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The Digital ContinentPlacing Africa in Planetary Networks of Work$

Mohammad Amir Anwar and Mark Graham

Print publication date: 2022

Print ISBN-13: 9780198840800

Published to Oxford Scholarship Online: February 2022

DOI: 10.1093/oso/9780198840800.001.0001

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Africa’s New Digital Connectivity and Economic Change

Africa’s New Digital Connectivity and Economic Change

Chapter:
(p.18) 2 Africa’s New Digital Connectivity and Economic Change
Source:
The Digital Continent
Author(s):

Mohammad Amir Anwar

Mark Graham

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198840800.003.0002

Abstract and Keywords

The rapid adoption and diffusion of digital technologies on the continent in the last decade has led many governments and observers to talk about Africa’s ‘Fourth Industrial Revolution’. The underlying assertion here is that digital technologies will help African economies move away from the primary sector towards tertiary economic activities, and therefore put them on track for economic development. However, there are genuine concerns about the extent to which digital technologies will alter the existing modes and structures of production that currently benefit the African continent. This chapter argues that Africa continues to be locked into a value-extractive position in the global economy. Digital production, predominantly characterized by low value-added economic activities that do not necessarily translate into socio-economic improvements for the African working classes, represents a new arena for these dynamics to play out.

Keywords:   scramble for Africa, Fourth Industrial Revolution, digital economy, outsourcing, digital platforms, ICT4D, economic development, africa rising

Introduction

Historically, Africa was seen as a key supplier of natural resources, such as minerals and oil, in the world economy. This was the main driver for European colonialism in Africa (Rodney, 2012), and many of its economies still depend predominantly on the export of low-value added commodities. However, many new actors have emerged in the contemporary scramble for Africa (Carmody, 2016; Southall and Melber, 2009). The rapid adoption and diffusion of digital technologies on the continent in the last decade has led many governments and observers to talk about Africa’s ‘Fourth Industrial Revolution’ (The Brookings Institution, 2020; Du Preez, 2019; Morsy, 2020). The underlying assertion here is that digital technologies will help African economies move away from the primary sector towards tertiary economic activities, and therefore put them on track for economic development. However, there are genuine concerns about the extent to which digital technologies will alter the existing modes and structures of production that currently harm the African continent (see Anwar, 2019; Gillwald, 2019; Murphy and Carmody, 2015). In this chapter, we argue that Africa continues to be locked into a value-extractive position in the global economy. Digital production, predominantly characterized by low value-added economic activities that do not necessarily translate into socio-economic improvements for the African working classes, represents a new arena for these dynamics to play out.

Africa’s Linkages with the World Economy

As one of the most resource-rich regions of the world, Africa is estimated to contain about 42 per cent of the world’s bauxite, 38 per cent of its uranium, 40 per cent of its gold, 73 per cent of its platinum, 88 per cent of its (p.19) diamonds, and 10 per cent of its oil. However, over 40 per cent of Africans live on less than what US$1.90 a day would buy you in the US (cited from Carmody, 2016: 1–2). Further, the unemployment rates on the continent are some of the highest in the world, with youth unemployment in North Africa standing at around 28 per cent—more than twice the global average (ILO, 2017a).1 South Africa has youth unemployment in excess of 64 per cent. Furthermore, the ILO estimates over 85 per cent of African employment to be informal, representing the highest rate in the world (ILO, 2018, 2020b).2 While we can find numerous explanations for these rather dismal development indicators, there is no denying that much of this is the result of Africa’s poor articulation with the world economy—which itself has been influenced by its long colonial legacy. Walter Rodney in his classic How Europe underdeveloped Africa (2012: xvi) has noted that ‘the operation of the imperialist system bears major responsibility for African economic retardation by draining African wealth and by making it impossible to develop more rapidly the resources of the continent’.

Put in very broad terms, the colonial powers—including Britain, France, Belgium, the Netherlands, Portugal, Spain, Italy, and Germany—instituted and structured the rules of the game in such a way as to support regimes of accumulation in which the benefits accrued to the European territories.3 These strategies set up the economic system in Africa in which natural resources became central to the ‘scramble for Africa’—and which continue to this day even after the independence movements that swept the continent from the 1950s onwards (Carmody, 2016).4 Politically, independence for many African states brought hopes of a structural transformation of their political economy; however, in failing to resolve the structure of their relationship with global powers, their economic dependence on their ex-colonial masters was preserved, leading to a situation of neocolonialism. As Kwame Nkrumah (1965) has described, the essence of neocolonialism is that the state which is subject to it is, in theory, independent and has all (p.20) the outward trappings of international sovereignty. However, in reality, its economic system and thus its political policy is directed from outside.5

An example of this in the post-colonial era in Africa is the series of structural adjustment programmes (SAPs) forced on it by the International Monetary Fund (IMF) and the World Bank. These programmes have had a lasting impact on African political economy, leading in some cases to deindustrialization, corruption, and inequalities (see Carmody, 1998; Gibbon and Mkandawire, 1995; Nyang’oro and Shaw, 1992). The local political elites within many African societies also became agents in ‘the process of political centralization and economic accumulation’ (Bayart, 2000: 219).6 At the same time, support by the US and Europe of a number of dictators (e.g. President Mobutu in Zaire, present-day Democratic Republic of the Congo (DRC)), financial aid, and free markets and free trade advocated by the IMF and the World Bank served the purpose of drawing African wealth away from the continent (Bond, 2006; Gibbon, 1993; Moyo, 2009).7 A 2017 report by a coalition of NGOs suggests that the continent is a net creditor to the rest of the world, i.e. more wealth leaves Africa every year, through debt payments and profit repatriation by foreign corporations, than it receives (see Honest Accounts, 2017).8

Africa’s structural place in the global economy is such that mining and agriculture still dominate the political–economic landscape of the region, which has dragged several African countries into long-term conflicts, civil wars, and insurgency (on oil, see Ovadia, 2016; on gold, see Engels, 2017; on diamonds and coltan, see Mantz, 2008; Nest, 2013).9 The global financial crisis of 2008, coupled with a rise in food grain prices, led to a surge in large-scale land deals (i.e. acquisition of land by both domestic and foreign investors) which served the purpose of supplying food and energy security to investor countries (Cotula et al., 2009; Matondi et al., 2011; Oya, 2013) (p.21) and entrenching control over politics and resources by the host African states, along with international investors (Carmody and Taylor, 2016; Lavers and Boamah, 2016). In 2011, an estimated 70 per cent of the land acquired globally by both the private sector and governments was sourced from the African continent (Cheru and Modi, 2013). Recently, new powers, including Brazil, Russia, India, and China, are reconfiguring Africa’s economic geography and development but are also reinforcing old patterns of economy and politics (Bond and Garcia, 2015; Carmody, 2013b). Indeed, a majority of Africa’s economies still depend on natural resources and agricultural goods (see Figure 2.1), which have a critical role in deepening the processes of contemporary globalization on the continent (Carmody, 2016).

Africa’s New Digital Connectivity and Economic Change

Figure 2.1 Worldwide dependence on commodity exports, 2013–17 (percentage)

Source: UNCTAD, 2019a. Reproduced with permission.

