Our project uses a political economy approach to examine digital innovation and the commercialization of digital data in agriculture across two inter-connected field-sites: Kenya’s Rift Valley and California’s Central Valley. It seeks to understand how different players (Tech and Agritech firms, farmers, farm workers, traders and Agribusinesses, policy-makers and donors) collaborate or compete to advance societal innovation while at the same time, furthering their own ideas and interests. Innovation plays a big role in development. It increases productivity and generates a surplus that can pay for higher wages, greater living standards and future productive investment. Governments support innovation by funding education, infrastructure and basic science research while private actors apply that basic science (and well educated workforce) to real life challenges, generating practical and commercially viable technologies. Yet while innovation generates a surplus for society as a whole, it also challenges pre-existing power relationships, firing up struggles over who should capture and control that surplus (Lazonick and Mazzucato, 2013; Mazzucato, 2013; Glenna et al, 2007, 2015). The outcome of this struggle is not merely of distributional concern, but one of sustainability as well. For the economy will only grow if the surplus continues to be reinvested in broad based productivity growth.
Digital technologies are a case in point. Their pervasive reach has profound implications for the economies of poor and rich countries alike. Innovators and tech firms are building digital apps and platforms that simultaneously boost productivity and efficiency yet also create opportunities for actors to extract new value from the recording and mining of transactional data and from greater control over labour made possible through digital surveillance (Levy, 2015).
Their innovations have reshaped markets and placed a strain on the regulatory frameworks and safety nets that have long stabilised our politically charged market societies (Polanyi, 1944; Ruggie, 1982). When these innovations meet a key economic sector like agriculture, the stakes are even higher. Data systems have the potential to increase efficiency, enhance outputs and boost profits and wages. But there is the risk that the benefits might be unevenly distributed.
Dominant players might entrench their positions of power and undermine the possibility for the technological surplus to continue to fuel inclusive and long-term development. This possibility raises questions about the strategic role of data in both advanced and emerging economies, and forces us to consider how our societies might respond.
Every economy is a developing economy struggling to seize control of the technological edge. For advanced economies like the US to maintain their high living standards and address their increasing inequality, their societies must compete with emerging innovation clusters forming in Asia and elsewhere, and find ways to manage their technological surpluses into broad-based growth. For developing economies like Kenya to break through, their societies must boost agricultural productivity and create much-needed jobs outside of traditional farming and low productivity services. This challenge will not be easy, as automation threatens to close off the traditional pathway of moving into low-cost manufacturing and then into higher skilled manufacturing. However, while the forecast for manufacturing may be gloomy, agriculture may provide some hope.
Consumers have grown more sophisticated, demanding exotic and often technologically enhanced produce year round. Some have described this change as bringing about an ‘industrialisation of freshness’ (Cramer, 2015) while others such as Carlota Perez have suggested that resource-rich economies within Latin America and Africa might be able to use their rich natural resources to develop their own geographical-cum-technological barriers to entry within the global economy (Perez, 2015; Whitfield et al., 2016). These changes have called into question the long-standing thesis that agricultural prices necessarily decline relative to manufacturing prices as well as the notion that agricultural work is necessarily a low skilled affair. It now depends on what kinds of agriculture we are talking about: low-tech or high-tech? On
farms across the world, farmers are deploying both ‘conventional’ agricultural technology and increasingly digital technologies, which have enabled them to record information about inputs and processing techniques, improve their production processes and supply consumers with safe, easily traceable and differentiated goods (i.e. single origin, heirloom, fair trade or organic, etc).
Embracing technology has both improved their productivity but also, in some cases, moved their farms into new areas of production in which they can command a technological premium. When compliance
hardens or when such farms integrate into larger input or supply systems, these systems may become a requirement. These informational chains have value beyond farmers and compliance agencies, providing
the platform operator with valuable market intelligence and frameworks for conducting research and development (Cohen, 2010; 2015; Citron and Pasquale, 2014). Thus while digital platforms promise to increase production, reduce waste and ensure compliance, perhaps more significantly, they also generate a new kind of economic value (or technological premium) from the agricultural data itself. Will this ‘datafication’ of the agricultural value chain boost the competitiveness of agriclusters in emerging countries like Kenya? Or will it instead widen the knowledge gap, with actors from more advanced economies monopolising control over the technological surplus generated by digital data on farms in both North and South? The discussion of Data for Development (D4D), a field increasingly popular among policy-makers and development practitioners, has so far largely neglected these questions. In fact, this debate has mostly focused on humanitarian aid and on Open Data frameworks that incentivize the participation of multinational firms in humanitarian programs (Mann, 2018).
Our project departs from this trend by asking, might data have a strategic role to play in achieving more inclusive economic growth in both North and South?
The premise of our study is that ‘development’ occurs across North and South. Thus, our choice of field sites is not driven by a comparative logic but rather an inter-connected one. In fact, we want to study how innovation and value capture play out within and across Kenya and the US.
Kenya has emerged in recent years as a breeding ground for digital innovation.
The vision of a Silicon Savannah cultivated by innovators and investors, has catalysed expectations of high economic growth, which have seeped into the Kenyan government and donor plans to boost agriculture. They anticipate a new Green Revolution within the Rift Valley- the country’s breadbasket.
After decades of under-investment, partnerships between Agribusiness, banks, start-ups, NGOs and governments have formed to raise farm-level agricultural productivity and connect Kenyan farms to global value chains. Digital innovators are playing their role. They are building mobile advice platforms and sensor networks that collect climate and input information, and are working with banks and governments to roll out payment and biometric identity systems to interlink the personal identities, financial behaviour and social networks of farmers and traders. For-profit digital innovation is favoured and developers are encouraged
to look West to Silicon Valley for inspiration.
Thus while NGOs and governments help scale digital networks and bring new users into databases, innovators are under pressure to make their businesses financially ‘sustainable’ and thus monetise data flows. Nevertheless we can envision different scenarios. Such data could strengthen statistical expertise and economic planning systems, or help Kenyan research scientists in their labs, or help educate farmers about how to increase the value of their farms or such capabilities could simply deepen the penetration of multinational research, agribusinesses and financial institutions. Much depends on how actors bargain over their terms of engagement in the innovation process.
On the other side of the world, the US has a long-standing reputation for its innovative and powerful Agri-tech, Agrichemical firms and agricultural heartlands. Its firms and research scientists have deep footprints in African agriculture, collaborating in commercial and non-profit innovation and developing projects in consultation with actors such as US-AID and the Bill and Melinda Gates Foundation. As we are interested
in both global and domestic struggles, we focus on California’s Central Valley due to its rich agricultural diversity, its historically strong worker unions and its innovative farmer cooperatives, as well as the public support given to the tech industry around San Jose. The key players in the Central Valley are not only farmers, but also agribusiness, agritech start-ups and research centres, aiming to build applications to meet global markets. As digital technologies have become ubiquitous in US agricultural production,American farm owners have grown more aware of the value of their data while US policy-makers have begun to explore alternative governance models. Debate has opened up over whom should the technological surplus but the future is uncertain here too, reflecting the relative power of groups to assert control.