Big Data – Big Benefits or Big Problems?

In the past decade, the research industry has been talking about “Big Data” to the point that people in most other industries are now holding their breath expecting a miracle. As a researcher, I am excited about big promise of big data and associated technological advancement. As a social researcher, I can’t stop asking myself – what are the tradeoffs? We are already losing our privacy to Facebook, WhatsApp, and other social networking sites. What’s next?

Last week, I happened to do two things related to my BIG question – I went to the IBM MobileFirst event and listened to a TED talk “Big Data is better data” by Kenneth Cukier. Both were worth the time. Both had at least one important theme in common: Big Data allow us as (and you can put any occupation here) to be more effective. Essentially, big data means fewer traditional jobs because one professional can now do as much work as would be done by 2-3-5 people. Kenneth Cukier went as far as to say that some of the occupations would be able to reinvent themselves and others would vanish forever. Today, big data lead the new industrial revolution. But unlike the revolution at the beginning of the last century which eliminated a lot of blue-collar jobs, this time around the group most affected will be white-collar people: doctors, educators, analysts, strategists, i.e., the thinkers or the intellectual/professional elites. 

I see a huge potential problem here. If Cukier’s forecast becomes a reality, the group of white-collars/intellectual elites will start gradually shrinking. At the same time, the entry barrier to this group will increase drastically, meaning it will no longer be enough to have good education from a good university. The education will have to be the best from the best university and the best professors at that university (i.e., expensive). In addition to education, high-level networks/relationships will evolve from a good-to-have to a must-have. In summary, the limited number of the remaining white-collar jobs will be reserved for those who are able to pay for getting them through a combination of elite education AND elite connections.

The process of a shrinking white-collar job market will have a domino effect on the professional world across the globe. First, a larger proportion of white-collar professionals in developed countries will be taking blue collar jobs pushing out the middle-class. The current members of the middle class either migrate to a lower professional group in developed countries or move to developing countries to retain their middle class status. We already see the examples of such labor migration with professionals from the USA and Western Europe moving to Africa and Asia to be teachers, doctors or work in the IT business. It can be surmised that the opportunities for low-level professional and impoverished groups will diminish in the future because of unsolved existing socio economic condition, like restricted educational access. In addition, their way to the top will become longer and more difficult; and their ambitions and aspirations will suffer. 

On the flip side, we will have to rely on less-educated less-skilled professionals to do the jobs once done by the intellectual elites. For example, a nurse will be able to prescribe a test or a medication using the support of the IBM’s Watson’s Lab; the nurse will type in patient’s symptoms, the Lab will analyze existing literature on similar cases and suggest tests and medications, the doctor will review (hopefully) and approve. 

As a professional in international development and financial inclusion and a businesswoman, I have a problem with above scenario because I foresee it having a dramatic effect on our efforts to achieve the Millennium Goals: reduce poverty, reduce maternal and childhood mortality, etc. However, that does not mean I do not support technological development and the rise of Big Data. I like the verb “reinvent” that Kenneth Cukier used repeatedly in the last 5 minutes of his speech. We need to reinvent ourselves and our world and we need to start right now after we have identified the potential dangers but before it’s too late the change the course. 

I don’t pretend to have all the answers, however, what I observe for the past several year is that the rise of big data is goes in parallel with the decline in educational achievements. If you type “decline in educational standards” in Google search, you will see that the problem is common across the world, be it the US or Kenya. Is the decline in education a coincidence or a part of the rise of big data? When I applied for a teaching job, one of the three key interview questions was, “How are you going to apply IT and mobile technologies to increase student engagement?” I think at one point we started focusing too much on the format of education, i.e., on engaging and entertaining students, and forgot that education is about learning. And learning cannot always be fun and games, sometimes it has to be hard or even painful.

In our financial inclusion research (, I see that in several countries where we work the levels of population literacy, especially among those living below the poverty line, are lower than the levels of numeracy. While counterintuitive at the first sight, this misbalance makes a lot of sense – people do not need to read to make financial transactions because the words are supported by visuals, i.e., arrows, emoticons, pictures, etc. So, to send money through mobile money services or through a mobile phone app, a person just needs to remember a sequence of pictures; being able to read is not really necessary. However, to be able to figure out how much money they can send so that they have enough to pay associated fees, a person still needs to know basic math. 

Maybe it is my background in education speaking, but I strongly believe that one of the features defining us as humans is our ability to think critically: to analyze, synthesize and evaluate. This ability makes us superior to machines and this is the ability that will serve as a foundation for our reinvented selves. I think while we need to continue exploring the benefits of big data, which are truly numerous and exciting, it is imperative that we look back at the time when educational achievements were at their peak. We need to understand what has been going wrong in the past decade, what we are missing and how we can help our children exercise their brains not their thumbs. Perhaps, we can use big data analytics in the process?