sneha – A Digital New Deal

January 25, 2021January 25, 2021

Latin American Visions for a Digital New Deal: Towards Buen Vivir with Data

Latin American Visions for a Digital New Deal: Towards Buen Vivir with Data

Stefania Milan & Emiliano Treré

para Diego Armando Maradona, desde los márgenes a las estrellas
[for Diego Armando Maradona, from the margins to the stars]

In this contribution, we explore the notion of ‘data poverty’ to examine the social costs of the first pandemic of the datafied society and identify critical fault lines in the dominant digital paradigm. We engage with Latin American perspectives and traditions, especially in the fields of popular education and communication for social change, to outline three key elements of a Digital New Deal: critical ecology, liberation pedagogy, and autonomous design. Taken together, we argue, these components can intercept and mitigate the new forms of data poverty visibilized and exacerbated by the pandemic. Subsequently, we mobilize the Andean indigenous social philosophy of buen vivir which outlines “a way of doing things that is community-centric, ecologically-balanced, and culturally-sensitive”. We elucidate the three ingredients of a ‘buen vivir with data’, namely the fusion of the social with the ecological question, a dialogic and participatory approach to decision-making, and a “localized, relationship-oriented” practice of community care and solidarity based on the recognition of ontological difference and commonalities. We conclude by illustrating how the notion of buen vivir can help us understand the present and collaboratively design a better future for the digital realm and beyond.

Introduction

In the second decade of the 2000s, cities are smart, service work takes place through platforms, society is datafied, and our lives are increasingly quantified and monitored through an array of dashboards and biometric technologies. The world has never been as technologically advanced as it is today. Yet, an infinitesimally small virus was all it took to bring the world to a grinding halt. Economic, educational, and social activities have been paused while the vaccine is rolled out. Friendships, family support, and work have been displaced to the digital sphere. Not only has the Covid-19 pandemic unveiled our fragility in the face of a global health emergency, it has also exposed our dependence on digital infrastructures for a myriad of crucial activities – from remote working to service delivery, from medical care to the monitoring of public space. It has massively accelerated the digital transformation of sectors as diverse as public education and public administration. The magnitude of this global health crisis seems to have prevented us from taking a critical view of the dominant digital paradigm but the time is ripe to re-evaluate the techno-architecture of the present and decide what the digital society of the near future should look like.

Not only has the Covid-19 pandemic unveiled our fragility in the face of a global health emergency, it has also exposed our dependence on digital infrastructures for a myriad of crucial activities.

The New World Information and Communication Order (NWICO), which at the turn of the 1980s was the first multilateral debate to put cultural imperialism on the global agenda, is now only a faint memory. Yet, the scale of the current crisis calls for a rethink of the prevailing social and economic order in ways that are commensurate with justice, equality, and environmental sustainability. In this essay, we review the social costs of the first pandemic of the datafied society to identify critical fault lines of the dominant digital paradigm. We then learn from Latin American traditions and perspectives, especially in the fields of popular education and communication for social change, to sketch out three core elements of a Digital New Deal: critical ecology, liberation pedagogy, and autonomous design. Taken together, these components can intercept and mitigate the new forms of data poverty visibilized and exacerbated by the pandemic. In the concluding section, we mobilize the power of the Andean indigenous social philosophy known as buen vivir – “a way of doing things that is community-centric, ecologically-balanced and culturally-sensitive”. We delineate the three ingredients of a buen vivir with data and illustrate how it can help us understand the present and collaboratively design a better future for the digital realm and beyond.

After the digital divide: Data poverty in the time of Covid-19

The pandemic has upended established ways of doing things, from shopping to traveling, from leisure to learning. It has made a handful of wealthy technology companies even richer, strengthening their quasi monopoly in sectors like e-commerce, cloud computing, and content streaming. Amazon, for instance, has doubled its profit during the pandemic while revenues of Microsoft’s Azure has increased by 48 percent, buoyed by the sales of cloud computing services. Even before the pandemic, state sovereignty had been jeopardized as strategic infrastructures such as healthcare data or border control technology moved into private hands. This trend has only expanded in the aftermath of Covid-19. Tech solutions such as location tracking have allowed us to perform remotely activities that would otherwise require co-presence such as university exams or office work, while legitimizing large-scale data surveillance with no end in sight. “Largely without public debate – and absent any new safeguards,” warned Ronald J. Deibert, author of Reset: Reclaiming the Internet for Civil Society (2020), “we’ve become even more dependent on a technological ecosystem that is notoriously insecure, poorly regulated, highly invasive and prone to serial abuse.”

