As the volume of consumer data grows, an increasing number of decisions previously made by humans are now made by algorithms. The past two years have brought continuous policy discussion around the benefits and challenges that accompany this growing use of big data analytics. The White House and the Federal Trade Commission released reports on big data and data brokers in early 2014. Since then, policymakers and wonks of all stripes have weighed in on the subject, frequently highlighting one of the most contentious topics raised by these studies: how to ensure that the increase in automated decision-making does not result in unfair, unethical, or discriminatory effects for consumers. Most of these conversations have included calls for transparency into the algorithms that are used to process and makes decisions around consumer data. The problem, writes Future of Privacy Forum Policy Counsel Lauren Smith for Privacy Perspectives, is that transparency is easier proposed than accomplished.
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