Big data, aka large data sets, is used to aid communication methodology practices every day. For example, Facebook takes cookies and internet history to tailor ads to your specific interests and even Chicago police use an algorithm to predict crime before it happens, yes… just like Minority Report. But sometimes the use of big data can bring about an unwanted outcome.
Employers have started prioritizing their search for new talent and they need to sift through thousands of resumes in a manageable fashion. Programs are being used to create lists of potential employees on the internet and predict job success. This sounds good and nice but in reality there is potential for these programs to aid in discrimination based on race, sex or other protected classes.
Bloomberg delves into this idea of formulaic discrimination where employers focus their criteria on job retention and performance. The problem arises where the program may be set to replicate their current workforce demographic by searching for resembling features of their top rated performers. That type of search can end up under representing woman, racial minorities, or other protected persons.
These types of suits can be difficult. The employer may only be focused on their efficiency criteria and may not be aware of the discriminatory effect. Another difficulty arises where discovery of these programs, created by the company, may be protected under trade secret protection laws for their formulas.
Programs only do what humans tell them to do, therefore employers should account for the applicable laws and be clear about what they want their programs to conclude. Using these programs to find that “perfect match” employee should take into consideration of all the criteria when hiring, including non-discriminatory practices.