Confronting Pattern Recognition and Embracing Diversity

In business and many industries, we create patterns to reduce errors and standardize production. However this same behavior, when taken too far can create unintended negative consequences such as bias. As we hire new employees, invest in new businesses, and offer promotions, how do we ensure that we are making impactful decisions that impact profit, innovation, efficiency, diversity and inclusion? Do we have tendencies, stereotypes, and beliefs that reinforce non-inclusive workplaces? Research indicates that everyone has their own set of unspoken beliefs called the “unconscious bias” (Hewett, 2019). These biases support the use of what Denise Hewett calls “pattern matching” (Hewett, 2019) which reinforces race, gender, educational, and economic disparities in the workplace. In this Insight article, we seek to understand pattern matching, what causes it, how is it used, and how can we prevent erroneous pattern matching to create a more inclusive and profitable workplace.

“Innovation does not fit a pattern” - Denise Hewett, CEO of Scriptd

What is Pattern Matching?

Pattern Matching is used in both algorithms and human nature. In coding and algorithm creation pattern matching is defined as, “the process of checking whether a specific sequence of characters/tokens/data exists among the given data” (educative, n.d). Humans use pattern matching in decision-making processes in much of the same way. John Wiese states that in human nature “pattern matching is the cognitive process by which your brain connects current sensory stimulation with past experience” (Wiese, 2020). In both forms of pattern matching, already learned information is applied to present situations or data. While this concept seems logically sound, it has its own pitfalls and drawbacks. For example, Stereotypes are an ever-present shortcoming in society. They marginalize individuals to the specific characteristics that are often associated with their race, gender, or other social groups. Oftentimes these stereotypes do not represent the individual but influence first impressions and opinions of the individual. When these stereotypes infiltrate the thought process of human beings and qualifications within algorithms, discriminatory pattern matching sequences can unintentionally take place. Because of this, pattern matching has morphed into the unintentional application of learned stereotypes and biases on employees, job applicants, and business practices in general.

What causes errors in Pattern Matching?

There are two essential components of pattern matching errors: stereotypes and unconscious bias. The combination of these two factors creates the foundation for discriminatory pattern matching.

“Stereotypes lose their power when the world is found to be more complex than the stereotype would suggest…” - Ed Koch, Former United States Representative


Stereotypes, according to Dr. Saul Mcleod, are the “over generalized belief about a particular group or class of people.” (2017). Dr. Mcleod states that stereotyping causes us to believe that an individual “has a whole range of characteristics… that we assume all members of that group have” (2017). An example of a stereotype would be the belief that women perform better in businesses focused on service and health (Hewett, 2019). This stereotype cannot accurately be applied to all women, however, it often is. In her speech, Denise Hewett states that investors are more likely to invest in women-owned businesses that skew towards stereotypically female fields such as health and wellness (Hewett, 2019). However, the existence of a stereotype in a society does not always indicate the use of discriminatory policies for each organization. Stereotypes must be left unconfronted by the individuals making decisions for an organization in order to increase discrimination. These unconfronted stereotypes embed themselves in the unconscious bias of business leaders and investors, further supporting discriminatory pattern matching practices.

Unconscious Bias

Unconscious biases are beliefs subconsciously held by individuals. They are not acknowledged and are learned over time through a “combination of data, knowledge, and experience[s]” (Bryant, 2019). This “learned data” can become convoluted with social stereotypes and personal assumptions about social groups (Bryant, 2019). Katherine Bryant of The Progress Partnership states that the “unconscious bias distorts our perception of risk and causes us to be over-reliant on initial data, to disregard information that contradicts our existing beliefs, and engage in potentially damaging group think” (2019). With over 250 recorded cognitive biases, it is essential that companies create safeguards against the biases (Bryant, 2019). An example of one of these biases is the salary history bias. The Center for American Progress states that “employers’ reliance on salary history in hiring and compensation decisions is a textbook example of structural bias” (Bleiweis, 2021). This bias thrives off of the stereotype that job applicants who were paid more in previous positions are better employees. This view is inaccurate as salaries are often dependent on local cost-of-living standards, and has little relevance to applicant job performance when compared to promotions and supervisor reports. This bias specifically reinforces wage gaps between majority and minority groups, and in many states acting on this bias and asking job applicants, their salary history is now considered an illegal business practice (Bleiweis, 2021). Unconscious biases, like the salary history bias, are fueled by stereotypes and when left unacknowledged further promote discriminatory pattern matching.

How is Pattern Matching Used?

Pattern matching has the potential to influence almost any area of business in which decisions are made. However, there are two specific areas in which discriminatory practices can be inadvertently reinforced with pattern matching: Hiring and Promotion Standards as well as Investment Standards.