(Photo by @mvdheuvel)
How does big data factor into the digital divide? I hadn’t considered the relationship between these two phenomena before this assignment. When we think about big data, we think about governments and corporations amassing financial, medical and digital-behavior information about all of us. But this big-data stuff is very new and so, like any new technology, it’s most visible among the more affluent. That’s where the money is, so that’s where the early capital is steered.
Lower-income people often have less credit history than higher-earning people. They also generally spend less time on social media, conduct fewer financial transactions, see doctors less often, spend less time in school and use fewer Internet-connected devices. So it would stand to reason that less data is collected about lower-income people and that marketers would place a lower value on data about them. Capitalism will catch up to this cohort, but for now many lower-income people are flying below the big-data radar.
So, the sparse representation of lower-income people in big data is a reflection of the digital divide, because less access to gadgets means less data collection. But I suspect that the process is also working in reverse: The absence of information about the poor in big data also contributes to and reinforces income inequality, because poorer people are becoming even more invisible. As a result, governments and corporations making spending decisions based on big data are likely to skew those decisions toward the interests of the wealthy and middle class over the rest of us.