Africa’s mineral exports to the rest of the world accounted for around half of its total exports in 2018 (UNCTAD, 2019b). The major export from the continent’s biggest economy, Nigeria, is crude petroleum (74 per cent by value), while the second biggest economy, South Africa, depends largely on the exporting of minerals such as gold, platinum, diamonds, coal, and iron ore, amounting to 42.8 per cent. The smaller economies are even more dependent on natural resources export, including Equatorial Guinea (petroleum 87 per cent); DRC (metal ores 53 per cent, copper 13 per cent); Ghana (gold 49 per cent, crude oil 17 per cent, cocoa 10 per (p.22) cent); Ethiopia (coffee 32 per cent, oilseeds 16 per cent, gold 11 per cent, cut flowers 9 per cent); Zambia (copper 74 per cent); and Uganda (coffee 20 per cent, gold 15 per cent). The North African economies are slightly more diversified—Morocco’s major exports are textiles and machines, while in Egypt, minerals are followed by chemical and vegetable exports.10 This dependence on commodities makes them susceptible to commodity price shocks. For example, between 2008 and 2017 the external debt to gross domestic product of Uganda increased from 16 per cent to 43 per cent; in Ghana the figure increased from 19 per cent to 47 per cent, while in Mozambique it is now close to 97 per cent (UNCTAD, 2019c). In the Republic of the Congo and Zambia, external debt payments account for more than 40 per cent and 50 per cent, respectively, of government revenue in 2019, with Republic of the Congo cutting public spending by almost 50 per cent between 2015 and 2018 (Jubilee Debt Campaign, 2020).

Despite African economies growing by 4.1 per cent between 2000 and 2019, which is higher than figures for South American countries, the region has performed poorly on various socio-economic indicators.11 Income inequality remains a major problem, with ten of the nineteen most unequal countries in the world being found on the African continent (UNDP, 2017). Even within different African countries, the distribution of income remains highly unequal, with the richest quintile having a disproportionately high income (see Figure 2.2). The rates of extreme poverty (i.e. US$1.90 per day per capita as poverty threshold) have declined from 54.3 per cent in 1990 to about 41 per cent in 2015, but absolute numbers have gone up from 280 million to 412 million during the same period (Roser and Ortiz-Ospina, 2019). These numbers are expected to increase further as a result of the COVID-19 pandemic, with the United Nations Economic Commission for Africa estimating that an additional 23 million Africans will be pushed into extreme poverty (United Nations Economic Commission for Africa (UNECA), 2020). The World Bank estimates that the pandemic will push around 50 million people into extreme poverty on the continent. Other indicators also reveal the grim reality for the African population. The average life expectancy at birth in Nigeria, the continent’s biggest economy, is fifty-four years, whereas the world average (p.23) is seventy-one years.12 While average adult literacy rates have historically increased worldwide, at least twelve African countries still have literacy rates of less than 50 per cent (Roser and Ortiz-Ospina, 2016). According to WHO data, only 30.1 per cent of the population on the continent have access to safely managed water, which is fewer than the number of mobile phone subscribers.13 Furthermore, on the 2019 Human Development Index, eighteen of the bottom twenty countries are on the African continent (UNDP, 2019). While these statistics make sombre reading, they do not necessarily indicate that change on the continent will be hard to come by.

Africa’s New Digital Connectivity and Economic Change

Figure 2.2 Distribution of income in Africa by quintile

Source: Reproduced with permission from the World Bank (n.d.) under CC BY 4.0 Licence.

The processes of contemporary globalization are changing (see Hirst and Thompson, 2019), and in particular, processes of digitization and automation driven by advancements in digital technologies have transformed the global production landscape, with new business models and new sectors of the economy opening up (Elding and Morris, 2018; OECD, 2017, 2020; WEF, 2018). The world economy has become more information technology and services intensive since the 1970s (Amin, 1994; Harvey, 1989a; Sassen, 2001), with IT-enabled services often regarded as a potential new pathway to economic development opportunities (Dossani and Kenny, 2007; UNCTAD, 2004). Not surprisingly, the emergence of a digital (p.24) economy has ushered in renewed optimism among observers and commentators that the African economies will embark on a process of political and socio-economic transformation.

Digital Economy

The ‘digital economy’ has been variously defined since Tapscott (1996) first coined the term (also see Brynjolfsson and Kahin, 2000; Malecki and Moriset, 2007). Bukht and Heeks’s (2017: 12) definition of the digital economy is flexible enough to incorporate a wide range of digital goods and services. However, they acknowledge the challenge of measuring or quantifying them due to the interwoven nature of the physical and digital economies (e.g. through digitalization of production processes), problems of data quality, and the invisibility of activities (e.g. intermediate services and cross-border data flows) (Elms and Low, 2013).14 That said, there are some metrics that allow us to put the growth and value of the global digital economy in perspective (also Bukht and Heeks, 2017).

In 2019, roughly 87,500 tweets and 188 million emails were sent per minute (Desjardins, 2019a). It is also estimated that by 2025, 463 exabytes of data will be created each day globally, equivalent to 212,765,957 DVDs per day (Desjardins, 2019b).15 While it is hard to quantify the value of all this digital data, one estimate suggests the global digital economy to be worth US$11.3 trillion (World Bank, 2019b).16 Furthermore, statistics from UNCTAD (2017: 15) suggest that the global production of ICT goods and services contributes about 6.5 per cent to the global economic output, with Taiwan, Ireland, and Malaysia’s ICT sectors contributing the most to their own national gross domestic products (UNCTAD, 2019a). Some observers (p.25) have noted that much of this points to the digital revolution taking place across the world (Brynjolfsson and McAfee, 2014). However, one of the genuine concerns about the growth of the global digital economy is about the unevenness of developments around the world.

The UNCTAD’s report (2019a: 3) on the digital economy finds a deep digital divide between countries. Just two countries, China and the US, account for 40 per cent of the total value added in the ICT sector. They also account for 75 per cent of the patents relating to blockchain technologies, 50 per cent of global spending on the Internet of Things (IoT), and more than 75 per cent of the world market for public cloud computing. The report also finds that both countries account for 90 per cent of the market capitalization value of the world’s seventy largest digital firms. Europe’s share is 4 per cent and Africa and Latin America’s share together accounts for only 1 per cent. In other words, there is a concentration of economic power taking place in the global information economy.

That said, the proliferation of digital technologies among the general population in Africa is growing rapidly, and various types of digital economy activities are emerging. The growth of Mpesa, a mobile money transfer scheme launched in 2007 by Safaricom Kenya, has been dubbed a huge success, and other telecom services providers are now providing mobile money transfer services in other parts of the continent (Jack and Suri, 2011, 2014; Jalakasi, 2019; Suri and Jack, 2016).17 Africa accounts for roughly 45.6 per cent of the mobile money market, with US$26.8 billion in transactions in 2018 (GSMA, 2018). Mobile money has also had an impact on the wider IT industry and digital entrepreneurship across the continent, with an increasing number of digital technology start-ups being launched (Andjelkovic and Imaizumi, 2012; Deloitte, 2017; Friederici et al., 2020). There are already 618 tech-hubs established across Africa, which aim to support local tech start-ups, and software and app developers (GSMA, 2019b). Two of the most widely talked about African tech start-ups are Andela (a talent accelerator that trains software developers) and Jumia (a digital marketplace), both of which were launched from Nigeria.18

