FTC Report on Big Data
The Federal Trade Commission (FTC) released its report “Big Data: A Tool for Inclusion or Exclusion?” in January 2016. Based on data from a public workshop on September 15, 2014, the commission sought to understand “both the potential of big data to create opportunities for consumers and to exclude them from such opportunities.” The information from the workshop was synthesized and put into the report, which focuses on the risks and benefits of using big data analytics as well as the laws and research relevant to the use of big data analytics.
The report is informative for collection agencies and how they use the data in their collection practices. Specifically, the report states that “potential inaccuracies and biases might lead to detrimental effects for low-income and underserved populations.”
The report also highlights the many positive ways that big data is being used to provide benefits, such as helping to target credit, educational, employment, and healthcare opportunities for those same underserved and low-income populations.
Quite a few consumer protection laws apply to big data, and these are outlined and examined in the report. In fact, the report goes into detail about how the Fair Credit Reporting Act (FCRA), equal opportunity laws, including the Equal Credit Opportunity Act (ECOA), and the Federal Trade Commission Act (FTC Act) all apply to big data.
What is Big Data?
According to the report, “‘Big data’ refers to a confluence of factors, including the nearly ubiquitous collection of consumer data from a variety of sources, the plummeting cost of data storage, and powerful new capabilities to analyze data to draw connections and make inferences and predictions.” Several phases of data are analyzed as part of the big data analysis, including collection, compilation, consolidation, analysis, and use.
Big Data Policy Review
While it may not seem like there are many risks to using big data, the report section “Research on Big Data” brought to light several possible issues, including whether the data is representative of the whole, as well as whether the data model accounts for biases.
In a future post, we’ll go over the criteria you should apply when reviewing your big data policies, including how the data is compiled and how the data is used and analyzed, as well as how to audit for biases and misrepresentation.
In addition to reviewing your big data policies, it’s also important to identify innovative ways to harness the data you’re collecting in order to prevent the potential risks of big data use. This will help you maximize what you get out of the data without making your policies and agency vulnerable to potential harm.