I helped a university department develop a small DSS to analyze and rank students who applied to a specialized program. Some of the information was numeric and could easily be processed directly by the system (e.g., gradepoint average, standardized test scores). Other information required the faculty to make subjective judgments among the students (e.g., extracurricular activities, work experience). The users entered their evaluations of the subjective information via several data analysis screens in which the students were listed in alphabetical order.

To make the system easier to use, it was designed so that the reports listing the results of the analysis were also presented in alphabetical order by student name rather than in order from the highest-ranked student to the lowestranked student. In a series of tests prior to installation, the users selected the wrong students to admit in 20 percent of the cases. They assumed, wrongly, that the students listed first were the highest-ranked students and simply selected the first students on the list for admission. Neither the title on the report nor the fact that all the students’ names were in alphabetical order made users realize that they had read the report incorrectly.

Question This system was biased because users assumed that the list of students implied ranking. Suppose that you are an analyst charged with minimizing bias in this application.
Where else may you find bias in the application? How would you eliminate it?