This has also left huge sections of the world’s population stranded and alienated. In our increasingly digitized and privatized world, only 53 percent of the population has some form of access to the internet, reports the International Telecommunication Union. The digital divide might no longer be high on the list of concerns for policymakers and multilateral organizations, supplanted by the dazzling marketing of tech companies and their efforts in the “zero rating” department, but it is by no means a problem of the past. On the contrary, it is worsened by the new class of advanced skills that are necessary to thrive in the datafied society, including data literacy, basic statistical knowledge, and perhaps even the ability to interpret code. Furthermore, it is now exacerbated by the impossibility of digital disconnection. The Covid-19 crisis has demonstrated that the choice to not be connected to digital networks and apps constitutes a privilege that many citizens cannot afford. For many workers whose livelihoods depend on the decisions taken by the algorithms of digital apps, there is no possible break from the data deluge and the sheer intensity of permanent, coerced connection.1

For many workers whose livelihoods depend on the decisions taken by the algorithms of digital apps, there is no possible break from the data deluge and the sheer intensity of permanent, coerced connection.

The pandemic has laid bare our over-reliance on quantification as a way to know and act upon the virus, with data becoming “a sine qua non condition of existence”.2 At the same time, it has exposed the weaknesses inherent in a number of technological solutions which were once presented as innovative ways to tackle societal inequalities. Biometric welfare in India may have made people go hungry when the risk of disease transmission associated with users’ fingerprints interrupted the distribution of food rations to impoverished families. The reach of citizen-scoring mechanisms based on automated detection of pockets of poverty, like the Colombian System of Possible Beneficiaries of Social Programs (Sisbén), have been extended by Covid-19, but the opacity and contradictions of their faulty algorithms have also been exacerbated. The design of these systems makes it virtually impossible for citizens to reclaim their social rights – let alone have a say in the decision-making process or correct algorithmic errors. Elsewhere in Latin America, distance education has exposed the limitations of a one-size-fits-all solution for rural areas. In Peru, for instance, governmental response to the pandemic glossed over the many socio-technical divides that still affect the country, leaving behind many families with no internet, TV, or radio access. Finally, the pandemic aggravated the already harsh working conditions of gig and delivery workers in both developing and wealthy countries, enslaved to the platform, forcing them to take on extended working hours in risky, unsafe environments, chasing the whims of algorithms.

We can file these distortions of the prevailing techno-solutionism under the rubric of data poverty. As we argued elsewhere, data poverty concerns a multifaceted condition of invisibility that becomes particularly dangerous during a pandemic. It has little to do with data exploitation3 or data colonialism4 which might come across as “luxury problems” in the face of a soaring Covid-19 death toll (which stood at an appalling 1.4 million at the time of writing). Rather, as “data is tied to peoples’ visibility, survival, and care”, the pandemic has revealed two types of data poverty. The first has to do with the scarce statistical and testing capabilities of developing countries. The second concerns a growing number of invisible populations within distinct geopolitical and socio-political contexts – including gig workers, sex workers, and undocumented migrants. While these segments of society suffer invisibility in ordinary times as well, during the pandemic their condition is particularly challenging; being invisible to the state might engender more risks and threats for these populations and their surrounding networks and communities. Furthermore, it can lead to exclusion from subsidies and welfare support – or even basic forms of assistance such as healthcare – even within resource-rich nations.

While data poverty maps into existing inequalities and exacerbates them, it also corresponds to a more general loss of agency for the individual and the community over their well-being. The forms of invisibility it perpetuates can deprive entire populations of voice and sovereignty over their futures. In this respect, investigating the impact of data poverty might help us to situate one of the paradoxes that has defined the governmental response to the Covid-19 crisis. On the one hand, governments across the globe have relied extensively on technocratic know-how, “expert committees”, and ad hoc “task forces” operating outside the control and constraints of democratic accountability. This approach has resulted in the imposition of top-down measures, stripping local communities of the power to define what constitutes community and care during a global pandemic. At the same time, individuals who have no control over this decision-making have frequently been penalized for not adhering to oftentimes draconian rules and dispositions such as lockdowns, their inability to do so framed as “recklessness” and blamed as the key factor in the aggravation of the pandemic. For all these reasons, we argue that rehabilitating the agency of individuals and their communities should be at the core of a Digital New Deal oriented toward destabilizing the dominant digital paradigm and offsetting the externalities of widespread data poverty.

