Magazine article Joint Force Quarterly

Framing the Big Data Ethics Debate for the Military

Magazine article Joint Force Quarterly

Framing the Big Data Ethics Debate for the Military

Article excerpt

Big data is everywhere these days. It shows up in many realms of contemporary life, ranging from how people are guided to potential purchases as they shop online, to how political campaigns win elections, and even to when farmers plant crops and apply fertilizer to their fields. While there is no denying the value that comes from data integration and information availability made possible by modern computing power, there are many associated challenges that relate to the privacy of the individual, security of personal data, and reach of decisions influenced by big data. These concerns describe an emerging discipline known as the ethics of big data. This growing conversation is relevant for the military, given both the potential gains from big data collection and analysis as well as the simple fact that big data is here to stay.

In this article, we first define what is actually meant by the terms big data and ethics of big data, explore the challenges associated with big data, discuss some examples and implications for the military, and conclude with a framework for addressing many of these challenges.

The term big data or mega-data refers to a collection of data sets so large and complex that the data become difficult to process using on-hand database management tools or traditional data processing applications. Big data arises from follow-on analysis of existing large data sets and the capture of software logs and information-sensing mobile devices such as cameras and global positioning systems. E-commerce retailers such as Amazon can exploit data on past Internet browsing histories to deliver targeted, personalized advertising to specific customers. As new technologies emerge and become more affordable to collect, process, and store data, the volume of data collection grows exponentially; some 2.5 x 1018 exabytes of new data are created every day. (1) In addition to the sheer volume of information in big data, these data collection efforts increase the breadth of information available to analysts while compressing the delay between data collection and its subsequent analysis. For example, researchers at the University of Michigan now construct social media indexes of labor market activity such as job loss and job posting using text searches of Twitter posts, a tool that is much more accurate in predicting hiring trends than the consensus forecasts of experts and that is close to being available in real time.

A fairly new and emerging field, the ethics of big data has started to address some of the challenges associated with big data, many of which are of an "ought to" rather than an "is" nature. Big data itself is ethically neutral; it is the actual use of big data that raises ethical questions. Thus, the ethics of big data concerns more than simply the matter of morality. Rather, it includes issues such as the privacy, validity, security, transfer, and analysis of big data as well as the business decisions or policy implementation that follow from big data insights. These topics have far-reaching consequences when the data relate to sensitive homeland security matters, individual medical records, or more broadly to data containing personally identifiable information, which often include sensitive information such as name, date of birth, and Social Security Number (SSN).

Understanding Big Data and the Ethics of Big Data

An important starting point for understanding big data is to consider the structure of the underlying information. Big data is referred to as structured when it is in traditional rows and columns such as one would find in a standard spreadsheet. At the other end of the continuum, photographs or feeds are considered unstructured data. Freeform text in a social media status update is an example of semistructured data and sits at the middle of this continuum because it has features similar to both structured and unstructured data.

One of the most appealing aspects of big data and its applications is the ability to study a larger share or sample of an underlying population. …

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