Glossary
Adverse impact
Adverse impact is when a hiring practice that looks neutral selects members of a protected group at a substantially lower rate than others.
Adverse impact, also called disparate impact, doesn’t require anyone to intend discrimination. A requirement or test that treats everyone the same on paper can still screen out one group far more than another. In many jurisdictions, that difference needs to be justified by the needs of the job.
This entry explains a concept. It isn’t legal advice. Speak to an employment lawyer about the rules where you hire.
The four-fifths rule
In the US, the Uniform Guidelines on Employee Selection Procedures, used by the EEOC and other agencies, offer a rule of thumb. Compare the selection rate of each group with the selection rate of the group selected most often. If a group’s rate is less than four-fifths (80%) of the highest rate, that is generally treated as evidence of adverse impact worth examining.
A worked example
Assume a screening step with these results:
| Group | Applicants | Passed | Selection rate |
|---|---|---|---|
| Group A | 100 | 60 | 60% |
| Group B | 50 | 20 | 40% |
Group B’s rate divided by Group A’s is 40 ÷ 60, or about 0.67. That’s below 0.8, so under the rule of thumb this step would warrant a closer look.
Limits of the rule
- Small numbers mislead. With 10 applicants in a group, one person changes the ratio a lot. Statistical tests are often used alongside the ratio.
- It’s a signal, not a verdict. Passing the four-fifths check doesn’t prove a step is fair, and failing it doesn’t prove it’s unlawful.
- Job-relatedness matters. A step with adverse impact may be defensible if it measures something the job genuinely requires, and there’s no less discriminatory alternative that works as well.
Where it creeps in
- Degree requirements for jobs that don’t need one.
- Keyword filters tuned on past hires.
- Scoring accent, fluency or grammar when the job doesn’t depend on them.
- Short time limits that disadvantage people with slower connections or disabilities.
- Scheduling that only works for people with flexible days.
Checking your own process
Where it’s lawful, collect demographic data voluntarily and keep it separate from hiring decisions. Look at pass rates at each stage, especially automated ones. Some laws, such as New York City’s rules on automated employment decision tools, require bias audits that report impact ratios for certain tools. A pass mark is one of the first places to check.