Big data's promise to personalize the delivery of goods and services with human-like accuracy may also result in discrimination and denial of the same benefits to targeted groups and individuals, warns Federal Trade Commission Chairwoman Edith Ramirez.

Ramirez made the statement during an FTC workshop "Big Data: A Tool for Inclusion or Exclusion?" The workshop focused on assessing the potential for analytics to draw up discriminatory policies against the poor and oft-overlooked groups in America.

"A growing number of companies are increasingly using big data analytics techniques to categorize consumers and make predictions about their behavior," said Ramirez prior to the workshop. "As part of the FTC's ongoing work to shed light on the full scope of big data practices, our workshop will examine the potentially positive and negative effects of big data on low-income and underserved populations."

While analytics is trickling down into the hands of the consumers, businesses have long had the opportunity to churn actionable information from mountains of data. But with the rise of machine learning and exponentially more processing power, big data has the ability to construct extremely accurate profiles of individuals from ambient bits of information floating around the Internet.

The workshop seeks to examine how organizations use analytics to categorize customers, how the classifications affect consumers and how businesses stand to gain from creating profiles for groups and individuals. The workshop also seeks to determine the social-economic impacts of big data practices, how existing laws apply to them and how companies use analytics with regard to low-income populations.

"[Big data] has the capacity to save lives, improve education, enhance government services, increase marketplace efficiency and boost economic productivity," Ramirez says. "But the same analytic power that makes it easier to predict the outbreak of a virus, identify who is likely to suffer a heart attack, or improve the delivery of social services, also has the capacity to reinforce disadvantages faced by low-income and underserved communities."

If regulators are aware of all of the risks associated with big data, they can create safeguards to protect consumers from the dark side of analytics, says Ramirez. She says regulators need to make sure big data is a tool for economic inclusion, but there didn't appear to be a need for new legislation or changes to existing structures for large-scale data anaylsis.

"I don't think the [longtime] structures need to be reinvented or shoved aside because data sets are larger," says Ramirez. "It's important to keep the regulations that we have ... to ensure that fair information practices are still applicable and relevant."