Furthermore, a nascent BPO industry has emerged in various parts of the continent, offering customer services, customer retention, sales, data management, consultancy, etc. (Anwar and Graham, 2019; Beerepoot and Keijser, 2015; (p.26) Benner, 2006; Mann and Graham, 2016). South Africa and Egypt have emerged as two such preferred offshore destinations on the continent, with Amazon, Microsoft, and Vodafone—among many others—operating their service centres in these countries (Anwar and Graham, 2019). In Kearney’s 2019 Global Services Location Index (Kearney, 2019), both Kenya and Ghana were ranked higher than Ireland as preferred locations for offshore services work. The demand for various types of business services is growing globally, as firms are increasingly looking to outsource some of their operations in order to remain cost competitive, and to focus on their core services (Deloitte, 2018a; Sassen, 2001). Many of these services operations can now be mediated digitally through platforms or websites which connect clients to a global workforce (Lehdonvirta et al., 2019).19 These digital transaction platforms have grown globally to provide services to buyer clients, with an estimated 365 digital work platforms operating in just eight countries on the continent, of which 301 are African (Insight2impact, 2019). Thousands of African workers are turning to these platforms to perform a variety of digital services and tasks for clients both abroad and within their own countries (see Anwar and Graham, 2020b; Graham and Anwar, 2019).

Outsourcing and Production Spaces

One way to think about contemporary configurations of digital economy landscapes and networks in which Africa is being incorporated is to look at the construction of capitalism across geographies, and how new networked spaces of production are being built. For Marx (1954), capitalism is inherently crisis ridden. In order to overcome its crises and survive, capital creates a physical landscape (Harvey, 1978) or produces space in its own image (Lefebvre, 1991; Smith, 1983). David Harvey (2003) referred to such processes as ‘spatio-temporal fixes’.20 ‘Fix’ has two meanings here: first, there is a literal fixing of capital in place in physical forms (e.g. in factories or transportation infrastructure); second, a more metaphorical fixing of crises in capitalism through spatial reorganization of capital, and (p.27) specific strategies to address these crises. In other words, fixes represent capitalism’s ability to create a landscape (only to have it destroyed at a subsequent point in time) so that profits are made, albeit temporarily. Fixes lead to newer contradictions, and therefore new rounds of fixes are introduced (Harvey, 2014). Fixes can therefore be understood as a never-ending search for both internal and external transformation of capitalism through ‘geographical expansion and geographical restructuring’ (Harvey, 2001).

In this section we outline three key waves of restructuring in capitalist production since the end of the World War II: (1) the relocation of industrial production; (2) services outsourcing; and (3) platform-based outsourcing. Our argument is that each of these waves represents a distinct spatio-temporal fix—namely geographical expansion, technological innovation, and organizational change—in contemporary capitalism (Harvey, 1982: 373–412; Hoogvelt, 2001; Jessop, 2006; Peet, 1983)21 that aims to restore the accumulation process and class power—a key feature of neoliberalism (Harvey, 2005; Peck and Tickell, 2002). Each of these waves is the result of long and regular cycles of boom and bust in capitalism, which generate particular production landscapes. In its constant search for profits, new markets, commodities, and cheap labour, capitalism must always create new spaces of production, and some of these are now located in Africa.

Industrial and Services Outsourcing

In practice, the contemporary outsourcing of production can be traced back to the 1960s with the relocation of industrial manufacturing (Fröbel et al., 1981). The attempt by American (as well as European) transnational corporations (Dicken, 2011) to relocate labour-intensive production to low-wage locations in South America and East Asian countries led to a new international division of labour (Fröbel et al., 1981). On the one hand, this division of labour allows production to be subdivided and relocated to multiple locations, and on the other hand it has made it easier for many low-wage locations to be potentially integrated into industrial production networks. For example, the emergence of China as a major (p.28) manufacturing hub has largely been driven by transnational firms relocating their industrial units to its many special economic zones (SEZs) (Zhang, 2006). This relocation was driven not just by a desire for market capture, but also to restore corporate profits by seeking cheap labour, tax breaks, and capable suppliers offshore.22 As Fröbel et al. (1981) observe, division of labour is an ongoing process, with transformative implications for social relations as they are increasingly stretched over larger distances (Massey, 1995; also see Manwaring, 1984). Massey (1995: 3) emphasized that ‘whole new sets of relations between activities in different places, new spatial patterns of social organisation, new dimensions of inequality and new relations of dominance and dependence’ have emerged as production has become increasingly international and complex.23

The globalization of production processes has ultimately resulted in the dismantling of existing social contracts and destroyed hard-fought collective bargaining in many high-cost locations (Gereffi, 2014; Lipietz, 1982)—in effect setting off a global race to the bottom (see Mehmet, 2006; Rodrik, 1997; Davies and Vadlamannati, 2013). Low-income countries with a large supply of low-wage labour set up policies and plans to attract incoming investment. This is achieved by various means, for example by adopting free market and free trade policies and deregulation, incentivizing production, and flexibilizing labour supply. Many countries established industrial zones—India and China set up SEZs (Anwar, 2014; Levien, 2018), Mexico has its ‘Maquiladoras’ (MacLachlan and Aguilar, 1998), and in Egypt and Jordan, they are referred to as qualifying industrial zones (Azmeh, 2014). More recently, there is a trend of SEZs being set up in Africa, for example in South Africa, Nigeria, and Ethiopia (Adunbi, 2019; Bräutigram and Xiaoyang, 2011; Dannenberg et al., 2013; Farole and Moberg, 2017; Giannecchini and Taylor, 2018). But an important point to note here is that these zones are not limited to industrial production alone. The Philippines (p.29) and India both have zones especially dedicated to outsourced services that cater to the needs of both foreign and domestic markets (Anwar, 2014; Anwar and Carmody, 2016; Kleibert, 2014).

The term ‘outsourcing’ emerged in the 1970s in the US as a corporate managerial strategy of firms to relocate production and jobs to multiple low-cost locations such as East Asia and Latin America (Barnett and Muller, 1974). This outsourcing soon came to be seen as a threat to domestic labour markets, particularly in the US. Business Week’s cover story titled ‘Is your job next?’ (Engardio et al., 2003) noted that:

[I]t is globalisation’s next wave—and one of the biggest trends reshaping the global economy. The first wave started two decades ago with the exodus of jobs making shoes, cheap electronics, and toys to developing countries. After that, simple service work, like processing credit card receipts, and mind-numbing digital toil, like writing software code, began fleeing high-cost countries . . . Now all kinds of knowledge work can be done anywhere . . . The rise of globally integrated knowledge economy is a blessing for developing nations. What it means for the US skilled labour force is less clear. At the least, many white-collar workers may be headed for a tough readjustment.

By the late 1990s, outsourcing had achieved a commonplace status in the political and economic sphere, being understood as practices involving lengthening of supply chains, modularization, standardization, lean managerial practices, fragmentation of production, and flexible specialization (see Peck, 2017: 26–27). With more firms actively looking to divest non-core functions such as administrative processing and information technology, the foundation for the outsourcing of back office functions was laid through the establishment of customer service centres across India and the Philippines. As Peck (2017) has noted recently, these outsourcing production networks have become increasingly sophisticated, widening their sectoral reach to include not just labour-intensive production, for example garments, leather goods, toys, consumer electronics, and automobiles, but also standardized service work (e.g. back office processing and customer support), as well as more knowledge-intensive and high value-added operations such as research and development, finance, and consulting. Outsourcing is a dynamic process, with firms constantly searching for new ways to generate value through strategies of nearshoring, onshoring, and multishoring (Abbott and Jones, 2012; Crane et al., 2007; (p.30) The Economist, 2005; Finnemore et al., 2010; Jacques, 2006).24 In other words, the emergence of a suite of outsourced services activities, ranging from low value-added to high value-added functions, and the offshoring, onshoring, and nearshoring of production has set the foundation of today’s far-reaching and complex global production networks, resulting in a significant reorganization of the world economy (see Coe and Yeung, 2015).