Lessons from Latin American scholarship and movement praxis

We now turn our attention to Latin American scholarship and community practice in search for productive venues to address the problems of data poverty and the resulting loss of agency and sovereignty that go hand in hand with the tech industry’s rising power over public and private life. Latin America is one of the most unequal regions of the world and has suffered a disproportionate loss of lives in the wake of the pandemic. Yet, over past centuries, the region has also nurtured a one-of-a-kind grassroots activism and critical scholarly thinking “pushing the boundaries of what it means to pensar desde el Sur [think from the South]”.5 Three critical fields of scholarly intervention and movement praxis provide food for thought to support our effort to draw the outlines of a Digital New Deal: critical ecology, liberation pedagogy, and autonomous design. These interventions go beyond the exposure of systemic injustice with roots in colonialist exploitation, and offer productive venues for social change centered on the individual and the community.

Taken together, these three disruptive epistemic operations allow us to foreground the autonomy of individuals and communities vis-à-vis the industry and the state, which we argue, should be at the core of any Digital New Deal.

Critical ecology builds on the Latin American traditions of biodiversity and ecology preservation endorsed by eco-social movements like the Brazilian Movimento dos Trabalhadores Rurais sem Terra and the international peasants’ movement Vía Campesina. It can inspire a Digital New Deal for two reasons. Firstly, it firmly positions the ecological question at the center of the social question – since “In the South, the ‘social question’ and the ‘ecological question’ get meshed together”6 – and calls for “a necessary biocentric and bioethical turn”7 in our understanding of our tech-mediated social relations. It invites us to put on “ecological spectacles”8 to acquire a holistic vision “based on a new paradigm which has the Earth as its root and foundation”9. Secondly, it encourages us to reignite the debate on the dependency of much of the Global South on technology developed in the North. “The ecological perspective again opens the discussion about the relations of international dependency,” writes Joan Martinez-Alier in an article aptly titled Ecology of the Poor. The “North-South conflict can now be seen also as an ecological conflict.”10 In a nutshell, the critical ecology tradition interrogates societal over-reliance on technology that, contrary to market propaganda, is the poisonous fruit of twisted political economy histories and has a skyrocketing environmental footprint.

A second tradition of interest concerns liberation pedagogy, also known as pedagogy of autonomy. In the 1960s, Brazilian educator Paulo Freire, influenced by Marxism and liberation theology, criticized the inability of the education system to empower the dispossessed to overcome their condition. In response to this structural problem, Freire proposed an educational approach that centers human beings as active agents in transforming their world and is based on dialogue and horizontal relationships between learners and teachers. Acknowledging that theory and practice of social change should go hand in hand if they are to break the prevailing ‘culture of silence’, liberation pedagogy can nurture a “critical consciousness” (conscientização in Portuguese) seen as “an intrinsic part of cultural action for freedom”11 Liberation pedagogy is of value here for three main reasons. First, it attributes an active role to individuals and communities in shaping their futures. Second, it conceptualizes the unity of praxis (e.g., engagement with technology) and theory (e.g. values) in social change. Finally, it interrogates the paternalistic approach that has often characterized governmental response to the pandemic, evident in coercive measures like lockdowns.

Last but not least, “autonomous design” – a term coined by anthropologist Arturo Escobar – provides another useful lens to productively imagine our post-pandemic futures. It takes the lead from critiques of the development project (“a grand design gone sour”), and from the Zapatista12 cosmovisión (worldview) of the pluriverse, “a world where many worlds fit”. Escobar asks “how difference is effaced and normalized – and conversely, how it can be nourished.”13 Grounded in “an ethical and political practice of alterity that involves a deep concern for social justice, the radical equality of all beings, and nonhierarchy”, autonomous design argues that design (of technology, policies, society) “can be reoriented from its dependence on the marketplace toward creative experimentation with forms, concepts, territories, and materials, especially when appropriated by subaltern communities struggling to redefine their life projects in a mutually beneficial relationship with the Earth.”14 Bringing the pluriverse to the fore encourages us to make room for and give voice to ontological difference in the Digital New Deal – an approach that is diametrically opposed to the one-size-fits-all techno-solutionism15 of our pandemic reality and helps to overcome the “data universalism16 that have characterized many Covid-related solutions.

