of African American Studies, 21(4), 674-683.&
Puddifoot, K. (2015). Accessibilism and the Challenge from Implicit Bias. Pacific Philosophical Quarterly, 97(3), 421-434.
Regan, D., & Hamstra, S. (2012). Shape discrimination for rectangles defined by disparity alone, by disparity plus luminance and by disparity plus motion. Vision Research, 34(17), 2277-2291.
Roberson, Q., & Parks, G. (2014). Michelle Obama: Inter-sectionalism, Implicit Bias, and Third-Party Associative Discrimination in the 2008 Election. SSRN Electronic Journal.
Sawchuk, P. (2014). Trade union‐based workplace learning: a case study in workplace reorganization and worker knowledge production. Journal of Workplace Learning, 13(7/8), 344-351.
Scherer, L., & Lambert, A. (2012). Implicit race bias revisited: On the utility of task context in assessing implicit attitude strength. Journal of Experimental Social Psychology, 48(1), 366-370.
Sekaquaptewa, D., Espinoza, P., Thompson, M., Vargas, P., & von Hippel, W. (2013). Stereotypic explanatory bias: Implicit stereotyping as a predictor of discrimination. Journal of Experimental Social Psychology, 39(1), 75-82.
Simon, B., Glassner-Bayerl, B., & Stratenwerth, I. (2013). Stereotyping and Self-Stereotyping in a Natural Intergroup Context: The Case of Heterosexual and Homosexual Men. Social Psychology Quarterly, 54(3), 252.
Sitzman, K. (2016). Workplace Germs. Workplace Health & Safety, 54(7), 336-336.
Song, X., Yang, L., Liu, Z., & Liao, L. (2013). Fast disparity estimation algorithm based on features of disparity vector. Journal of Computer Applications, 32(6), 1856-1859.
Spencer, K., Charbonneau, A., & Glaser, J. (2016). Implicit Bias and Policing. Social and Personality Psychology Compass, 10(1), 50-63.
Stagg, S., Sheridan, D., Jones, R., & Speroni, K. (2013). Workplace Bullying: The Effectiveness of a Workplace Program. Workplace Health & Safety, 61(8), 333-338.
Tetlock, P., & Mitchell, G. (2014). Implicit Bias and Accountability Systems: What Must Organizations Do to Prevent Discrimination? Research in Organizational Behavior, 29, 3-38.
Tinkler, J. (2012). Controversies in Implicit Race Bias Research. Sociology Compass, 6(12), 987-997.
Verneau, F., La Barbera, F., & Del Giudice, T. (2016). The Role of Implicit Associations in the Hypothetical Bias. Journal of Consumer Affairs, 51(2), 312-328.
Vreven, D. (2016). 3D shape discrimination using relative disparity derivatives. Vision Research, 46(25), 4181-4192.
Wagner, H., & Frost, B. (2013). Disparity-sensitive cells in the owl have a characteristic disparity. Nature, 364(6440), 796-798.
Williams, M., & Spencer-Rodgers, J. (2013). Culture and Stereotyping Processes: Integration and New Directions. Social and Personality Psychology Compass, 4(8), 591-604.
Zhu, C. (2012). Book Review: China's Changing Workplace: Dynamism, Diversity and Disparity China’s Changing Workplace: Dynamism, Diversity and Disparity Edited by Sheldon Peter, Kim Sunghoon, LiYiqiong and Warner Malcolm (2011) Routledge (Taylor & Francis Group), London and New York. pp. xx+326 Hardback: ISBN 978-0-415-58454-8 RRP: AUD 155. The Economic and Labor Relations Review, 23(2), 141-144.
Zhu, Y. (2013). China's changing workplace: dynamism, diversity and disparity. Asia Pacific Business Review, 19(1), 142-143.

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