This vision of a new globalized world of production and work seemingly overcoming the constraints of the physical geography is epitomized in Thomas Friedman’s The World is Flat. This contemporary round of globalization, he argued (Friedman, 2005: 176), is enabling ‘the sharing of knowledge and work in real time, without regard to geography, distance, or, in the near future, even language’. Friedman’s persuasive account shed light on the global networks that are bringing many different places into the realm of the world economy. However, he ignored the socio-political factors that affect the ways people and places participate in these networks. While it is true that many new places were integrated into global production networks, the inherent power relations in these networks meant that not all places found themselves on a level playing field. India and the Philippines today occupy more than half of the global services market, while new regions like Africa have struggled to capture the market, with countries like Kenya—seen a decade ago as a potential location for outsourced services work—struggling to tap into it (Kleibert and Mann, 2020). In the case of South Africa, the BPO industry has grown over the last decade, but functional upgrading (i.e. moving into high value-added services) among local firms is constrained (Anwar and Graham, 2019).

Furthermore, while it is true that many low-income countries have been able to connect to the world economy in wholly new ways, new sets of structures and power relations in the world economy have emerged (see Gereffi et al., 2005). The geographical relocation and dispersal of economic production—the quintessential hallmark of globalization—has simultaneously been linked with the integration of many more corporate activities. New forms of high-end complex services have emerged that require highly specialized skills to support and manage the operations of large firms. Some (p.31) of these services tend to cluster around only a handful of localities, to take advantage of agglomeration economies (see Sassen, 2001).25

Through all of this linking and delinking of economic activities, corporate organizational structures and patterns of trade have also changed. As firms have become less involved in production they have increasingly bought goods and services from specialized suppliers, often with strict quality control and based on the lead firm’s original design (Gereffi et al., 2005). The best-known example of this is Apple. The company’s flagship iPhone range of mobile phones is designed at the company’s headquarters in California but its individual component parts (such as batteries, processors, and networking chips) are produced by a large number of contract manufacturers or original design manufacturers (ODMs) located globally. These component parts are then assembled by Hon Hai Precision Industry Co. Ltd (aka Foxconn) and Pegatron, both Taiwanese firms, primarily in assembly plants in China and also in other parts of the world (see Costello, 2020; Duhigg and Bradsher, 2012; Moorhead, 2019).26 In fact, this practice of firms buying goods and services directly from a specialized seller or supplier is the hallmark of the contemporary global outsourced services industry, with around 80 per cent of the Fortune 500 companies outsourcing mostly to overseas suppliers, of which India captures the majority share (Poster and Yolmo, 2016: 585, cited from Peck, 2017: 2).

There is no doubt that outsourcing is a spatio-temporal fix that allows firms to extend their production networks on a global scale, often by leveraging advanced digital technologies (Oshri et al., 2015)—which is what Friedman understood as the revolution that is ‘flattening’ the world. However, the patterns of trade and investments that are emerging point to an uneven landscape (see Dicken, 2015) of regionalizing tendencies, clusters, and agglomerations (see Dunning, 2002; Storper, 1997). Indeed, some have dismissed Friedman’s account ‘as a series of exaggerated visions’ about globalization (see Ghemawat, 2009). Nonetheless, underneath the corporate rhetoric lie insights into the complex (p.32) technological, organizational, and social transformations that have enabled the emergence of a new global-spanning but uneven digital production landscape.

New Digital Spaces of Production

Complex long-distance trading networks have existed for centuries. For instance, two thousand years ago, the Silk Road allowed Roman glassware to be sold in China and Chinese silk to be sold in the Roman Empire.27 Similarly, Chinese goods such as porcelain have been found in Great Zimbabwe, an ancient city in Southern Zimbabwe. The trans-Saharan trade in gold, textiles, and slaves which connected West Africa to North Africa and the Roman Empire and beyond (Mattingly et al., 2017) flourished long before the later European colonial powers entered Africa. Centuries later, the advent of contemporary technologies has changed the temporality of such relationships: a Kenyan rose grower who picks and packages her flowers on a Monday on the shores of Lake Naivasha could have her products bought and displayed in a home in Rome or London by the end of the week. However, even with the advancements made in transportation technologies, perishable goods tend to be produced closer to home (e.g. dairy production), with non-perishable goods (e.g. shoes or cars) being produced at great distances from sites of consumption. Many other factors undoubtedly also come into play (e.g. regulatory environments, regional specializations, commodifiability of goods), but the point remains that there has traditionally been an important relationship between what is produced, and where it is produced and consumed. It is also noteworthy that while many sites of production (and associated labour) can be spread out across the planet, some types of work remain geographically bound to the places in which it is used or consumed. While a Chinese silk weaver or Kenyan rose grower can perform their work thousands of miles from the place of consumption, a shopkeeper or a delivery person is still needed to bring those goods to consumers. Put differently, some jobs carry with them an inherent geographic stickiness.

That said, digital technologies are fast changing the geographies of production, distribution, consumption, and organization of work, and the relationship between workers and place is becoming more complicated as a result. Cheap computers and connectivity have drastically lowered the cost (p.33) of some production processes. If workers can do information-based work that can be quickly transmitted around the world, then that work can, in theory, be done from anywhere and by anyone who has access to the right machines and connectivity. When you file a complaint because your train was late or call an airline to request a refund for your flight, the workers who handle your requests could be either down the road from you or on the other side of the planet. Put simply, unlike a farmer or a factory worker, today’s digital workers have far less need to be physically proximate to the object of their labour.

For many types of digital service work, geography has thus become less sticky, with a whole host of services activities being endlessly divided, repackaged, rebundled, and allocated to various suppliers around the world (Peck, 2017). The modularization, commodification, and standardization of work tasks (Scott, 2001), and advances in automation and robotization all present ways to digitally connect service work with different places. In other words, an increasingly digitally connected world has enabled complex virtual production networks to emerge (Tuma, 1998).