Taken together, these three disruptive epistemic operations allow us to foreground the autonomy of individuals and communities vis-à-vis the industry and the state, which we argue, should be at the core of any Digital New Deal. In light of the growing data poverty and the lessons learnt from Latin American movements and thinkers, we now examine how the dominant digital paradigm can be reimagined for equity, justice, and sustainable futures. In the following section, we we argue that the Andean indigenous social philosophy of buen vivir – defined as “a way of doing things that is community-centric, ecologically-balanced and culturally-sensitive” – can help us understand the present and collaboratively design a better future for the digital realm and beyond.

Nurturing integrated autonomy: Buen vivir with data

Buen vivir (itself a Spanish translation of the original Quechua sumak kawsay) is translated into English through rather imprecise phrases such as “good living” or “living well”. It points to the harmonious coexistence of human beings with each other as well as the surrounding ecosystem. It is also connected to a sense of the collective. While neoliberalism promotes individual rights, buen vivir shifts priorities away from economic growth as an end in itself towards social and environmental wellbeing and meaningful human connections. It insists that the rights of the individual cannot be disentangled from those of peoples, communities, and nature. Not surprisingly, the notion has gained traction in recent years, finding itself enshrined in Ecuador’s new constitution in 2008 with the recognition of the rights of nature and cultural diversity.

As sustainable development scholar Eduardo Gudynas explains, there are two common misunderstandings that attach themselves to the notion of buen vivir.17 Firstly, buen vivir has often been injected with an idealized return to an imagined idyllic pre-Colombian past. In reality, it is a concept shaped not only by indigenous thinking, but also Western critiques of capitalism over the last three decades, especially in relation to feminist critical thinking and environmentalism. Secondly, while the term has been superficially equated to Western notions of wellbeing and welfare, it is radically different as it focuses not just on the individual and their needs, but is also rooted within the social context of the community and the environmental context in which the individual is embedded. We evoke buen vivir here because it intercepts some of the key concerns illustrated above, most notably the inevitable interconnection between humankind and the environment in the critical ecology approach, the agency of individuals and communities put forward by liberation pedagogy, and the coexistence of ontological difference cherished by autonomous design.

Rather than conceiving buen vivir as a strict blueprint for change, we should view it as a launchpad for fresh thinking and new perspectives.

In the context of the Covid crisis, buen vivir can help us effect an economic and social “reset”18 and rethink our mid- and long-term priorities. Linked to degrowth, the notion can help us redefine how we understand the limits of the dominant digital paradigm. It can inspire us to set new parameters for a future trajectory and prefigure possibilities for contesting the capitalist “there-is-no-alternative” imperative. Through this notion and related rights, we can, for example, reimagine and reorient health, travel, and education away from exploitative models that disregard people, places, and the natural environment and usher in a transformative change in society. At the same time, the focus on buen vivir can promote social and environmental wellbeing and strengthen meaningful human connections.

We should, however, resist the temptation to romanticize the complex notion of buen vivir and strip it from socio-political contexts. Ecuador introduced buen vivir into its constitution not merely as an ethical principle (as in the case of Bolivia) but also embedded it as a set of rights. Yet it failed to manage the current health emergency due to the usual corollary of an overworked hospital system and a helpless population. How, then, should we react to Ecuador’s catastrophic handling of the pandemic? Unfortunately, the analysis of public policies adopted in the last decade reveals a worrying discrepancy between the promises of the official agenda and programs implemented on the ground. There is an evident gap between the principles and rights emanating from the notion of buen vivir and the policies and measures implemented by countries such as Bolivia and Ecuador in response to the crisis. This is why it is imperative to transform buen vivir into a concrete set of policies, activities, and regulations that can improve wellbeing. The ethical principle and the rights that emanate from this concept provide the right direction, but principles and promises must result in on-ground policies and measures that speak to the lived experiences of the people.19 What the case of Ecuador makes evident is that rather than conceiving buen vivir as a strict blueprint for change, we should view it as a launchpad for fresh thinking and new perspectives that “helps us see the limits of current development models and […] allows us to dream of alternatives that until now have been difficult to fulfil.”

