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The federal judiciary derives its power from Article III of the United States Constitution. That power is limited to deciding “Cases” and “Controversies,” Art. III, section 2. In the case of Spokeo v. Robins, the United States Supreme Court considered whether a plaintiff presents such a “case” or “controversy” where he only alleged a violation of a consumer protection statute, but did not allege any additional harm. The statute in question was the Fair Credit Reporting Act (“FCRA”). The Court found that plaintiff “cannot satisfy the demands of Article III by alleging a bare procedural violation. A violation of one of the FCRA’s procedural requirements may result in no harm.” Slip op. at 10. Even though Congress enacted the FCRA to avoid dissemination of inaccurate information, for example, “It is difficult to imagine how the dissemination of an incorrect zip code, without more, could work any concrete harm.” Id. at 11. The Supreme Court remanded this case for the Ninth Circuit Court of Appeals to further consider whether this plaintiff presented a “concrete injury” justifying the assertion of Article III jurisdiction.
Continue Reading In Spokeo v. Robins, The United States Supreme Court Articulates a Need for ‘Concrete’ Injury To Sue in Federal Court

The FTC unveiled a lengthy report, Big Data: A Tool for Inclusion or Exclusion? Understanding the Issues, warning companies about commercial uses of big data and the discriminatory impact it may have on low-income and underserved populations. “Big data” refers to the ubiquitous collection of massive amounts of consumer information by companies, which may be analyzed to reveal certain consumer patterns, trends, and associations.

While the term may conjure up an ominous feeling for some, big data has brought numerous advantages to society by efficiently and effectively matching products and services to consumers of all demographics. However, the FTC’s report warns that potential inaccuracies and biases might lead to detrimental effects on low-income and underserved populations, such as the misuse of personal information, reinforcing existing biases and disparities against certain populations, perpetuating fraud against vulnerable consumers, and weakening the overall effectiveness of consumer choice. While companies can design efficient big data algorithms that learn from human patterns and behavior, those algorithms may also “learn” to generate biased results.
Continue Reading FTC Warns Big Data Brings Big Consequences in New Report