In a recent Gartner study showed that by 2018, half of all business ethics violations will happen as a result of improper big data analytics usage. For that reason, companies need to be very careful that as they embrace the idea of using analytics to make business decisions, they don’t put themselves or their customers in jeopardy.
Using data, especially the personal data of consumers, for analytics and making business decisions can quickly become unethical or immoral if proper care isn’t taken regarding the types of information gathered and used. If a business gets too personal with customer information, it may be viewed as an invasion of privacy and could result in the loss of a customer. And even though the U.S. doesn’t have the strongest laws around privacy, the European Union and other countries “have more stringent privacy laws,” says Michael Walker, co-founder and president of the Data Science Association. This means, depending on where you’re practicing analytics, that it can be easy to shift from unethical to illegal.
There are countless examples for data, in general, being used in unethical ways from “judges allowing junk science into the courtroom that can skew a lot of legal cases” to quantitative analysts (aka quants) on Wall Street building flawed predictive analytic models that led to the housing market crash and economic crisis in 2008, Walker says. However, some of these examples cross the line from unethical into illegal territory, which is a distinction businesses need to learn to identify and take into consideration.
Illegal and/or Unethical
The problem with thinking in legal terms with data analytics is that because the U.S. doesn’t have stringent privacy laws, simply following the law isn’t enough to prevent the unethical use of information.
There are obvious situations where gathering data is illegal, such as hacking into devices and stealing information directly from them, but when it comes to business analytics and big data, it’s better to not only rely on the law, but also come up with your own reasons for why you should or shouldn’t use data in a certain way.
Sources : Cybertrend, full article : http://www.cybertrend.com/article/19075/the-ethics-of-data-analytics