This article highlights the existence of predictive bias in standardized testing.

What is it about?

These results have significant DEI implications in organizations because they demonstrate how standardized assessments can systematically underpredict or overpredict performance for individuals from different demographic groups, thereby violating fairness and equal opportunity principles. The article clearly shows the need for organizations to implement more equitable assessment and selection methods, ensuring that predictive models do not reinforce historical discrimination or systemic barriers to success. By providing empirical evidence of intercept- and slope-based predictive biases, the study highlights how traditional testing methods may disadvantage certain underrepresented groups, reinforcing systemic barriers to success. In sum, based on this study’s results, organizations must reevaluate their reliance on standardized assessments, adopt alternative selection strategies, and implement bias-mitigation techniques to ensure more equitable hiring, promotion, and admissions processes.

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Why is it important?

This article highlights the existence of predictive bias in standardized testing and demonstrates how it disproportionately impacts individuals based on protected characteristics such as race, ethnicity, and other demographic factors. By identifying intercept- and slope-based predictive biases in testing, the study provides empirical evidence that certain groups experience systematic under- or overprediction of their performance, influencing selection decisions and opportunities (e.g., college admissions and job offers). By mapping statistical causes of predictive bias onto psychological and contextual mechanisms, the article integrates multiple research domains and fields of study, improves our understanding by providing a clear theory-based explanation for different types of bias, and charts a path that will guide future research efforts on improving fairness in testing for many years to come.