Big Data: A Tool for Inclusion or Exclusion? Understanding the Issues

A new report from the Federal Trade Commission outlines a number of questions for businesses to consider to help ensure that their use of big data analytics, while producing many benefits for consumers, avoids outcomes that may be exclusionary or discriminatory.

The report looks specifically at big data at the end of its lifecycle – how it is used after being collected and analyzed. The report highlights a number of innovative uses of big data that are providing benefits to underserved populations, including increased educational attainment, access to credit through non-traditional methods, specialized health care for underserved communities, and better access to employment. In addition, the report looks at possible risks that could result from biases or inaccuracies about certain groups, including more individuals mistakenly denied opportunities based on the actions of others, exposing sensitive information, creating or reinforcing existing disparities, assisting in the targeting of vulnerable consumers for fraud, creating higher prices for goods and services in lower-income communities and weakening the effectiveness of consumer choice.

The report outlines some of the various laws that apply to the use of big data, especially in regards to possible issues of discrimination or exclusion, including the Fair Credit Reporting Act, FTC Act and equal opportunity laws. It also provides a range of questions for businesses to consider when they examine whether their big data programs comply with these laws. The report also proposes four key policy questions that are drawn from research into the ways big data can both present and prevent harms. The policy questions are designed to help companies determine how best to maximize the benefit of their use of big data while limiting possible harms, by examining both practical questions of accuracy and built-in bias as well as whether the company’s use of big data raises ethical or fairness concerns.