Seeing like a machine: big data and the challenges of measuring Africa’s informal economies

The Juba Archives
State research capacity has been weakened since the 1980s. It is now hoped that the ‘big data’ generated by mobile phone use can shed light on African economic and social issues, but we must pay attention to what new technologies are doing to the bigger research environment. Image by Nicki Kindersley.

As Linnet Taylor’s recent post on this blog has argued, researchers are gaining interest in Africa’s big data. Linnet’s excellent post focused on what the profusion of big data might mean for privacy concerns and frameworks for managing personal data. My own research focuses on the implications of big (and open) data on knowledge about Africa; specifically, economic knowledge.

As an introduction, it might be helpful to reflect on the French colonial concepts of l’Afrique utile and l’Afrique inutile (concepts most recently re-invoked by William Reno in 1999 and James Ferguson in 2005). L’Afrique utile, or usable Africa represented parts of Africa over which private actors felt they could exercise a degree of governance and control, and therefore extract profit. L’Afrique inutile, on the other hand, was the no-go area: places deemed too risky, too opaque and too wild for commercial profit. Until recently, it was difficult to convince multinationals to view Africa as usable and profitable because much economic activity took place in the unaccounted informal economy. With the exception of a few oil, gas and mineral installations and some export commodities like cocoa, cotton, tobacco, rubber, coffee, and tea, multinationals stayed out of the continent. Likewise, within the accounts of national public policy-making institutions, it was only the very narrow formal and recordable parts of the economy that were recorded. In a similar way that economists have traditionally excluded unpaid domestic labour from national accounts, most African states only scratched the surface of their populations’ true economic lives.

The mobile phone has undoubtedly changed the way private companies and public bodies view African economies. Firstly, the mobile phone has demonstrated that Africans can be voracious consumers at the bottom of the pyramid (paving the way for the distribution of other low-cost items such as soap, sanitary pads, soft drinks, etc.). While the colonial scramble for Africa focused on what lay in Africa’s lands and landscapes, the new scramble is focused on its people and markets (and workers; as the growing interest in business process outsourcing demonstrates).

Secondly, mobile phones (and other kinds of information and communication technologies) have created new channels of information about Africans and African markets, particularly in the informal sector. In an era where so much of the apparatus for measuring Africa’s economies has been weakened, this kind of data reaps enormous potential. One might say that the mobile phone and the internet have made former parts of l’Afrique inutile into l’Afrique utile — open for business, profit, analysis, and perhaps, control.

The ‘scramble for Africa’s data‘ is taking place within a particular historical trajectory of knowledge production. Africa has always been a laboratory for Western scientists and researchers, with local knowledge production often influenced by foreign powers and foreign ideas (think back to the early reliance on primary products for export, to which the entire colonial system of economic measurement and development planning was geared). Within the contemporary context of ever-expanding higher education and dwindling finances for local research, African academics and researchers have been forced to take on more and more consultancies and private contracts.

This ‘extraversion’ of African institutions of higher education has contributed to a re-orientation of the apparatus for academic research towards questions posed from outside. Within state bodies, similar processes are underway. Weakened by corruption, Structural Adjustment Policies (SAP), and pervasive informal economic activity, management of the economy has migrated from state institutions into the better paid offices of NGOs, consultancies and private companies. State capacity to measure and model is presently very weak, and African governments are therefore being encouraged to ‘open’ up their own records to non-state researchers. It is into this research context that big data emerges as a new source of ‘legibility’.

ICTs offer obvious benefits to economic researchers. They have often been heralded as offering potentially more democratic and participatory kinds of ‘legibility’. Their potential partly lies in the way that ICTs activate ‘social networks’ into infrastructures through which external actors can deliver and extract information. This ‘sociability’ makes them particularly suitable for studying informal economic networks. ICTs also offer the potential to modernise existing streams of data collection and broaden intra-institutional coordination, leading to better collaboration and more targeted public policy. In our project on the economic impacts of fibre optic broadband in East Africa, we have seen how institutions such as the Kenya Tea Board and the Rwandan Health Ministry are better integrating their information systems in order to gain a better national picture, and thereby contribute to industrial upgrading in the case of tea or better public services in the case of health. Nevertheless, big data is not accessible to all, and researchers must often prove commercial or strategic value in order to gain access.

Use of ‘big data’ is still a growing field, born within the discipline of computer science. My initial interviews with big data researchers working on Africa indicate they are still figuring out what kinds of questions can be answered with big data and how they might justify themselves and their methodologies to mainstream economics. Big data’s potential for hypothesis-building is somewhat at odds with the tradition of hypothesis-testing in economics. Big data researchers start with the question, ‘Where can this data lead me?’ There is also the question of how restricted access might frame research design. To date, the researchers that have been most successful in gaining access to African big data have worked with private companies, banks and financial institutions. It is therefore the incorporation and integration of poor people into private sector understandings that big data currently seems to offer.

