United States: FTC Report Alerts Organizations About The Risks And Rewards Of Big Data Analytics

On January 6, the Federal Trade Commission (FTC) released a report that it hopes will educate organizations on the important laws and research that are relevant to big data analytics. The report, Big Data: A Tool for Inclusion or Exclusion? Understanding the Issues, looks specifically at how big data is used after it is collected and analyzed and provides suggestions aimed at maximizing the benefits and minimizing the risks of using big data.

Risk and Rewards

The report argues that big data analytics can provide numerous opportunities for improvements in society. In addition to more effectively matching products and services to consumers, big data can create opportunities for low income and underserved communities. The report highlights a number of innovative uses of big data that provide benefits to underserved populations, such as increased educational attainment, access to credit through nontraditional methods, specialized health care for underserved communities, and better access to employment.

At the same time, the report shows that potential inaccuracies and biases might lead to detrimental effects for low-income and underserved populations. For example, organizations could use big data to inadvertently exclude low-income and underserved communities from credit and employment opportunities, which may reinforce existing disparities or weaken the effectiveness of consumer choice.

Considerations for Using Big Data

The report outlines some of the consumer protection laws (in particular, the Fair Credit Reporting Act and FTC Act) and equal opportunity laws that apply to the use of big data, especially with regard to possible issues of discrimination or exclusion. It also recommends that an organization consider the following questions to help ensure that its use of big data analytics does not lead to unlawful exclusion or discrimination:

How representative is your data set?

If the data set is missing information from particular populations, take appropriate steps to address this problem.

Does your data model account for biases?

Review data sets and algorithms to ensure that hidden biases do not have an unintended impact on certain populations.

How accurate are your predictions based on big data?

Balance the risks of using correlative results, especially where the business' policies could negatively affect certain populations.

Does your reliance on big data cause ethical or fairness concerns?

Consider whether fairness and ethical considerations advise against using big data in certain circumstances and whether the business can use big data in ways that advance opportunities for previously underrepresented populations.

Monitoring and Enforcement Ahead

The FTC stated that its collective challenge is to make sure that big data analytics continue to provide benefits and opportunities to consumers while adhering to core consumer protection values and principles. It has committed to continue monitoring areas where big data practices could violate existing laws and to bring enforcement actions where appropriate. With that in mind, organizations that already use big data and those that are have been persuaded by reported benefits of big data should heed the FTC's advice. The FTC is highlighting its interest in the consumer protection and equal opportunity ramifications of big data use. This report serves as a warning—a statement of intent—that the FTC will be evaluating data practices in light of these concerns. It is clear that organizations must identify and mitigate the risks in using big data, not only those dealing with privacy and data protection but also those presenting consumer protection and equal opportunity issues. Thinking critically about and taking corrective action in line with the considerations listed above, and creating a record that such steps have been taken, may help organizations using big data to avoid FTC regulatory scrutiny.

FTC Report Alerts Organizations About The Risks And Rewards Of Big Data Analytics

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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