At the centre of these production networks are digital platforms. Such has been the tremendous growth of these new corporate entities that some scholars have termed this the emergence of ‘platform capitalism’ (Srnicek, 2016). In his lucid account of how capitalism evolves between cycles of growth and downturn with technology playing a key role, Srnicek argues that the capitalism that emerged after the 2008 global financial crisis is built around the application of digital technologies in production, and the monopolizing, extracting, manipulating, and analysing of large quantities of a key raw material: digital data (also see Couldry and Meijas, 2019).28 Because digital data is codified and can be moved relatively easily across borders, firms’ business models have changed as platforms have become the new organizational structures of digital capitalism, bringing users together to interact and undertake business transactions (Lehdonvirta et al., 2019). This has led some to call such platforms the ‘dominant forms of rentier in contemporary capitalism’ (Sadowski, 2020: 575).29 Srnicek describes (p.34) various types of emerging platforms, e.g. product platforms, industrial platforms, and advertising platforms. While this is a useful classification, our primary concern in this book is with digital platforms that connect buyers and sellers of services (Lehdonvirta et al., 2019). Some of the biggest and most notable of these digital work platforms are Upwork, Freelancer.com, and Amazon Mechanical Turk, representing a workforce of many millions around the world.30

Unlike the outsourcing of the 1990s that took place between different firms and organizations (Manning et al., 2017 cited from Lehdonvirta et al., 2019), digital work platforms can now match big firms, small businesses, and individual clients directly with individual workers and small enterprises anywhere. In theorizing the new ‘global platform economy’, Lehdonvirta et al. (2019) argue that platforms have emerged as new technology-enabled offshoring institutions that enable gains for organizations and individuals by mediating and managing cross-border services. Vallas and Schor (2020: 1) refer to these digital platforms as ‘a distinct type of governance mechanism different from markets, hierarchies, or networks’. Similarly, Langley and Leyshon (2017) argue that platforms play the role of ‘socio-technical intermediary’ and facilitate ‘business arrangement’ between buyers and suppliers of certain digital services. Firms no longer have to take advantage of low-cost locations to set up their offices or customer service centres. A small business in London, for instance, can now directly hire a worker in Kenya to make a website for them and also hire a Nigerian virtual assistant to do customer support and upselling via web chat. Already Kenyan workers are doing article writing for clients based in the US, the UK, and the EU for a variety of purposes, for example magazines and web content.31 Some Fortune 500 firms are already using platform-based workers globally to undertake complex knowledge-intensive work such as graphic design, software development, and data management work (Corporaal and Lehdonvirta, 2017). In other words, the global platform economy leverages the changing nature of internet connectivity and digital technologies to provide firms with access to skilled (p.35) and cheap labour power in areas (such as Africa) not necessarily associated with outsourcing networks, while enabling workers to seek alternative employment outside their local labour markets. Our argument is that labour arbitrage still remains at the centre of global sourcing activities—these platforms are simply the latest digital spaces of outsourced production in the contemporary digital economy, where workers are bought and sold as a commodity on a planetary scale (Graham and Anwar, 2019). However, as we have already noted, these labour markets are very much concentrated in only a few geographical locations (see Graham and Anwar, 2018b, 2019). As such, the new division of labour we are witnessing with the emergence of a global platform economy has the potential to exacerbate geographical inequality, by entrenching the social and economic relations that are embedded within it.

Previously, outsourcing firms got access to cheap and skilled labour by buying services directly from a provider or a vendor located in a select few low-cost locations. But while earlier modes of outsourcing and offshoring were constrained by technological infrastructure, regulatory factors, and other socio-political and cultural factors to cluster around a handful of locations (Gereffi and Lee, 2016; Manning et al., 2017), digital work platforms have eliminated some of these constraints, enabling the platform economy to theoretically operate globally and have access to cheap labour. Whereas the earlier modes of outsourcing did not bring economic production or jobs to Africa on a scale comparable with China and India, digital outsourcing has the potential to bring some forms of digital production and jobs to the African continent. The information economy is characterized by digital forms of value, which are intangible in nature. The raw material is primarily digital data which can be extracted and moved across locations with relative ease, compared with, say, gold or oil. With improved digital connectivity, digital data can flow to locations such as Africa and thus bring new forms of economic activities. The potential of the digital economy and its associated jobs to support development in Africa is now deeply entrenched in the thinking of international development organizations, policymakers, and businesses. Terms like the Fourth Industrial Revolution and Industry 4.0 are rapidly gaining ground among various observers in the African context, and digital jobs are being touted to solve the long-standing unemployment problem. But to understand the potential of new digital production networks emerging in Africa, we should first take stock of the ways in which digital technologies and internet connectivity are understood to impact development.

(p.36) ICTs and Digital Connectivity in Africa: Development Contradictions

Digital technologies have undoubtedly driven transformative changes in the global economy, with newly emerging digital economy activities now widely regarded as critical drivers for economic development, with profound social, political, economic, and cultural implications for individuals, businesses, and the state (Brynjolfsson and Kahin, 2000; Lane, 1999; World Bank, 2016). The importance of the digital economy for economic development in low- and middle-income countries is also underscored by UNCTAD’s Secretary-General, Mr Mukhisa Kituyi, in its 2019 Digital Economy Report. He states:

The rapid spread of digital technologies is transforming many economic and social activities. However, widening digital divides threaten to leave developing countries, and especially least developed countries, even further behind. A smart embrace of new technologies, enhanced partnerships and greater intellectual leadership are needed to redefine digital development strategies and the future contours of globalisation.

UNCTAD, 2019a: v

Today more than half of humanity is connected to the internet—that is, well over 4.1 billion people—with more people from the low- and middle-income regions of the world expected to join in the future (Figure 2.3). By some estimates, the African continent has witnessed one of the fastest growth rates in internet penetration over the last decade, though it still lags behind the world average in terms of the percentage of population that is connected to the internet (ITU, 2019). The cost of mobile broadband remains the highest in the world (ITU, 2019) which prevents further penetration of these technologies.

Africa’s New Digital Connectivity and Economic Change

Figure 2.3 Individuals using the internet 2005–19

Source: ITU, 2019: 1. Reproduced with permission from the International Telecommunication Union (ITU).

Nonetheless, policymakers, development organizations, and the private sector have invested huge sums of money into various highly ambitious (and perhaps overly optimistic) programmes to bring the world’s digitally unconnected people into the networks of digital technologies. These include Facebook’s Free Basics, Google’s balloon-powered internet provision for all through Project Loon, the One Laptop per Child initiative, the Connect Africa initiative of the African Development Bank (AfDB), and programmes run by several African governments to connect their citizens with free internet services through public WiFi hotspots such (p.37) as Project Isizwe (South Africa) and MYUG (Uganda).32 The logic is that digital technologies can help bring progressive change, particularly in the case of low- and middle-income regions (e.g. Radelet, 2010, 2015; Sachs, 2005). The World Bank in its 2016 report titled ‘Digital Dividends’ noted that:

Digital technologies have dramatically expanded the information base, lowered information costs, and created information goods. This has facilitated searching, matching, and sharing of information and contributed to greater organization and collaboration among economic agents—influencing how firms operate, people seek opportunities, and citizens interact with their governments. The changes are not limited to economic transactions—they also influence the participation of women in the labour force, the ease of communication for people with disabilities, and the way people spend their leisure. By overcoming information barriers, augmenting factors, and transforming products, digital technologies can make development more inclusive, efficient, and innovative.

World Bank, 2016: 8–9

(p.38) Debates around the impact of digital technologies have gained considerable traction in recent years, particularly around the idea that ICTs could be a means to deliver ‘development’ (see Heeks, 2006). Heeks (2009: 1) has argued that

ICT4D – the application of information and communication technologies for international development – is moving to a new phase. This will require new technologies, new approaches to innovation and implementation, new intellectual perspectives and, above all, a new view of the world’s poor. All these must be understood if we are to harness digital technologies in the service of some of our world’s most pressing problems.

