The Data Dilemma

It is said that any sufficiently advanced technology is indistinguishable from magic.

This holds for the word ‘data’ that has come to have so much significance in this decade. And rightfully so, because nothing in human history has evolved as much as computer processing power- a trillion times more from the 1960s! Consequently, this means there’s data of such volume, variety, and veracity that we cannot even begin to comprehend. Leveraging this data has led to the growth of trillion-dollar industries in our age, but there is a dilemma.

Concerning advantages, the analysis of big data has improved the process of decision-making for businesses, thereby saving cost and time. Access to data on the vast expanse of a market has improved customer service and relations, increased the scope of personalised insight and content, and even opened the doors to innovations that tackle problem statements of different varieties.

This is the information age, the age of a click, everything is fast and vast. Search engines and recommendations became eerily accurate; Google uses an algorithm called MapReduce. It searches for a query by dividing tasks into small parts and assigns them to computers connected over the network to form the final result. Financial companies use machine learning algorithms and artificial intelligence to detect anomalies and transaction patterns that help detect unusual activity and fraud. Companies have made B2B communities for supplier networks that give them high contextual intelligence and enhance their chance at success. And the list can go on, as to how useful data has become to us.

But we must ask the question, where is the privilege to leverage digital data to the advantage of the individual? It only lies with big companies as of now. Data rights are only slowly being brought to the attention of society.

Big tech companies are like de facto governments that function with fewer regulations. The extent of data that a company can hold about a person is questionable, and could even be labelled an unethical practice. For companies that sell certainty, it comes with a heavy price that we pay without even knowing. Their marketing strategy is to tap deeply into the human psyche and make a gradual change in our perception and behaviour.

Come to think of it, how many times have your recommendations been spot-on? How many times have you bought something you did not need? Or how long has your phone kept you occupied by recommending content to you? Companies have so much information on our behaviour patterns that they can predict human futures. Therefore, something as big and powerful as this needs to be regulated. There must be discourse around data autonomy as much as data monopoly. So what can be done to handle this dilemma?

The tech representatives themselves say that data assets and processing must be taxed like any other commodity. The intricacies of digital business models create a near-impossible task of determining where multinational corporations generate profits and fulfill their tax obligations. So there is a need for regulations that make sure organisations are more accountable for the data they own or access. Additionally, there must also be good leaders in the tech industry; who will employ ethical business models and will understand the responsibility at their end.

Most importantly, there needs to be collected will and awareness on both sides of the data coin.

As technology continues to advance, we must take accountability and responsibility. Because human synthesis and machine learning can be paired to get the best possible results. A good example that automation enthusiasts use is that of Chess. Although the AI had a considerable advantage over human chess players, when the Chess experts were given the AI tools, they were able to perform better than any human or machine could by itself. This man-machine relationship must continue harmoniously.
Otherwise, we are lost in the noise of digital zettabytes.