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Read the article, The Ethics of Big Data. Based on the content presented in the article, describe the microeconomic principles being used, in other words what is the impact for demand? List the different types of market structures that big data benefits the least and benefits the most. While data collection may benefit the business community, discuss the potential concerns for consumers that arise with the proliferation of big data. Respond to at least two of your classmates' posts.

ARTICLE:

By Ellen Rooney Martin

The rapid ascent of data mining in corporate America has garnered lots of media attention lately and not always in a flattering way. As companies seek to capture data about consumer habits, privacy concerns have flared.

Every time you click on a website, post on social media, use a mobile app and comment via email or to call centers, your data is collected for future use. This has many consumers concerned, not just about targeted marketing but about what can be inferred about them every time they "like" something on Facebook or post a snarky tweet on Twitter TWTR -1.09%.

Data gathering is not going away. Every business sector now collects data of one form or another, and the future marketplace will have even more computing power at their fingertips to mine customer behavior. But, experts say, companies can collect and analyze confidential data in a way that doesn't alarm their customers or compromise privacy. All it takes is a little planning and forethought.

More is not necessarily better

Just because a company can collect all kinds of personal information on consumers, it doesn't mean they should use it, says Bill Schmarzo, chief technology officer for EMC Global Services. Schmarzo says companies risk annoying consumers when using data collected about an individual to tailor messaging and offers.

"I think the biggest concerns are related to organizations using my personal identifiable data, usage and storage against me," says Schmarzo. "But the bigger concerns are related to unsanctioned organizations using my data and inferences about my interests, passions, affiliations and associations for borderline uses about my political, religious, sexual, etc. preferences."

Part of the problem, Schmarzo says, is that companies often pursue a "more is better" philosophy. Therein lies the trouble. Tracking customer preferences and purchases can reveal all kinds of private information, like illnesses, financial problems, even pregnancy, the latter of which created an embarrassing incident for Target in 2012, when it sent coupons to a teenager for baby products by analyzing her shopping patterns. The girl's father complained, only to find out that his daughter was expecting a baby?-something he discovered only because of Target's TGT -1.27% custom advertising technology.

"Unfortunately, the [news] stories always seem to have occurred first and then [companies] figure out how to act," Schmarzo says. Target learned the hard way because the information was used without considering the customer's age, which tarnished the retailer's image. "The minute you use the information you mined to your benefit and not your consumers', then they'll bolt."

Long before a marketing plan based on big data is in place, companies should decide what information would be helpful and limit themselves to just that. Schmarzo advises companies to use the "What Would Mom Do?" test when it comes to analyzing data.

"Companies clearly have to be responsible beforehand," Schmarzo says. "Think ahead of the information you want to tease out and be sure you know what you are looking for."

Aggregate rather than pinpoint

One way companies can harness this power while heeding privacy worries is to aggregate their data, says Hui Xiong, associate professor of management science and information systems at Rutgers Business School, New Jersey.

Companies can create algorithms that identify patterns but protect individual identities. According to Xiong, if the data shows 50 people following a particular shopping pattern, stop there and act on that data rather than mining further and potentially exposing individual behavior.

"Things are getting very interesting," Xiong says. "Google GOOG -0.38%, Facebook, Amazon and Microsoft MSFT -0.26% take the most private information and also have the most responsibility." Because they understand data so well, companies like Google typically have the strongest parameters in place for analyzing and protecting the data they collect, he says. Those companies also understand that data is money so they are hiring the best talent in data science to perform their analyses. When analyzing collected data, data scientists should be very careful revealing their findings, Xiong says.

The professor believes big data collection in itself is pure technology; the ethics come into the analysis through scientists and company directives. "In my opinion, the government should have proper regulations about how and what kind of data should be collected," Xiong says. "Also the industry should have some standards for the use of big data."

However, many traditional retailers haven't grasped the potential of data mining yet, he says, so they haven't put the necessary safeguards in place to protect consumers. They don't put as much importance on the data they collect as they do on the merchandise in their stores, which he views as a mistake. Xiong says gradually companies will become aware of the importance of data and will hire talent to maintain the storage, maintenance and protection of the data they collect, but there's a learning curve.

"I believe whomever owns the company's brand and reputation needs to own this trust and ethics issue, which probably has to start with the CEO," Schmarzo says. "It must be a corporate conviction and belief that consumer trust is priority number one. It can't just be important to the marketing folks and lawyers."