Predictive analytics is the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. Predictive analytics does not tell you what will happen in the future. We can predict powerful insights from existing innocuous data. While we come to terms with the sheer magnitude of prediction’s power, we’ve only begun to fathom the privacy concerns it introduces.

The article cites several cases that illustrate how analysis is powerful but at the same time could intrude into privacy of citizens in various situations and the primary example was on the prediction of Target (the retailer) and target of Prediction. Target used predictive analysis to predict which female customers are pregnant. For the same they initially used a baby register to understand the pattern and later extrapolate it to customers’ buying patterns who don’t use the registry. The company evaluates the customer based on what he/she has purchased.

Target’s public announcement of their results from analysis unfortunately spurred reactions from media. Media outbursts about how PA makes the retailers seem like a zoo where customers are the exhibits. Target reassured audience that they carefully adhered to all privacy and data-use laws, but this was a difficult battle for them.

How can true piracy concerns be clearly defined – even as media overblows and confuses? Data is indeed very powerful and more data means more power. But more powerful data is more sensitive and is perceived dangerous as it is powerful and easily transferable.Similarly, GPS location tracker although extremely useful, provides real-time and historical data of the locations one has been and helps spouses and bosses know of your exact location. HP on the other hand mathematically scrutinized the loyalty of their 330,000 colleagues using trends of their salaries, raises, job ratings and job rotations. Many cases of using PA in regard to law enforcement were very effective - police efforts in predicting the location of future crime and criminal prosecution.

It is difficult to entrust a machine to contribute to these life changing decisions for which there can be no accountability. We can’t measure the quality of the decisions taken – how an incarcerated person would fare free – so there is no way to determine the blame. It presents tough ethical questions – Does PA for law enforcement fly in the face of the very notion of judging a person as an individual?

Privacy and analytics are often publicly positioned as mortal enemies, but are they really? The two worlds may have some real differences, but can probably live a peaceful coexistence if they simply understand where the other is coming from. It is not what an organization comes to know; it’s what it does about it. Inferring new, powerful data is not itself a crime, but it does evoke the burden of responsibility. Each org must decide under which circumstance and for what type of intention or purpose should they Retain, Access, Share, Merge and React data.Also as organizations and consumers don’t speak the same language, dialogue is critical and a check box on reading agreements before execution is a necessity.