How Big Data Can Affect Your Bank Account—and Life

How Big Data Can Affect Your Bank Account—and Life

How Big Data Can Affect Your Bank Account—and Life

Big Data – Mustafa loves good coffee. In his free time, he often browses high-end coffee machines that he cannot currently afford but is saving for. One day, traveling to a friend’s wedding abroad, he gets to sit next to another friend on the plane. When Mustafa complains about how much he paid for his ticket, it turns out that his friend paid less than half of what he paid, even though they booked around the same time.

He looks into possible reasons for this and concludes that it must be related to his browsing of expensive coffee machines and equipment. He is very angry about this and complains to the airline, who send him a lukewarm apology that refers to personalized pricing models. Mustafa feels that this is unfair but does not challenge it. Pursuing it any further would cost him time and money.

This story–which is hypothetical, but can and does occur–demonstrates the potential for people to be harmed by data use in the current “big data” era. Big data analytics involves using large amounts of data from many sources which are linked and analyzed to find patterns that help to predict human behavior. Such analysis, even when perfectly legal, can harm people.

Mustafa, for example, has likely been affected by personalized pricing practices whereby his search for high-end coffee machines has been used to make certain assumptions about his willingness to pay or buying power. This in turn may have led to his higher priced airfare. While this has not resulted in serious harm in Mustafa’s case, instances of serious emotional and financial harm are, unfortunately, not rare, including the denial of mortgages for individuals and risks to a person’s general credit worthiness based on associations with other individuals. This might happen if an individual shares some similar characteristics to other individuals who have poor repayment histories.

Instances of emotional harm can also occur. Imagine a couple who find out they are expecting a much wanted child, but suffer a miscarriage at five months. The couple may find they continue to receive advertisements from shops specializing in infant products months later, celebrating which should have been key “milestones,” causing distress. This is another hypothetical but entirely possible scenario.

The law–or lack of it
In many of these cases, because the harmful practice may not have broken any laws, those who were harmed by data use have limited or no legal options open to them. What happened to Mustafa, for example, was perfectly legal, as there are no current laws forbidding personalized pricing as such. Our current legal systems do not adequately protect people from the harms emerging from big data.

This is because it is very difficult to trace how our data is linked and used. Even if the airline company had done something unlawful, such as broken data protection laws, it would be near impossible for Mustafa to find out. People who feel they have been harmed by data use may struggle to show how their data has been used to cause this harm, which data was involved or which data controller used it. And so they may lack the proof they’d need to get a legal remedy.

Furthermore, even if they show how something someone did with their data harmed them, that particular use of customer information, to adjust pricing for example, may not be unlawful.

Equally, the harm may be caused not by one’s own data but by the use of other people’s data (third party data). For example, in Mustafa’s case it might be that other individuals who were also interested in expensive coffee machines had very high incomes or bought expensive items. This may have been used to suggest that Mustafa also fell into this category, which may have resulted in higher prices for him for other products. An individual harmed through the use of third party data will often not have remedies under current data protection laws.

This article originally appeared on news.yahoo.com To read the full article and see the images, click here.

Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

  • Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
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