This vision of development fits into a broader trend. Just as Hernando de Soto has argued that development is hampered by the exclusion of poor people from formalised property rights, proponents of microcredit have likewise argued it is the poor’s exclusion from financial institutions that limit their ability to develop self-sustaining enterprises. Researchers are therefore encouraged to use big data to model poor peoples’ actions and credit worthiness to incorporate them into financial systems, thereby transforming them from invisible selves into visible selves.

Critics of microfinance have cautioned that incorporating poor people into globalised structures of finance makes them more vulnerable to state interference in the form of taxes and to debt and international financial crises. It is also unclear what the drift into the private sector might do to wider understandings of poverty. While national measures situate citizens as members of national or collective groups, mobile financial innovations often focus on the individual’s financial records and credit worthiness. It remains to be seen whether this change of focus might move us away from more social definitions for poverty towards more individual or private explanations.

Likewise the flow of digital information across geographical space has the potential to change the nature of collaboration. As Mahmoud Mamdani has cautioned, “The global market tends to relegate Africa to providing raw material (“data”) to outside academics who process it and then re-export their theories back to Africa. Research proposals are increasingly descriptive accounts of data collection and the methods used to collate data, collaboration is reduced to assistance, and there is a general impoverishment of theory and debate”. This problem could potentially be exacerbated by open data initiatives that seek to get more people using publicly collected data. As Morten Jerven writes in his recent book, Poor Numbers, interactions between African data producers and users are currently limited, with users often unable to effectively assess the source and methods used to collect the original data. Nevertheless, such numbers are often taken at face value, with dubious policy recommendations formed as a result. While multiple sources of data (from the public and private sector) can help increase the precision of research and lead to better conclusions, we do not understand how big data (and open data) will impact the overall research environment in Africa.

My next project will examine these issues in relation to economic studies of unemployment in Egypt and financial inclusion in Uganda. The key objectives will be to improve our understanding of how data is being collected, how data is being communicated across groups and within systems, how new models of the economy are being formed, and what these changes are doing to political and economic relationships on the ground. Specifically, the project poses six interrelated questions: Where is economic intelligence and expertise currently located? What is being measured by whom, and how, and why? How do different tools of measurement change the way researchers understand economic truth and construct their models? How does more ‘legibility’ over African economies change power relations? What resistance or critical thinking exists within these new configurations of expertise? How can we combine approaches to assemble a fuller picture of economic understanding? The project will emphasise how economics, as a discipline, does not merely measure external reality, but helps to shape and influence that reality.

How we measure economies matters, particularly in the context of ever increasing evidence-based policy-making and with increasing interest from the private sector in Africa. Measurement often changes and shapes our realities of the external world. As Timothy Mitchell writes: “the practices that form the economy operate, in part, to establish equivalences, contain circulations, identify social actors or agents, make quantities and performances measurable, and designate relations of control and command”. In other words, researchers cannot make sense of an economy without first establishing a research infrastructure through which subjects are measured and incorporated. The particular shape, tools and technologies of that research infrastructure help frame and construct economic models and truth.

Such frames also have political implications, as control over information often strengthens one group over others. Indeed, as James C. Scott’s work Seeing Like a State has shown, the struggle to establish legibility over societies is inherently political. Elites have always attempted to standardise and regularise more marginal groups in an effort to draw them into dominant political and economic orders. However, legibility does not have be ‘top-down’. Weaker groups suffer most from illegible societies, and can benefit from more legibility. As information and trust become more deeply embedded within stronger ties and within transnational networks of skill and expertise, marginalised ‘out groups’ are particularly disadvantaged.

While James C. Scott’s work highlighted the dangers of a high modernist ‘legibility’, the very absence of legibility can also disempower marginal groups. It is the kind of legibility at stake that is important. While big data offers enormous potential for economists to better understand what is going on in Africa’s informal economies, economic sociologists, anthropologists and historians must remind them how our tools and measurements influence systems of knowledge production and change our understandings and beliefs about the external world. Africa might be becoming ‘more usable’ and ‘more legible,’ but we need to ask, for whom, by whom, and for what purpose?

Dr Laura Mann is a Postdoctoral Researcher at the Oxford Internet Institute, University of Oxford. Her research focuses on the political economy of markets and value chains in Africa. Her current research examines the effects of broadband internet on the tea, tourism and outsourcing value chains of Kenya and Rwanda. From January 2014 she will be based at the African Studies Centre at Leiden University. Read Laura’s blog.

