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R-Net Blog

R Net Blog

R-Net viewpoints: Humanizing big data

Daniel Bennett

From the offset of the talk, Verve’s Colin Strong had the audience intrigued. Opening with a comparison between the modern fascination with big data/quantification and the very nature of time was apt and illuminating. Throughout human history we have attempted to break down complex phenomena into manageable quantifiable frameworks to suit limitations in our cognitive capacities, and there are few better examples of this than the nature of time. Colin then expanded this lateral interpretation of data lead frameworks to that of a ship’s log, which has served an incredibly valuable purpose for hundreds of years, and if we are to believe Star Trek, will continue to in the future. These examples show how ‘big data’, might not be quite the novel phenomena that we assume, and seem to be an intrinsically human way of dealing with some of humanity’s greatest dilemmas.

The use of big data in market research, and other behavioural, psychological and attitudinal research is pertinent given the vast complexities of human nature. As with the given example of time, attempting to understand the human condition as a whole construct is lunacy. By compartmentalising smaller aspects into manageable frameworks and introducing data, it is a much more attractive, and plausible option.

There are further factors that make the case for big data even more compelling. It can be cheaper than other data sources, even free in terms of publically accessible data offerings from services such as Amazon reviews to Google’s services. The methodologies by which big data is gathered are often less obtrusive than alternatives, which cause less operational ‘friction’, most likely fewer demand characteristics and a naturalistic representation of the research question. Furthermore big data offers the benefit of social, real time and longitudinal insights that most methodologies couldn’t even comprehend because of logistical and financial restrictions. All of these factors combined suggest that big data has the potential to provide findings that are a more robust representation of the research hypothesis than other sources.

An important consideration raised was that of the role of the human interpreting big data, especially if we accept that there are incongruities between the perceived self, the actual self, and the externally represented self. If for example, we are to use big data sourced from Facebook as gospel truth without a nuanced critical interpretation we may well get mislead, or so psychological academic literature on emerging phenomena in social media suggests.

With big data providing such an accessible large scale representation of human behaviour, the ethical considerations are well worth debate. With the burgeoning field of Behavioural Economics and the growing application of social science theory to policy, the prospective use of ‘nudging’ theory in a commercial sense is contentious. With big data providing the tools for behavioural ‘nudgers’ there is a risk of driving Machiavellian marketing practice, whereby our very agency is compromised and theories of determinism are even closer to reality than some might suggest.

At this point I’ll be meandering slightly off-piste, to an astrology article that I had read not long before the talk and resonated with me throughout. The article I’m referring to was about the subject of a recent revelation in astronomy. In recent weeks a story about a potential ‘alien superstructure’ has been cycling the scientific press. A strange occurrence was found near a star monitored by NASA’s Kepler telescope, one which could not be explained by existing theories of physics nor astronomy. There is debate about what is actually causing the intriguing occurrence, be it a more likely difficult to scientifically explain mass of comet interaction, or something truly from the realms of science-fiction. One thing however is certain; that without a human volunteer looking through NASA’s data nothing at all would have been noticed. Now, I’m by no means an astrological data scientist, but as far as I can comprehend NASA and Yale Universities’ planet search programme has been setup in such a way that it would exclude this find because of the way the data and search algorithms are coded to our existing human understanding. It was only the eyes of the untrained human that saw through the data to notice the potentially inconceivable oddity. If this is not proof in itself for the necessity of the human in, and humanisation of, big data, I’m unsure what is. 

I came away from the talk really appreciating how much of an important role a critical, responsible, and ethical researcher has in the use of big data. This is best epitomized in this quote from the American writer George William Curtis; ‘It is not the ship so much as the skillful sailing that assures the prosperous voyage.’

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