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The Ethics of Big Data (and What Companies Should Be Doing)

Big data and predictive analytics are reshaping the corporate world, but the ethics of using them aren’t always straightforward. If you want to maintain a positive reputation for your company and its customer facing representatives, it’s your responsibility to understand these ethical dilemmas, and navigate them in a way that protects your customers.

As Adrian Holloway from, an insurance industry focused technology company explains, “running any business transparently and ethically, especially federal and state regulated industries that have consumer protections in place, like insurance or financial services , is vital for improving customer loyalty, employee retention and  other business partnerships.” Unfortunately, big data has been a gray area since its inception, partially because so much of the data gathered is anonymous data—and many companies have forgone ethical considerations.

Consent and User Privacy

First, there’s the problem of ownership, consent, and user privacy. As explained in this study on the role of ethics in big data, “While Big Data allows firms to rapidly capture, analyze, and exploit information, it can also enable access to data that compromises an individual’s privacy.” Necessarily, we must infringe on some level of user privacy when we obtain data—but how much of a breach is ethical? And how must we require consent? For example, is the passive consent of using a platform enough to surrender your data to it?

Sharing and Usage

We also need to consider how data can be shared and used. For example, let’s say that a business gathers data on 1,000 people, then wants to share that data with an organization that will use it to market to those people. Depending on how it was done, this is most likely a legal transaction, but is it ethical? Users may blindly consent to having their data used for any number of applications when they agree to a terms and conditions form, but may have problems with precisely how companies go about using it.

Value and Currency

Data is somewhat intangible; you can gather it without directly “taking” anything from consumers. Yet already, companies are finding that there’s an inherent worth to customer data—particularly companies with business models built around high-tech advertising, like Google and Facebook. But when data starts to be used as currency, how are we to value it? Should there be a fixed rate per unit of data, and if so, how could we judge the quality of that data? Should consumers be entitled to a fixed rate of compensation for the data they provide? Things get messier the bigger your application is.

Transparency and Disclosure

Finally, there’s the problem of transparency and disclosure. Most legal forms express a company’s legal right to use customer data in a number of ambiguous ways. Knowing that, is it ethical for companies to abuse that ambiguity by refusing to disclose exactly how consumer data is being used? If not, what steps need to be taken to ensure an atmosphere of transparency? Which data-related transactions need to be disclosed to customers, and which ones can be forgone? This problem is especially complicated because consumers may not know or realize how their data is being used unless explicitly told so.

What Steps Should Your Business Take?

There aren’t any clear answers for these ethical dilemmas; otherwise, they wouldn’t be dilemmas. So instead of trying to solve them, focus first on considering them, and figuring out how important each one is to your business, specifically. Big data isn’t going away, so the more proactively you establish your company’s own big data ethics, the better.

If you’re just getting started in the world of big data, make sure to try out SAP’s predictive analytics software, which can turn your data into something actionable that can improve your business.

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