Big data has been the buzz phrase in most businesses nowadays as the switch from owning physical assets to that of owning massive data of consumers becomes a norm. This digital asset, among other things, is used to analyze personal or consumer segment profiles and predict future economic behaviors such as buying preferences.
My personal sentiment regarding big data lies on the ethics on how our data is being used and treated. Some companies even sell data to third parties without the consent of the consumers. But how is this problematic? Among other things, the problem depends on who controls and uses our data.
When for-profit companies use our data to profile us and take advantage of our vulnerabilities or wrongly profile us; then red flags should be raised, and our morality test should be checked. This is strongly highlighted in Cathy O’Neil’s book Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy.
The algorithms behind the analytics are man-made and are therefore still prone to human biases even while deliberately removing obvious ones. Such as the case of profiling people for ability to repay loans. In the traditional way of humans assessing clients, blacks, Latinos and other minorities are favored against. If the algorithm is trained to learn from the bank’s history of approving and rejecting loans, then it also learns and adopts obvious human biases. But even if the racial bias is removed and controlled for in the algorithm, in a certain case, it was replaced by an implicit biased variable such as postcode. If you live in a certain “problem” area then the algorithm can work against you, and people who live in problem areas tend to be people of color and minority backgrounds. This is a societal problem because if you come from a poor neighborhood but have an indomitable entrepreneurial spirit and a high business potential, the algorithm will reject your loan application. Consequently, you tend to miss out on opportunities that can alleviate you from your economic situation. Now multiply this scenario to hundreds and thousands of people who were born and raised in poor neighborhoods.
Big Data Analytics is of course not all bad provided that algorithms are scrutinized and especially if controlled by trusted institutions who use it for the good of all. Bill Gates, for example, supports open and deliberate use of people’s data for healthcare especially public institutions working in the field. However, warning signs are everywhere on how consumer data is treated and so we need to revisit where our ethics are.