(On the growing body of ICT4D research, see Aker and Mbiti, 2010; Akpan-Obong, 2009; Avgerou, 2010; De’ et al., 2018; Donner, 2015; Heeks and Krishna, 2016; Juma and Agwara, 2006; Kleine and Unwin, 2009; Mamba and Isabirye, 2015; Poveda and Roberts, 2018; Qureshi, 2015; Roztocki et al., 2019; Unwin, 2009, 2017; Walsham, 2017); for critical reflections, see Anwar, 2018; Chaudhuri, 2012; Díaz and Urquhart, 2012; Friederici et al., 2017; Murphy and Carmody, 2015: chs 12).

The upshot of this growing body of research is that digital tools have wide-ranging social, political, and economic impact—including on economic growth (Qiang and Rossotto, 2009; Waverman et al., 2005); bridging the digital divide (Norris, 2001); social inclusion (Warschauer, 2003); services delivery such as education and health (Blaya et al., 2010; Khan and Ghadially, 2010); better governance, political well-being, and reduction of corruption (Asongu and Nwachukwu, 2019; Bailard, 2009; Bratton, 2013); economic and industrial development (Oyelaran-Oyeyinka and Lal, 2006); financial development (Asongu, 2013); increased market integration (Muto and Yamano, 2009); reduced transaction costs (Molony, 2006); the reduction of information asymmetries (Aker, 2010); and enabling of enterprise development to allow firms to tap into global markets and generate new kinds of IT-based employment opportunities (Asamoah et al., 2020; Benner, 2006; Graham and Mann, 2013; Okpaku, 2006). Such has been the unwavering support for these technologies that ICT tools like mobile phones have been called ‘the single most transformative technology for development’ (Jeffery Sachs quoted from Cable News Network (CNN), 2011).

(p.39) Africa Rising

Such powerful imaginaries concerning, digital tools such as mobile phones, and ‘internet for African development’ efforts, are perhaps best symbolized by the ‘Africa Rising’ narrative (The Economist, 2011; Perry, 2012). This was driven in large part by the arrival of the fibre-optic undersea cable in 2009 to the eastern coast of Africa, hailed by SeaCom, the company backing these cables, as a ‘revolution’ (SeaCom Live, 2009). Of course, Africa was already connected to the world economy, albeit based on commodities export on terms that favoured rich countries. Nonetheless, in recent years, major international organizations and institutions such as the World Bank (2009, 2012, 2015, 2016), African Development Bank (AfDB, 2013), Rockefeller Foundation (2014), and the World Economic Forum (Schwab, 2016) have fuelled further speculation about the potential of digital technologies for development on the continent. Talks of a Fourth Industrial Revolution, automation, the ‘machine age’, robotization, machine learning, and artificial intelligence have seeped into the linguistic repertoire of politicians, businesses, development organizations, aid agencies, lobbying groups, and the mainstream media.33 The World Economic Forum has established a hub called the Centre for the Fourth Industrial Revolution, and two affiliate centres have already been set up in Rwanda and South Africa.34

Nevertheless, these predictions of an African Rising have been strongly criticized. One of the main criticisms stems from the privileging of economic growth as an indicator for development, despite this telling us little about broad-based development (Taylor, 2016; also Meagher, 2016). Lopes and Kararach (2020) point to the fragility of economic growth on the continent, and a worrying tendency of the continent’s economies to grow rapidly but for structural transformation to remain slow, making them vulnerable to crises (also see Cheru, 2017). Rwanda, Botswana, and Ethiopia are often portrayed as countries that have turned their fortunes around through state-directed development strategies, with high economic growth in the last ten years. However, much of that wealth has accrued to (p.40) elite interest groups (see Goodfellow, 2014; Mann and Berry, 2016; Matfess, 2015).35 Similarly, Phillips et al.’s (2016) study of the growth of the Ghanain oil sector points to the problem of elite accumulation with benefits rarely reaching the poor. In other words, while the Africa Rising narrative is built around—and depends on—high economic growth and good governance (see World Bank, 2000), economic growth by itself will not transform African economies and their structural position in the world economy (Gray and Khan, 2010; Noman et al., 2012). As Taylor (2016: 8) has noted, ‘a rise based on an intensification of resource extraction whilst dependency deepens, inequality increases and de-industrialisation continues apace, cannot be taken seriously’.

Mkandawire (2014) argues that much of the discussion within these Africa Rising accounts often ignore the issue of socio-economic inequality emerging from recent economic growth. Not to say inequality is a uniquely African problem—UNDP figures suggest that income inequality is on the rise globally, with the richest 10 per cent receiving up to 40 per cent of global income, and the poorest 10 per cent earning only between 2 per cent and 7 per cent.36 Oxfam’s latest report, ‘Time to Care’ (Oxfam, 2020), finds that the combined wealth of the world’s 2,153 billionaires is greater than that of 4.6 billion people—or 60 per cent of the world’s population—and also that the twenty-two richest men in the world have more wealth than all the women in Africa. Another criticism of Africa Rising narratives comes from the lack of clear evidence on the role of digital technologies and internet connectivity in economic development in general, and for low- and middle-income regions in particular (see Friederici et al., 2017). Thompson (2004) cautions that the way ICT4D discourse is legitimized and replicated in practice, for example in the speeches of the President of the World Bank, can blur the problematic link between ICTs and development for many low- and middle-income countries.

Digital: A Fix for Africa’s Problems?

Ambitious visions of the power of digital technologies to effect economic development are recreated repeatedly, acting to encourage greater economic integration of Africa with the world economy. Advocates such (p.41) as the World Bank often argue that ICTs have great potential to bring about socio-economic and political transformations around the world. First and foremost, digital technologies are seen to overcome physical geography and increase the flows of information, enhance communications, and allow greater market integration (World Bank, 2009; but see Harvey, 2009 for a critique). Second, ICTs are assumed to reduce poverty and inequality, increase productivity and economic growth, and improve accountability and governance (World Bank, 2012). ICTs and improved connectivity are therefore regarded by some observers as a ‘technological fix’ to Africa’s myriad political, economic, and social development problems (Royal Geographical Society, n.d.). The World Bank argues that:

[T]he challenge for the next decade is to build on the mobile success story and complete the transformation. This will require reducing the cost of access for mobile broadband, supporting government private-sector collaboration, improving the e-commerce environment, enhancing ICT labour market skills, encouraging innovative business models that drive employment, such as micro-work and business process outsourcing, and creating spaces that support ICT entrepreneurship, such as ICT incubators, and local ICT development clusters.

World Bank, 2012: 17

This kind of ideology gives preference to ICT-driven connectivities, open markets, free trade, economic growth, and property rights as critical drivers of development. Development for Africa is therefore reduced to a process of spatial diffusion of capitalism from the (high-income) centre, with digital technology playing a key role in this. The World Bank (2009;2016) for example, argues that African countries should improve their connectivity-enhancing infrastructure (including digital technologies) in order to make development more inclusive, efficient, and innovative. However, there is a danger here that these digital connectivities could act to amplify existing economic, political, and social inequalities (Fuchs and Horak, 2008) rather than necessarily create a level playing field. As we shall see in the following chapters, much as we might think of digital outsourcing as a frictionless (Parker et al., 2016) and free-market product of capitalism, it is also generating uneven economic geographies.

In a similar vein, UNCTAD in their 2019 Digital Economy Report (UNCTAD, 2019a) have warned that while digital advances have generated enormous wealth in the world in a record amount of time, that wealth has been concentrated around a small number of individuals, companies, (p.42) and countries. Indeed, there is evidence that ICTs and connectivity have a variegated impacts across different geographical contexts (e.g. low income vs high income countries), and that more evidence is available from high-income countries than low- and middle-income countries (Friederici et al., 2017: 4). In other words, digital connectivities can reinforce the production of spatially uneven development.