If “living with data”20 is our inevitable present and post-pandemic future, can we imagine a buen vivir for the datafied society? We argue that buen vivir with data entails foregrounding at least three key ingredients. The first concerns the fusion of the social with the ecological question, or in other words, the search for a harmonious relation between human and nature. This is obviously of paramount importance in an age of climate emergency. However, it also entails deconstructing the notion that a datafied society is inherently the green alternative to the fossil fuel era. The data economy is expected to consume one-fifth of global electricity by 2025, but this figure corresponds to the pre-pandemic energy consumption. In 2016, data centers had the same carbon footprint as the aviation industry. A Digital New Deal must seek to put the social and the ecological questions at the core as the two are intimately connected.21

A Digital New Deal must seek to put the social and the ecological questions at the core as the two are intimately connected.

The second ingredient for a buen vivir with data points to the necessary dialogic and participatory approach that must be at the center of any decision-making that concerns people, paving the way for the autonomy of and an active role for communities in shaping their datafied futures. Without downplaying the role of expertise in a global crisis like the one we currently face, centering dialogue à la Freire generates situated knowledges and individual as well as collective empowerment.

Finally, the third ingredient in our list has to do with a “localized, relationship-oriented”22 practice of community care and solidarity based on the acknowledgment of ontological difference as well as commonalities. We have seen many instances of this spontaneous solidarity at play during the pandemic, as testified by the blog ‘Covid-19 From the Margins’, among others.23 Rather than just filling in for the (many) failures of the (welfare) state, solidarity and community care should be seen as a way to reclaim agency and sovereignty while defining the kind of societies we want to live in. An ambitious and much-needed green recovery program based on environmentally-friendly growth and an expansion of renewable energy in Latin America can offer a platform where the diverse elements foregrounded in this intervention can be reconciled and experimented with. Only in this way can we hope to reconcile a Digital New Deal with local preferences, values, customs, worldviews, and practice, and make room for a sustainable digital future.

