Eraptis, September 22.
Thinking about data (for development) has really got me thinking. What is data, and what makes it “big”? How can it be used in the context of development, and which data really matters – is all data created equal? Blogging to reflect on these and other questions, sharing our thoughts with the (social media) world, might help in putting these things into perspective. It may even change how we view things. But then again, to who are we talking – who reads our blogs, and which blogs do we read ourselves?
Tobias Denskus and Andrea S. Papan have taken a closer look into the practices of blogging by development practitioners. In their paper, they interviewed a set of international development bloggers’ on their motivations for maintaining a blog. Although the motivations might be many, their research primarily points towards some individual reasons for maintaining a blog. Among the reasons stated were venting and reflecting on everyday occurrences in the professional life of the bloggers, putting them “out there” for others to engage with. The “Others” mainly comprising other development professionals sharing and consuming information as a way to stay in tune with the “hot topics” of the development sphere, and as a way to show one’s own expertise on the issues of the day. The networking aspect of it all, thus, seems to be an important motivation for blogging – leading to both virtual and real meetings. From an organizational perspective, these things certainly have the potential to create innovative ideas, and lead to improved processes – but there seems to be something missing. As the authors also point out, for blogging to be truly impactful, it needs to turn away from this inward tendency to also engage with local communities.
Why is this important? In my view, it potentially reflects a common practice of development discourse to view the means to an end as the end itself. ICT and data seem to be no different. In the opening chapter of his recent book, Tim Unwin argues exactly this point when writing:
”All too often, ICT4D research and practice has been technologically driven, and has therefore tended to replicate existing social and economic structures, thereby failing sufficiently to explore, interpret, or change the very conditions that have given rise to them.” – Tim Unwin
So – how to challenge this? Perhaps a good starting point is to look at the very definition of “data”, defined by the Oxford dictionaries as “facts and statistics collected together for reference or analysis”. Data, thus, is by its very nature positivistic. It can, at best, tell us what ”is”. But can data be normative? Can data tell us what ”should be”? As Spratt and Baker writes, the answer is not straight forward. While some would argue that if the data sets were just big enough theory as we know it would cease to exist, others point to such statements as hubris – dangerously overestimating the potential of technology to advance development.
Although I would tend to join ranks with the latter, I simultaneously share Unwin’s optimistic mindset that done right ICTs can indeed be a powerful medium for advancing development. But before that can happen we all need to engage in self-reflection and be critical about the appropriate use of ICT4D in order to consider all aspects of an implementation of data-driven development initiatives. At the heart of all this, Unwin argues, lies adopting a critical theory mindset. Among many things, this means doing away with the rather naïve and problematic notion that ICT, in and by itself, is good. And instead see it for what it is, one of many potential means to an end where the central aspect must be to understand the needs of those people for whom these kinds of interventions are intended. In the context of big data, this means working with and empowering those peoples to both generate and analyze this kind of information for themselves.
Before ending this post I would like to leave you with a thought related to one of my initial questions – is all data created equal? Well, Spratt and Baker note that big data analysis, particularly in the context of social media, is heavily biased towards information in the English language. If data is “facts and statistics collected together for reference or analysis”, and most data analyzed is in English, then who’s voices are we really listening to?
Featured image: Eventfinda