As technology progresses and people spend more of their time online, background checks can rely on Big Data and algorithms to get the job done quicker. “Big Data” refers to the practice of using advanced computing power to collect, analyze, and present lots of information in a format that reveals patterns and trends. These data sets are very large and complex, often with thousands or millions of data points. In the world of background checks, Big Data helps employers and landlords hone in on the best choices for hires or tenants. It can be tedious to review and assess each background check individually, and the information isn’t always presented in a simple, intuitive format.
Big Data hopes to change this part of the background check process. Background check providers can tap into large pools of data (employment history, home addresses, education, criminal background and many more) to quickly and efficiently get the best possible answer as soon as possible. Using algorithms based on their own research, background check providers can greatly increase the speed, accuracy, and effective presentation of these results. The customer gets the background check information very quickly using Big Data analytics in a useful format and visual presentation.
There are some problems with Big Data analytics in background checks, and the Federal Government has shown an interest in the issue. The White House released a report from President Obama’s Big Data Working Group entitled Big Data: A Report on Algorithmic Systems, Opportunities, and Civil Rights. One of the key challenges of using Big Data is the potential for discrimination and legal trouble from hiring practices. The government is concerned about the potential for Big Data background checks enabling and automating discriminatory hiring based on the subjective handling of data and how it’s presented to the reader. Many Big Data providers are working to find a way through the maze of employment laws, civil rights codes, and best practices from the HR industry in order to take advantage of the benefits of Big Data without introducing bias into the system.
Big Data will only continue its growth as we all move forward into the 21st century. The recent report by the White House regarding the opportunities and challenges of Big Data challenges the assumption that Big Data is objective and unbiased. It’s a mistake to assume that data-driven reports are necessarily objective. With proper controls and a conscious effort to avoid any bias on the basis of race, age, religion, physical ability, and other things protected under civil rights codes in the United States. It’s a challenge for the industry to overcome, but the future is very bright. With powerful cloud-based computing and better data tools being developed, Big Data is now a part of our regular, day-to-day life. Background checks are no different, and there’s a great opportunity to do them faster with fewer errors and better presentation of results. Whether deliberately or unintentionally, the design and implementation of the Big Data analytics for background checks can introduce bias in the analysis. Employers and landlords need to make sure that they know the limitations of Big Data analysis as well as the potential pitfalls when it comes to discrimination.
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