In fact, the emerging critical research on ICT4D in relation to African development presents a contradictory and complex picture, with some of this work suggesting that there is a greater amount of hype than reality vis-à-vis technological connectivity and its role in economic development (e.g. Anwar, 2019; Friederici et al., 2017; Graham and Mann, 2013; Murphy and Carmody, 2015; Murphy et al., 2014). In their review, Murphy and Carmody (2015: xv) maintain that the ICT4D literature in relation to Africa often lacks ‘geographic contextualization, theoretical grounding, and/or inter-study comparability or transferability’. Friederici et al. (2017) in their extensive review of the literature on the impact of digital connectivity found that the evidence of the transformative potential of ICTs for African development is inconclusive at best. More specific empirical studies also support this depressing reality. Murphy and Carmody (2015) in examining the use of digital technologies in the wooden furniture and tourism industry in South Africa and Tanzania, for example, found that the use of ICT tools has limited positive transformative impact on furniture producers and hotel owners as they seek to extract more value. Similarly, Friederici et al. (2020: 209) in their multi-city study on the emerging phenomenon of digital entrepreneurship find that in Africa ‘digital enterprises are creatively and productively applying and adapting digital technologies to their local economic, social, and political contexts’; but they also find that digital entrepreneurship is highly unevenly distributed, recreates post-colonial dependencies, and ‘positive local impacts have so far happened at neither the rate nor the scale that widespread narratives about African digital entrepreneurship had suggested’ (Friederici et al., 2020). Furthermore, the role of financial technologies (fin-tech) on African development is also highly celebrated. For example, M-Pesa in Kenya is now widely acknowledged as a success story (see Jack and Suri, 2011, 2014; Suri and Jack, 2016), finds support even among international institutions, and is now seen as critical for achieving sustainable development goals (SDGs). However, Suri and Jack’s research on M-Pesa in Kenya is criticized by Bateman et al. (2019) who highlight a number of problems in their work, including omission of key impact factors and the use of false logic and faulty methodology. (p.43) They argue that these have ‘helped to catalyse into existence a largely false narrative surrounding the power of the fin-tech industry to advance the cause of poverty reduction and sustainable development in Africa and elsewhere’. They conclude that while ‘the fin-tech has the potential to liberate enormous value . . . the bulk of this value does not go to the poor. Rather, fin-tech is very clearly designed to hoover up value and deposit it into the hands of a narrow global digital-financial elite’ (Bateman et al., 2019: 490).

There is no doubt that ICT penetration has increased over the last five years across Africa, and the region has witnessed some growth of ICT-based economic activities. But there is a danger of replicating old-style adverse economic integration of African economies into global digital production networks. Local firms might be generating new forms of digital value on the continent but because of the digital nature of the goods, the value might flow out of the regions—indeed, more easily than commodities such as oil, coffee, gold, wood, etc. This might be the case, for example, in those sectors of the economy that depend on digital technologies, but also those where the products are intangible and not digital in nature, like the tourism sector. There are indications from some parts of the continent that value is being captured by foreign lead firms while local actors simply become dependent on these foreign entities for their survival (for South Africa, see Anwar et al., 2014; for Zanzibar, see Murphy, 2019). Similarly, in digitally intensive sectors such as the outsourced services sector in South Africa, local firms can get locked into low value-added activities, and opportunities for upgrading into high-value complex activities are relatively few (Anwar and Graham, 2019).

As the world economy becomes increasingly digital, the flows of digital data (which is considered by some a resource in itself) will play a crucial role in development and act as a source of power (see Couldry and Meijas, 2019). Digital data is the source of economic value, and firms do everything to exercise control over its ownership and flows—for accumulation (Sadowski, 2019, 2020). In their latest book, Couldry and Mejias (2019) argue that at the heart of the contemporary capitalist mode of production is extraction and exploitation of digital data (also see Sadowski, 2019).37 Information technology firms, along with international organizations (e.g. United Nations (UN) and World Bank) and private sector lobby groups (p.44) (e.g. World Economic Forum) have pushed for the valorization of digital data, hence the emerging narrative around data for development (including open data and big data) (Hilbert, 2016; UN Global Pulse, 2012;).38 For example, International Business Machines Corporation’s (IBM) Project Lucy—a US$100 million cognitive computing project—is expected to learn and discover insights from big data and develop commercially viable solutions to Africa’s grand challenges in health care, education, water and sanitation, human mobility, and agriculture (IBM, n.d).

This data for development (D4D) discourse fits into broader ICT4D discourses, whereby digital data has become a justification for new and old kinds of ICT4D engagement (Mann, 2018 also see European Commission, 2017). Many African countries have also bought into these narratives to create governance and regulatory environments that facilitate flows of data outside the continent, and ultimately (economic) developmental opportunities to be missed. (Mann, 2018).

While digital capitalism holds the promise of bringing new forms of economic production to the continent, to be able to say something meaningful about its implications for development we need to examine its economic geographies. We do this in the next chapter by focusing more closely on BPOs and the remote gig economy. We shall see that uneven distribution of these activities across the continent forces us to ask whether and how the digital is implicated in generating new forms of uneven development at multiple scales.

Notes:

(1) In the region, among those aged 15–29, those not in education, employment or training (NEETs) account for 32% in Tunisia and 40% in Egypt (ILO, 2016).

(2) Informality is often understood to be economic activities and employment outside the purview of legal and regulatory frameworks of the state. From the workers’ point of view, informal employment is often low-paid and lacks social protection. The ILO advocates for the transition from informal to formal employment as a route to development. However, this does not mean the formal sector jobs always offer better pay and social protection, as has been the case with the call-centre work we describe in this book.

(3) African colonization was made possible not just by sheer violence but also by several rules enforced by European colonial powers, such as terra nullius and trusteeship (see Boisen, 2013).

(4) Egypt achieved its independence from Britain in 1922, long before successive waves of independence in the rest of the continent began in the 1950s.

(5) France’s involvement in Francophone Africa is a classic example of a power continuing to exert control over its former colonies, both militarily and monetarily, in order to protect its interests (see Aggad-Clerx, 2013; Charbonneau, 2016; Kamel, 2018; Kane, 2017).

(6) That said, Bayart’s thesis of extraversion has been criticized for downplaying the influence of colonialism, and homogenizing African political experience (see Young, 1999).

(7) The US, by some accounts, has provided military assistance to 36 of the 49 dictatorships around the world as of 2015, that is, to around three-quarters of them (Whitney, 2017).

(8) In 2019, remittances flows to Africa stood at about US$82 billion (World Bank, 2020), higher than the foreign direct investment (FDI) in flows (US$45 billion) (UNCTAD, 2020) and the total overseas development assistance (ODA) or government aid (about $30 billion in 2019) (Organisation for Economic Co-operation and Development (OECD) Stats, n.d.). Put simply, not only do foreign actors extract more wealth from Africa, they give back less than Africans abroad.

(9) Botswana and South Africa may be outliers here, with relatively stable political–economic environments and an economic output largely built around mining. That said, they are still highly unequal societies, with South Africa’s GINI coefficient of 0.61 still the highest in the world.

