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(Image: Geralt via Pixabay)

(Image: Geralt via Pixabay)

The volume and types of data describing individuals and organizations continue to expand, and this trend will continue as sensors make their way into more of the everyday items we use. There are fine lines that separate the use and misuse of data, and some industry associations are addressing the issue head-on with ethical guidelines. While organizations usually have stated privacy policies, more could be done to ensure the ethical use of data.

Although obvious offenses such as fraud are clearly unethical, there is a lot of gray area when it comes to the collection, use, and analysis of data. Ethical guidelines, laws, statutes, and regulations may draw many lines. Even so, questionable situations can arise at various stages of the data life cycle that can confound reasonable people and expose their organizations to risks. Knowing that, the Data Science Association has established the Data Science Code of Professional Conduct to help data scientists navigate tricky situations.

[Read more about analytics and data visualization.]

"Right now, we're just giving guidance. It's to help you, as a data scientist, do the right thing," said Michael Walker, cofounder and president of the Data Science Association. "Their clients or parent organizations can use them in tricky situations where they're going to hurt people at the macro level and hurt people at the micro level." While the Data Science Association is not enforcing its guidelines, it plans to do so in the future.

Two other examples are the American Statistical Association, which created and has an enforcement mechanism for the Ethical Guidelines for Statistical Practices, and the Digital Analytics Association, which created but does not enforce the Web Analyst's Code of Ethics.

The professional associations' guidelines help promote ethical practices in specific roles. However, ethical behavior is an organizational issue. There's no single type of professional that can have sole responsibility for it. Following are some of the basics that companies should consider when measuring their own data ethics.

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