Mobile phones are not for calling

Gone are the days when the utility of phones was to make phone calls. Mobile phones for development have endless potential surpassing that of the desktop computer. Their value is primarily in data-gathering and knowledge-sharing, but not without a fair share of associated risks.

Over the last few weeks, I have been busy with some elaborate research. And for once, I am not talking about coursework nor my job. This time I have actually been looking to replace my four-year-old and by now screen-shattered smartphone. Like most people, I use my phone for anything but calling, and on my days off work, I use it far more than I do my computer.

I then remembered my days in Uganda. In the small town where I worked, most people owned a mobile phone, some had a smartphone, but very few had a computer. In fact, the number of mobile phone users in sub-Saharan Africa has increased at an annual rate of 18% since 2007 (Taylor and Schroeder 2015), transforming communications as well as development projects.

Location and time bound data collection

For a device with such a short history, the mobile phone but even more so the smartphone is responsible for tremendous impact, all over the globe. For one thing, it has the power to collect a significant amount of information such as location, communication practice, behaviour, and even movement. The device can be taken advantage of even more profoundly – or invasively – and gather all kinds of big data, from political ideologies to dietary preferences. As smartphones are becoming the dominant way to access the internet, different services are enabled by big data approaches (Meikle 2016). And with the South being home to so many mobile phones, the region has joined the North in contributing to big data creation.

Held near to one’s body, with all its multitude of connection portals, the mobile phone becomes an extension of oneself (Meikle 2016). And it is for this reason that it becomes much more effective than a computer in collecting data – particularly if the data needs to be time and/or location bound. For instance, in a crisis situation like a disease outbreak, routinely-collected data, made possible by mobile telephones, can provide estimates of magnitude, distribution and trends in population displacement.

“If data science is to be brought together successfully with humanitarian response, timely data access is critical” (Taylor and Schroeder 2015).

Data collected from mobile phones is also useful in other crises situations such as conflicts or natural disasters. (Check out ICT4Humans: From tech to people in humanitarian response)

Fast and cost-effective

Mobile phone technology offers some ground-breaking changes in development practice , in terms of reducing expenses and local participation. Mobile phones empower local populations to more actively participate in projects either by communicating or simply by accessing knowledge on their own.

Collecting data via mobile phones is far more cost-effective and faster than the old-fashioned face-to-face interviews. The data produced in this way is in many cases thought to be more reliable than the existing statistics collected by governments (Taylor and Schroeder 2015). Mobile surveys are a great way to provide governments, development professionals and citizens relevant and timely information regarding public services, and the like.

Big data and digital technology offer better possibilities of analysis and integration of the plethora of variables. By merging information gathered on market prices, political situation, community’s habits and weather conditions, development practitioners may be able to predict food prices and act pre-emptively.

While the North is more used to (and often times annoyed at) phone surveys, poorer states are not as familiar with this practice due to the low telephone ownership in the past. Mobile phones are, in fact, interesting in that they’re an example of a leapfrog technology, skipping over the era of fixed lines, wires and desktop computers.

Risks and future

It is no secret that development is incredibly complex without shortcuts or single cure-alls. Thus, we have to expect that even the magnificent mobile phone does not aid without its consequences. The most obvious of which is the new divide created between those that have access to a smartphone and those that do not (See blog: If it Matters, it’s Measured #WomenMatter). The mobile phone, especially the smartphone, converges the public media and the personal communication (Meikle 2016), creating risks of privacy. And as with all big data, another issue is who gathers this data and to what end.

The mobile phone has hence moved far beyond its original purpose of calling. And, it seems that we’ve only tapped into its potential, with the development of blockchains and cryptocurrencies the future of mobile technology is boundless.

At four years old, my smartphone is looking rather old and I’m ready for a replacement. And to do so I will use the money I saved from not replacing my old desktop.