(10) These data come from the Observatory for Economic Complexity. Available at https://oec.world/en/resources/about/, accessed 8 July 2021.

(11) Data extracted from the Data Bank World Development Indicators. Available at https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG, accessed 8 July 2021.

(12) Data from the Data Bank, World Development Indicators. Available at https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=ZG-1W, accessed 8 July 2021.

(13) Available at https://washdata.org/data/household#!/, accessed 8 July 2021.

(14) This is also part of the bigger problem with the services sector in general, which is increasingly dependent on digital technologies. The services sector, unlike manufactured goods like garments, can be heterogeneous, generally not seen, and hence can remain invisible in statistical and analytical expressions (Low, 2013).

(15) The market intelligence company International Data Corporation (IDC) estimates that by 2025 annual data creation will reach 175 zettabytes, which if one was to store on DVDs, would be long enough to circle the earth 222 times (IDC, 2018).

(16) An important aspect of the growth of the global digital economy which is often sidelined is the externalities that it creates. For example, in 2016, 44.7 metric tonnes of e-waste, i.e. discarded electronic waste including mobile phones, laptops, tablets, desktop monitors, etc. was generated, equivalent to 4,500 Eiffel Towers (ITU, 2017c). A significant proportion of European e-waste is shipped to West Africa. This has not only environmental and health implications but also economic ones. The e-waste often contains rich deposits of recoverable minerals gold, silver, copper, platinum, palladium, etc., whose total value is estimated at $55 billion (UN News, 2017). It by no means suggests that this value can be easily recovered as the minerals are hard to extract from the electronic goods; instead, these goods become environmental hazards.

(17) A critique of Jack and Suri’s assessment of M-Pesa is given in Bateman et al. (2019).

(18) Andela is now headquartered in New York, receiving funding from the Chan Zuckerberg Initiative. Jumia’s founders are French, the company’s headquarters are in Berlin and its technology and product team is based in Portugal.

(19) With the COVID-19 pandemic forcing many companies to adopt a digital transition and encourage working from home, it is likely that many more services will be outsourced to remotely located workers.

(20) Spatio-temporal fixes refers to ‘a metaphor for a particular kind of solution to capitalist crises through temporal deferral and geographical expansion’ and involves many different ‘ways to absorb existing capital and labour surpluses’ (e.g. production of space) (Harvey, 2003: 115–116).

(21) The famous maxim that every crisis is an opportunity applies as capitalism emerges from crises and attempts to restart the cycle of accumulation by cutting costs or capturing cheaper assets and new markets, and forcing out competitors (Harvey, 2011, 2014).

(22) SEZs are later rendition of export processing zones (Anwar, 2014). The first EPZ is said to have been built in the Republic of Ireland. The 1960s saw India’s first EPZ built in 1965, Mexico’s in 1966, and Taiwan’s in 1967. An estimated 5,000 exist around the world today (UNCTAD, 2019d).

(23) The French regulationist scholars have been quite influential in explaining the transformation of the capitalist production landscape and accompanying economic and socio-political relations (Aglietta, 1979; Boyer and Saillard, 2002; Lipeitz, 1987, 1997; on its adoption among Marxian political economy scholars see Jessop, 2001). The regulationist approach uses two concepts: ‘regime of accumulation’ (the way production, distribution, circulation, and consumption is organized to create a stable economic system) and ‘mode of regulation’ (set of laws, norms, forms of state and policy that create a supporting environment for regimes of accumulation). The transition from Fordism (industrial mass production) towards post-Fordism (flexible specialization) represents a shift in the way production is spatially organized (see Storper and Christopherson, 1987) and also the socio-cultural changes associated with it (Harvey, 1989a).

(24) Nearshoring is a strategy of outsourcing of business processes to suppliers or service providers to a country closer to the buyer’s home country. Onshoring refers to moving these services to rural areas or other small cities within the home country of the buyer firm.

(25) The financial services industry developed around London and New York, the motion picture industry in Hollywood (Storper and Christopherson, 1987), information technology cluster developed around Silicon Valley in California, with Bangalore emerging as the Silicon Valley of India (the location of Friedman’s eureka moment) primarily as outsourcing destinations for American firms (Parthasarathy, 2004). Similarly, many more specialized global cities or regions can be seen around the world. Milan and Paris became centres of the fashion industry (though the bulk of garment production takes place in China), Gurgaon and Manilla emerged as call centre hubs of the world (but customers are based in the US and EU countries).

(26) According to Dedrick et al. (2018) the US captures the bulk of the value of the iPhone 7 (US$237.45 per handset) while China only gets 3.6% of the value of its factory cost. While it is true that China has been able to capture a slightly higher share of the value from Apple’s latest iPhone X than from the iPhone 3G, the total value capture is still only 10.4% (Xing, 2019; also see Applebaum et al., 2018).

(27) Part of this section is reproduced with permission from Graham and Anwar, 2018a.

(28) The 2008 global financial crisis became a watershed moment in the history of capitalism as the focus shifted towards the rise of new technologies (the Internet of Things, artificial intelligence, machine learning, automation) and new models of accumulation (the fourth industrial revolution, platform economy, sharing economy, on-demand economy) (see Schwab, 2016; Sundarajan, 2016).

(29) Despite often positioning themselves as intermediaries or platforms, big technology companies have set in motion a new regime of accumulation by setting the rules of the marketplaces and products. The politics of some of the biggest technology corporations, their monopolistic tendencies, and the effects they have on the market and consumer is covered in great detail elsewhere. Rana Foroohar’s (2019) excellent exposé Don’t Be Evil: The Case against Big Tech and Soshanna Zuboff’s (2019) The Age of Surveillance Capitalism are good starting points.

(30) Other platforms enabling local work such as taxi services, domestic help, care work, and online deliveries are not the subject of this book. The most notable local work platforms are Uber, Deliveroo, Task Rabbit, Care.com, Bolt, Helpling, and Airtasker.

(31) Some of the writing done by Kenyan workers fills relatively niche areas. In one case, we spoke to a worker who specialized in writing paid online reviews for doctor surgeries in the US (even though he had never been to the US).

(32) Google has also partnered with local cable network providers to set up free WiFi spots in Nigeria (Akinyelure, 2018). Facebook Free Basics is now accessible in 32 countries on the continent (Nothias, 2020). In January 2021, Google’s parent firm Alphabet decided to shut down its Loon project.

(33) See, for example: World Economic Forum (WEF): Here’s how Africa Can Take Advantage of the Fourth Industrial Revolution; Forbes: How Africa Wins the 4th Industrial Revolution; African Development Bank: Unlocking the Potential of the Fourth Industrial Revolution in Africa. The COVID-19 pandemic has further fuelled debates and anxiety about automation and artificial intelligence in the post-pandemic era in Africa (see Africa Renewal, 2020; Daramola, 2020; Turnbull, 2020).

(34) In a way, the future of African development is now hyped around digital innovation (see Liu, 2019) rather than industrialization, which was the case a few decades ago.

(35) Kagame was a de facto leader between 1994 and 2000 and has been the President of Rwanda since 2000. Ethiopia is effectively a single party democracy which has recently faced serious internal conflicts.

(37) The dangers of surveillance using digital data and services are all too real too (see Donovan and Martin, 2014).

(38) See Big Data for Development (BD4D). Available at http://bd4d.net/about.html, accessed 8 July 2021.