Can Big Data Lead to Discrimination?

The advent of big data has sparked controversy over the last two decades about violations of consumer privacy and consumer rights. However, it seems that big data could also have the potential to threaten fairness in the workplace if employers aren’t careful.

What is Big Data?

For those unfamiliar with the term “big data,” it may be helpful to also refer to its more technical term, data mining. Data mining refers to the aggregation of large amounts of consumer data through various streams of information sources. The data is pooled for the purposes of analyzing it to reveal systematic patterns or similarities that can, in turn, be analyzed further.

However, it’s important to note, even though the two terms are often used interchangeably, big data and data mining are two different things. Big data refers to the actual pool of large amounts of data – usually this is considered amounts that are too large to be handled in, say, an Excel spreadsheet.

Data mining, then, is the process of scouring big data in order to discover patterns or to reveal information that would allow for predictions of consumer behavior based on those patterns.

Even though most data mining occurs within the realm of consumer products, big data also has other applications – particularly in employment. Today’s employers frequently rely on big data to screen employees and even to predict which employees are the best candidates for a particular job.

Data Mining and Discrimination

As the use of big data among employers continues to grow, the concern about discrimination grows right along with it. It is feasible the use of big data could lead to employment discrimination if an employer does not carefully maintain detailed records of screening and hiring process and instead relies too heavily on data mining for job recruitment.

Contributing to this concern is the increasing use of social media profiles to aid the hiring process. According to a 2014 study conducted by employment recruitment firm Capterra, 94 percent of employers used or plan to use social media in the hiring process. This is a number that has seen steady increases over the past six years.

During a 2014 Federal Trade Commission (FTC) workshop, the Equal Employment Opportunity Commission (EEOC) expressed concerns about the growing trends related to the use of big data and data mining in employment. EEOC representatives were quick to note well-known employment rights laws, particularly Title VII of the 1964 Civil Rights Act, the Age Discrimination in Employment Act and the Genetic Non-Discrimination Act, could offset any discrimination brought on by big data and data mining.

How Does Discrimination Law Handle Data Mining?

To date, most of the legal issues surrounding big data and data mining have related to consumer protection laws and privacy issues. However, anti-employment discrimination laws also contain preventive measures that could apply to the use of big data in the hiring process.

Title VII, for instance, prohibits discrimination that would have a disparate impact on protected groups of employees. Disparate impact discrimination describes employment policies or processes that have a disproportionately adverse effect on groups of employees protected under Title VII from discrimination based on race, color national origin, sex, religion, age or disability.

Such policies could be facially neutral and unintentionally discriminatory and still be in violation of federal law. That is, they may apply equally to all employees, but have the effect of singling out groups of employees protected under federal law on the basis of one or more of the categories noted in Title VII and other employment discrimination laws.

For example, in recent years, the EEOC has used the theory of disparate impact discrimination to challenge employers’ increasingly frequent use of criminal history and background checks. The main argument goes that these checks often disproportionately affect African-American male applicants, a group often targeted and hit hard by law enforcement policy and incarceration.

Data Mining, Discrimination and the EEOC

Noting the rise in reliance on big data among employers, both the EEOC and the FTC have discussed ways that employment rights laws could preserve fairness in the workplace. The obvious concern is that the use of big data could be skewed, resulting in a disparate impact on protected groups in violation of well-established civil rights laws.

The danger is if the analysis of big data is not accurate in its depiction of good job candidates, data mining in employment is not legally justifiable as a means for assessing job performance. This observance brings into play the business necessity defense, which is also a part of the disparate impact theory. It’s a defense that employers can use to justify a policy that may have a disparate impact but is necessary for business purposes.

The current EEOC stance seems to be to encourage employers to keep detailed records in association with any data mining processes used in recruitment and screening job applicants. In this way, decisions made based on the data can at least be verified and analyzed to ascertain whether they are in compliance with federal law.

Can Big Data Lead to Discrimination?

Yes, it is possible big data could lead to discrimination in employment. However, it is important to note the use of big data itself does not automatically trigger a disparate impact theory of discrimination in violation of Title VII. Much of what should be considered a violation of Title VII and other employment rights law regarding data mining depends heavily on how the information is analyzed and what specific information is being gathered.

Until more cases related to big data arise, it is difficult to say whether it’s an issue that should cause employees hardship. However, from the increasing rise of big data and data mining in almost every sector of society, the issue is definitely one to keep an eye on.