Time for debate about the societal impact of the Internet of Things

European conference on the Internet of Things
The 2nd Annual Internet of Things Europe 2010: A Roadmap for Europe, 2010. Image by Pierre Metivier.
On 17 April 2013, the US Federal Trade Commission published a call for inputs on the ‘consumer privacy and security issues posed by the growing connectivity of consumer devices, such as cars, appliances, and medical devices’, in other words, about the impact of the Internet of Things (IoT) on the everyday lives of citizens. The call is in large part one for information to establish what the current state of technology development is and how it will develop, but it also looks for views on how privacy risks should be weighed against potential societal benefits.

There’s a lot that’s not very new about the IoT. Embedded computing, sensor networks and machine to machine communications have been around a long time. Mark Weiser was developing the concept of ubiquitous computing (and prototyping it) at Xerox PARC in 1990.  Many of the big ideas in the IoT — smart cars, smart homes, wearable computing — are already envisaged in works such as Nicholas Negroponte’s Being Digital, which was published in 1995 before the mass popularisation of the internet itself. The term ‘Internet of Things’ has been around since at least 1999. What is new is the speed with which technological change has made these ideas implementable on a societal scale. The FTC’s interest reflects a growing awareness of the potential significance of the IoT, and the need for public debate about its adoption.

As the cost and size of devices falls and network access becomes ubiquitous, it is evident that not only major industries but whole areas of consumption, public service and domestic life will be capable of being transformed. The number of connected devices is likely to grow fast in the next few years. The Organisation for Economic Co-operation and Development (OECD) estimates that while a family with two teenagers may have 10 devices connected to the internet, in 2022 this may well grow to 50 or more. Across the OECD area the number of connected devices in households may rise from an estimated 1.7 billion today to 14 billion by 2022. Programmes such as smart cities, smart transport and smart metering will begin to have their effect soon. In other countries, notably in China and Korea, whole new cities are being built around smart infrastructuregiving technology companies the opportunity to develop models that could be implemented subsequently in Western economies.

Businesses and governments alike see this as an opportunity for new investment both as a basis for new employment and growth and for the more efficient use of existing resources. The UK Government is funding a strand of work under the auspices of the Technology Strategy Board on the IoT, and the IoT is one of five themes that are the subject of the Department for Business, Innovation & Skills (BIS)’s consultation on the UK’s Digital Economy Strategy (alongside big data, cloud computing, smart cities, and eCommerce).

The enormous quantity of information that will be produced will provide further opportunities for collecting and analysing big data. There is consequently an emerging agenda about privacy, transparency and accountability. There are challenges too to the way we understand and can manage the complexity of interacting systems that will underpin critical social infrastructure.

The FTC is not alone in looking to open public debate about these issues. In February, the OII and BCS (the Chartered Institute for IT) ran a joint seminar to help the BCS’s consideration about how it should fulfil its public education and lobbying role in this area. A summary of the contributions is published on the BCS website.

The debate at the seminar was wide ranging. There was no doubt that the train has left the station as far as this next phase of the Internet is concerned. The scale of major corporate investment, government encouragement and entrepreneurial enthusiasm are not to be deflected. In many sectors of the economy there are already changes that are being felt already by consumers or will be soon enough. Smart metering, smart grid, and transport automation (including cars) are all examples. A lot of the discussion focused on risk. In a society which places high value on audit and accountability, it is perhaps unsurprising that early implementations have often been in using sensors and tags to track processes and monitor activity. This is especially attractive in industrial structures that have high degrees of subcontracting.

Wider societal risks were also discussed. As for the FTC, the privacy agenda is salient. There is real concern that the assumptions which underlie the data protection regimeespecially its reliance on data minimisationwill not be adequate to protect individuals in an era of ubiquitous data. Nor is it clear that the UK’s regulatorthe Information Commissionerwill be equipped to deal with the volume of potential business. Alongside privacy, there is also concern for security and the protection of critical infrastructure. The growth of reliance on the IoT will make cybersecurity significant in many new ways. There are issues too about complexity and the unforeseenand arguably unforeseeableconsequences of the interactions between complex, large, distributed systems acting in real time, and with consequences that go very directly to the wellbeing of individuals and communities.

There are great opportunities and a pressing need for social research into the IoT. The data about social impacts has been limited hitherto given the relatively few systems deployed. This will change rapidly. As Governments consult and bodies like the BCS seek to advise, it’s very desirable that public debate about privacy and security, access and governance, take place on the basis of real evidence and sound analysis.