PHOENIX--Kimberly Underwood, Ph.D., MBA, chair, Center for Workplace Diversity and Inclusion Research (CWDIR) with the University of Phoenix College of Doctoral Studies, joined the proceedings of the JFF Horizons conference on June 7-8, 2022, in New Orleans, LA. Jobs for the Future (JFF), a national nonprofit driving transformation in the American workforce and education systems, earlier this year announced a partnership with University of Phoenix Career Institute® to support Black learners and workers in building professional social capital to advance their careers.
Big Data: One More Illusion
Big Data: One More Illusion
Firstly, I want to make clear that the purpose of this text is not to be against the so-called “big data”, but to alert to the fact that whatever the tools we have they all depend on the use we make of them.
In recent times, we have been increasingly hearing about the so-called “big data” – the huge databases stored in computers, from which people all too often expect so many wonders. It has been stated that in companies, governments and in the educational area, there is a big degree of anxiety as to how the analysis of these data may provide conclusions about the behavior of people, their purchasing habits, and their reactions to the launching of new products and services, including those concerned with public policies.
In other words, as has happened countless times before, people cotinue to expect predicting with total accuracy the future based on past data. This is one of the multiple manifestations of the deterministic mindset of our culture. The examples are numerous. I will talk about one of them.
When it was made possible to sequence the human genome, it was seen as a huge database from which everyone expected decisive information. Conceptually, the project was consolidated in the mid-1980s and launched in 1990. Astonishment was general. The genome mapping has been called “the book of life”, whose records supposedly would tell everything about our lives. It was sufficient to open and read it, to know in advance which “defective” genes would cause this or that disease in the future.
This has been called “personalized medicine”, an endeavor that, according to an enthusiastic Bill Clinton, would “revolutionize the diagnosis, prevention and treatment of most, if not all, human diseases”. For American geneticist Francis Collins, this new type of medicine would be “likely to emerge by the year 2010”. And so, always according to the deterministic mindset of our culture, began to “emerge” the “specific” genes for each disease: obesity, schizophrenia, alcoholism and so on. In February 2001, the prestigious scientific journal Nature published a long text on the beginning of the sequencing and analysis of the human genome.
Ten years later the question was revised and updated. And the same Nature journal reported that the expectations had not been confirmed (Lander, 2011). Most experts concluded that practically nothing of the expected in previous years had happened, and the chances of significant developments in the future also were not encouraging.
So many promises and so few clinical results. But even so the lay press insisted on ignoring the scientific evidences, and continued to speak of “personalized medicine” and to publish texts according to which “specific” genes of certain diseases actually exist, when in fact this only occurs in very restricted circumstances.
But even so, the expectation to turn other people predictable through consultations of accumulated information about them still persists. It is clear that to some extent people are really predictable: what was said in the previous sentence is a proof of that. However, after a certain point they reveal to be unpredictable and this can surprise even themselves, no matter what we think we know about them.
In other words, if human nature is in good measure predictable, human behavior is to this same extent unpredictable – and there are no databases, however great, or mathematical models, however sophisticated, that can reverse this situation.
All that said, the current “big data” wave may prove to be an illusion as many others – besides being, like many others, a research project dedicated to recording and manipulating people’s behavior. Under the usual disguises (concerns with education, welfare, and health, for example) the actual intent is the same as always: to accumulate knowledge about human behavior which allows to sell people too often unnecessary services and useless trinkets.
Putting it another way: to turn into heavy consumers those who are not yet so, and to reinforce this same behavior on those supposedly already under control. That is, creating and maintaining more and more faithful followers to the creed of technocracy.
It is also obvious that the analysis of “big data” seeks the eternal – and hitherto unrealized – technocratic illusion of predicting what will come based on what has passed. Many people seem to ignore a widely known phenomenon which can be characterized in three items: (1) in any complex system (such as human societies) it is impossible to know exactly the starting points (that is, the initial conditions); (2) as a consequence, initiatives based on inaccurate data also give inaccurate results, however large their quantity; (3) the conclusions (1) and (2), of course, will always be undervalued and/or discarded, because they are realistic and the real world is not always good for the businesses.
Thus it seems to be appropriate to ask what is the real meaning and the real utility of “big data” – and there is no doubt that they exist.
On the other hand, a 2011 report by the consulting firm McKinsey, known for its quantitative and mechanistic approach (Taptiklis, 2008), argued that five new kinds of value could arise from the analysis of large databases: (1) to create areas of transparency in corporate activities that could be used to increase efficiency; (2) to enable more detailed assessments of people’s performance; (3) to target populations to customize actions; (4) to replace and/or to support human decisions through automated algorithms; (5) to create new business models, products and services.
Nothing new, however. The undeclared aim is the same as always: to create and maintain totally managed societies. In the beginning of the last century (1944), thinkers Theodor Adorno and Max Horkheimer were already concerned in knowing “why mankind, instead of entering into a truly human condition, is sinking into a new kind of barbarism" (Horkheimer and Adorno, 1972).
Maybe these two thinkers of the Frankfurt School have been too pessimistic. Maybe not. Anyway, it seems appropriate to reflect on whether we, consciously or unconsciously, might be reinforcing a well-known totalitarian way of thinking that has caused us so many problems in the past and continues to do so nowadays. Maybe it is the case of thinking without being catastrophic, but also without unnecessary illusions about predicting with total accuracy the future based on past data.
HORKHEIMER, Max.; Adorno, Theodor W. (1972). Dialectic of Enlightenment. New York: Herder and Herder, p. xi.
LANDER, Eric. (2011). “Initial impact of the sequencing of the human genome”. Nature470: 187-197.
TAPTIKLIS, Theodore (2008). Unmanaging: opening up the organization to its own unspoken knowledge. New York: Palgrave Macmillan).