Four-Fifths Rule: Fair Employment Selection

job analysis

The Four-Fifths Rule is a term that refers to a guideline for fairness in hiring practices in the USA.  Because tests are often used in making hiring decisions, the Four-Fifths Rule applies to them so it is an important aspect of assessment in the workforce, but it also applies to other selection methods, such as interviews or biodata.  It is important not only because violations could lead to legal entanglements, but because achieving a diverse and inclusive workforce is a goal for most organizations.

What is the Four-Fifths Rule?

The Four-Fifths Rule, also known as the 80% Rule, is a statistical guideline established by the Equal Employment Opportunity Commission (EEOC) in the United States, used to evaluate whether a selection process leads to adverse impact against any specific group. The rule comes into play when comparing the selection rates of different demographic groups within an organization, aiming to identify potential disparities. According to the EEOC, a selection rate for any group that is less than four-fifths (or 80%) of the rate for the group with the highest selection rate may indicate adverse impact.

This applies to any organization that is hiring in the United States, even if that organization is based overseas.  A great example of this is a 2023 lawsuit against a Chinese company that was hiring US employees with unfair practices.

The Four-Fifths Rule serves as a vital benchmark for organizations striving for diversity and inclusion. By highlighting disparities in selection rates, it helps employers identify and rectify potential discriminatory practices. This not only aligns with ethical considerations but also ensures compliance with anti-discrimination laws, fostering an environment that values equal opportunity for all.

four-fifths rule diversity in pre-employment testing

Calculation Method

First, determine the selection rate for each demographic group by dividing the number of individuals selected from that group by the total number of applicants from the same group. Next, compare the selection rates of different groups. If the selection rate for any group is less than 80% of the rate for the group with the highest selection rate, it triggers further investigation into potential discrimination.

Example:

Group A has 500 applicants and 100 were selected; a 20% selection rate

Group B has 120 applicants and 17 were selected; a 14.17% selection rate

The ratio is 0.1417/0.20 = 0.7083.  This is below 0.80, so the procedure is biased against Group B.

Note that we are focusing on rates and not overall numbers.  Clearly, Group B has far fewer selected, but the rates are not too different at 20% and 14.17% – but different enough that this test would be under scrutiny.

Implementing the Four-Fifths Rule in Practice

To implement protections against the Four-Fifths Rule effectively, organizations must adopt proactive measures. Regularly monitoring and analyzing selection rates for different demographic groups can help identify trends and address potential issues promptly. Furthermore, organizations should establish clear policies and procedures for hiring, ensuring that decision-makers are well-informed about the Four-Fifths Rule and its implications.

Note that this is only a guideline for flagging potential adverse impact.  It does not mean the selection method will be stricken.  Consider a physical fitness test for firefighters; it most definitely produce lower results for people aged 60 and over, but physical fitness is unarguably a job requirement, so if the test has been validated it will most likely be upheld.

How does AI fit into this?

Artificial intelligence (AI) is governed by the Four-Fifths rule as any other selection approach.  Do you use AI to comb through a pile of resumes, and flag those worthy of an interview?  This is then a selection procedure, and if it were to be found that it was biased against a subgroup, you would be liable.

Conclusion

In the pursuit of a fair and inclusive workplace, the Four-Fifths Rule is a valuable tool for organizations committed to diversity. Moreover, it is a legal guideline for any organization that hires in the United States.  It is legally required that your organization follow this guideline with respect to pre-employment assessments as well as any other selection procedure.

Note: ASC does not provide legal advice, this is only for educational purposes.

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Nathan Thompson, PhD

Nathan Thompson earned his PhD in Psychometrics from the University of Minnesota, with a focus on computerized adaptive testing. His undergraduate degree was from Luther College with a triple major of Mathematics, Psychology, and Latin. He is primarily interested in the use of AI and software automation to augment and replace the work done by psychometricians, which has provided extensive experience in software design and programming. Dr. Thompson has published over 100 journal articles and conference presentations, but his favorite remains https://scholarworks.umass.edu/pare/vol16/iss1/1/ .
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