How should privacy concerns be weighed against the benefits of big data? This question has been at the heart of policy debates about big data all year, from the President’s announcement of the White House Big Data review in January to the FTC’s latest workshop looking at big data’s ability to exclude or include. Answering this question could very well present the biggest public policy challenge of our time, and the need to face that challenge is growing.
Increasingly, there are new worries that big data is being used in ways that are unfair to some people or classes of people. Resolving those worries and ensuring that big data is being used fairly and legitimately is a challenge should be a top priority for industry and government alike.
Today, FPF is releasing two papers that we hope will help frame the big data conversation moving forward and promote better understanding of how big data can shape our lives. These papers provide a practical guide for how benefits can be assessed in the future, but they also show how data is already is being used in the present. FPF Co-Chairman Christopher Wolf will discuss key points from these papers at the Federal Trade Commission public workshop entitled “Big Data: A Tool for Inclusion or Exclusion?” in Washington on Monday, September 15.
We are also releasing a White Paper which is based on comments that will be presented at the FTC Workshop by Peter Swire, Nancy J. & Lawrence P. Huang Professor of Law and Ethics, Georgia Institute of Technology. Swire, also Senior Fellow at FPF, draws lessons from fair lending law that are relevant for online marketing related to protected classes.
The papers are entitled:
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The world of big data is messy and challenging. The very term “big data” means different things within different contexts. Any successful approach to the challenge of big data must recognize that data can be used in a variety of different ways. Some of these uses are clearly beneficial, some of them clearly are problematic, some are for uses that some believe beneficial and others believe to be harmful. Some uses have no real impact on individuals at all. We hope these documents can offer new ways to look at big data in order to ensure that it is only being used for good.
Privacy professionals have become experts at evaluating risk, but moving forward with big data will require rigorous analysis of project benefits to go along with traditional privacy risk assessments. We believe companies or researchers need tools that can help evaluate the cases for the benefits of significant new data uses. Big Data: A Benefit and Risk Analysis is intended to help companies assess the “raw value” of new uses of big data. Particularly as data projects involve the use of health information or location data, more detailed benefit analyses that clearly identify the beneficiaries of a data project, its size and scope, and that take into account the probability of success and evolving community standards are needed. We hope this guide will be a helpful tool to ensure that projects go through a process of careful consideration.
Identifying both benefits and risks is a concept grounded in existing law. For example, the Federal Trade Commission weighs the benefits to consumers when evaluating whether business practices are unfair or not. Similarly, the European Article 29 Data Protection Working Party has applied a balancing test to evaluate legitimacy of data processing under the European Data Protection Directive. Big data promises to be a challenging balancing act.
Even as big data uses are examined for evidence of facilitating unfair and unlawful discrimination, data can help to fight discrimination. It is already being used in myriad ways to protect and to empower vulnerable groups in society. In partnership with the Anti-Defamation League, FPF prepared a report that looked at how businesses, governments, and civil society organizations are leveraging data to provide access to job markets, to uncover discriminatory practices, and to develop new tools to improve education and provide public assistance. Big Data: A Tool for Fighting Discrimination and Empowering Groups explains that although big data can introduce hidden biases into information, it can also help dispel existing biases that impair access to good jobs, good education, and opportunity.
Where discrimination presents a real threat, big data need not necessary lead us to a new frontier. Existing laws, including the Equal Credit Opportunity Act and other fair lending laws, provide a number of protections that are relevant when big data is used for online marketing related to lending, housing, and employment. In comments to be presented at the FTC public workshop, Professor Peter Swire will discuss his work in progress entitled Lessons from Fair Lending Law for Fair Marketing and Big Data. Swire explains that fair lending laws already provide guidance as to how to approach discrimination that allegedly has an illegitimate, disparate impact on protected classes. Data actually plays an important role in being able to assess whether a disparate impact exists! Once a disparate impact is shown, the burden shifts to creditors to show their actions have a legitimate business need and that no less reasonable alternative exists. Fair lending enforcement has encouraged the development of rigorous compliance mechanisms, self-testing procedures, and a range of proactive measures by creditors.
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There is no question that big data will require hard choices, but there are plenty of avenues for obtaining the benefits of big data while avoiding – or minimizing – any risks. We hope the following documents can help shift the conversation to a more nuanced and balanced analysis of the challenges at hand.
To contact the authors to discuss any of the papers or issues related to privacy and big data, contact FPFMedia@futureorprivacy.org.