 

Photo CC0 Creative Commons

References:

– Canuto, O. 2013: Mobilizing Development via Mobile Phones. The World Bank. Retrieved 9 March from http://blogs.worldbank.org/growth/mobilizing-development-mobile-phones

– End of the smashed phone screen? Self-healing glass discovered by accident. 2017. The Guardian. Retrieved 10 March from https://www.theguardian.com/technology/2017/dec/18/smashed-cracked-phone-screen-self-healing-glass-university-of-tokyo

– Meikle, G. 2016: Social Media: Communication, Sharing and Visibility. Abingdon: Routledge.

– Schroeder, R. 2018: Social Theory After the Internet: Media. Technology & Globalization. London: UCL Press.

– Taylor, L., Schroeder R. 2015: Is bigger better? The emergence of big data as tool for international development policyGeoJournal 80: 503-528.

– The limits of leapfrogging. 2008. The Economist. Retrieved 9 March from https://www.economist.com/node/10650775

 

 

4 Comments

  1. O. F.

    Hi Mirna,
    Very interesting post, I enjoyed reading it a lot. I’ve done some research before on how smartphones are used by refugees and migrants along their journeys and how this changes the ways assistance can be provided (eg. launching apps that keep people updated with the most relevant news of border closures, regulations, etc.), but data collection is another interesting aspect.
    As an example, IOM has its ‘Displacement Tracking Matrix’ project (https://displacement.iom.int/) that tracks and monitors displacement and population mobility, which is a large-scale global program to map movements, but even there most data is collected by data-collectors using face-to-face interviews at different entry and exit points along the migratory routes.
    I’m just wondering that given the importance of smartphones for refugees and that most people own one, also in this case they could be well used for monitoring population movements in a more cost-effective way and probably also reaching more people.
    Just out of curiosity, do you know any examples where more complex movements were being tracked and monitored relying on people’s access to smartphones?
    Thanks for the interesting read! 🙂

    • Mirna

      Hey, Thanks for reading and for the insightful comment. I actually just noticed a few things and made small edits but only to structure and concluding sentences (nothing in terms of actual content). Since the topic is really simply much too vast for a brief blog post, I had in mind to follow it up with a concrete example of how mobile phone data collection is being used (or rather we’re using in the organization I work in) in the field of agriculture and nutrition. Common practice is holding various kinds of surveys and interviews with households on what their food consumption looks like, and what foods they’re growing to then create a database and use this information for better informed development projects. However, this entails having people personally speak to households and jot down their responses. You can imagine what a challenge it is then to integrate all this information, with that of other interviews/surveys, with pictures, location and so on. Also, by the time a report comes out, this data is already getting old. Moreover, the development practitioners are not well equipped to provide on-the-spot advice and recommendations to the households. With mobile technology, these things become easier. The respondents take pictures of what they’re eating/growing, these pictures include metadata such as location. Researchers can ask questions, and the respondents can answer immediately. The weather conditions, market prices, location, culture, pictures and nutrition information is all easily merged, facilitating analysis and informing practice. Also, when house visits are done, the development practitioners with access to the digital database can offer timely recommendations.

      And now after writing all this I realize I really haven’t answered your question properly. I can’t remember off the top of my head, but there was an example in the article “Is bigger better? The emergence of big data as tool for international development policy”. It was indeed about a disease outbreak in Haiti. I can check and get back to you, but otherwise, I wouldn’t of a precise example from my own experience (other than nutrition/agriculture ones but these generally don’t look at movement).

  2. Diana Waruhiu

    Hey Mirna,
    Thank you for your interesting post. I enjoyed reading your points on the other uses of mobile phones and especially the smart phone. The feature phone already had begun to ease our lives and now with the smart phone; how we bank, interact with one another, access social welfare not forgetting about how the data collected about us and by us has brought changes of unimaginable measure. I am particularly interested in the importance of mobile phones in a humanitarian crises and how it has enabled ordinary people to be digital humanitarians. I also trust that the gap of those who have access to phones and internet will be reduced in the near future because in many developing countries the device is still mainly owned by men thus excluding women from enjoying its benefits.

  3. Pingback: Five things you might not know about Big Data - #DataTalks

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