Testing and the Paradoxes of Fairness

How can admissions officers, employers, and scholarship committees maximize the accuracy of prediction of individual performance while minimizing adverse impact due to group differences? Testing offers a straightforward solution to the first half of this problem. Tests are the best way to predict how someone will perform in school, in the military, in medicine, or while controlling airline traffic and flying a plane. Tests are also useful beyond personnel selection, such as for selection of a college major or courses. However, the other side of this problem is more complex. Using tests is always accompanied by group differences that could result in continued systemic discrimination by limiting opportunities for those who are marginalized. This book charts an approach to using tests that incorporates evidence, transparency, and societal values to maximize efficiency and fairness.

Howard Wainer is an award-winning American statistician and research scientist. His areas of work include testing, graphical methods for data analysis and communication, and robust statistical methodology. He has served on the faculty of the University of Chicago, at the Bureau of Social Science Research during the Carter Administration, and as Principal Research Scientist in the Research Statistics Group at Educational Testing Service for twenty-one years, and in 2016, he retired after fifteen years as Distinguished Research Scientist at the National Board of Medical Examiners.

Daniel H. Robinson is the K-16 Mind, Brain, and Education Endowed Chair at the University of Texas at Arlington. He received his Ph.D. in Educational Psychology in 1993 from the University of Nebraska where he majored in both learning/cognition and statistics/research. He previously taught at Mississippi State University, the University of South Dakota, the University of Louisville, the University of Texas at Austin, and Colorado State University. He has served as department chair, director, and associate dean of research.