Notes

1 Simone Natale and Emiliano Treré, “Vinyl Won’t Save Us: Reframing Disconnection as Engagement,” Media, Culture & Society 42, no. 4 (2020): 626–33, https://doi.org/10.1177/0163443720914027.
2 Stefania Milan and Emiliano Treré, “The Rise of the Data Poor: The COVID-19 Pandemic Seen from the Margins,” Social Media + Society, no. July (2020), https://doi.org/10.1177/2056305120948233.
3 Shoshana Zuboff, The Age of Surveillance Capitalism (New York: Profile Books, 2019).
4 Nick Couldry and Ulises A. Mejias, “Data Colonialism: Rethinking Big Data’s Relation to the Contemporary Subject,” Television & New Media 20, no. 4 (May 1, 2019): 336–49, https://doi.org/10.1177/1527476418796632.
5 Milan and Treré, “The Rise of the Data Poor: The COVID-19 Pandemic Seen from the Margins,” 2.
6 Joan Martinez-Alier, “Ecology and the Poor: A Neglected Dimension of Latin American History,” Journal of Latin American Studies 23, no. 3 (1991): 621–39.
7 Alejandro Carretero Barranquero and Chiara Saez Baeza, “Latin American Critical Epistemologies toward a Biocentric Turn in Communication for Social Change: Communication from a Good Living Perspective,” Latin American Research Review 52, no. 3 (2017): 435, https://doi.org/10.25222/larr.59.
8 Martinez-Alier, “Ecology and the Poor: A Neglected Dimension of Latin American History,” 636.
9 Moacir Gadotti, Pedagogia Da Terra (São Paulo: Petrópolis, 1990), 15 (authors’ translation from the Portuguese original).
10 Martinez-Alier, “Ecology and the Poor: A Neglected Dimension of Latin American History,” 623.
11 Paulo Freire, Pedagogy of the Oppressed (New York: Continuum, 1968); see also Ana Cristina Suzina and Thomas Tufte, “Freire’s Vision of Development and Social Change: Past Experiences, Present Challenges and Perspectives for the Future,” International Communication Gazette 82, no. 5 (July 31, 2020): 411–24, https://doi.org/10.1177/1748048520943692.
12 R. Stahler-Sholk, “Resisting Neoliberal Homogenisation. The Zapatista Autonomy Movement,” Latin American Perspectives 34, no. 2 (2007): 48–63.
13 Arturo Escobar, Designs for the Pluriverse. Radical Interdependence, Autonomy, and the Making of Worlds (Durham, NC: Duke University Press, 2018), xiii, xvi.
14 Escobar, xvi–xvii.
15 Stefania Milan, “Techno-Solutionism and the Standard Human in the Making of the COVID-19 Pandemic,” Big Data & Society, 2020, https://doi.org/10.1177/2053951720966781.
16 Stefania Milan and Emiliano Treré, “Big Data from the South(s): Beyond Data Universalism,” Television & New Media 20, no. 4 (2019): 319–35, https://doi.org/10.1177/1527476419837739.
17 Eduardo Gudynas, “Buen Vivir: Today’s Tomorrow,” Development 54, no. 4 (2011): 441–47, https://link.springer.com/article/10.1057/dev.2011.86.
18 Phoebe Everingham and Natasha Chassagne, “Post COVID-19 Ecological and Social Reset: Moving Away from Capitalist Growth Models towards Tourism as Buen Vivir,” Tourism Geographies, 2020, 555–66, http://dx.doi.org/10.1080/14616688.2020.1762119.
19 Naomi Joy Godden, “Community Work, Love and the Indigenous Worldview of Buen Vivir in Peru,” International Social Work, 2020, https://doi.org/10.1177/0020872820930254.
20 Deborah Lupton, “How Do Data Come to Matter? Living and Becoming with Personal Data,” Big Data & Society 5, no. 2 (July 1, 2018): 2053951718786314, https://doi.org/10.1177/2053951718786314; Helen Kennedy, “Living with Data: Aligning Data Studies and Data Activism Through a Focus on Everyday Experiences of Datafication,” Krisis: Journal for Contemporary Philosophy 1 (2018), http://krisis.eu/living-with-data/.
21 Martinez-Alier, “Ecology and the Poor: A Neglected Dimension of Latin American History.”
22 Godden, “Community Work, Love and the Indigenous Worldview of Buen Vivir in Peru.”
23 Stefania Milan, Emiliano Treré, and Silvia Masiero, COVID-19 from the Margins: Pandemic Invisibilities, Policies and Resistance in the Datafied Society (Amsterdam: Institute for Networked Cultures, 2020).

Stefania Milan (stefaniamilan.net) is Associate Professor of New Media and Digital Culture at University of Amsterdam. Her work explores the interplay between digital technology, activism and governance. Stefania is the Principal Investigator of DATACTIVE (data-activism.net) and “Citizenship and standard-setting in digital networks”, funded by the European Research Council and the Dutch Research Council. In 2017, she co-founded the Big Data from the South Research Initiative, investigating the impact of datafication and surveillance on communities at the margins. Stefania is the author of Social Movements and Their Technologies: Wiring Social Change (Palgrave Macmillan, 2013/2016) and co-author of Media/Society (Sage, 2011).

Emiliano Treré is Senior Lecturer in Media Ecologies and Social Transformation in the School of Journalism, Media and Culture (JOMEC) at Cardiff University, UK. He’s globally recognized as a ‘bridge’ between the Western and the Latin American traditions at the intersection between communication, activism and data studies. He’s a member of the Data Justice Lab where he’s the Co-PI of the project ‘Towards Democratic Auditing: Civic Participation in the Scoring Society’, funded by the Open Society Foundations. He is also the co-founder of the ‘Big Data from the South’ Research Initiative. His monograph Hybrid Media Activism (Routledge, 2019) won the Outstanding Book Award of the Activism, Communication and Social Justice Interest Group of the International Communication Association.

Together with Silvia Masiero from the University of Oslo, Stefania and Emiliano are the editors of the open access book COVID-19 from the Margins: Pandemic Invisibilities, Policies and Resistance in the Datafied Society (Theory on Demand Series, Institute of Network Cultures, 2021) that stems from a blog with the same title launched in May 2020 and represents a snapshot of the datafied society during the pandemic, amplifying the marginalized voices of 75 authors from 25 countries in 5 languages.

November 1, 2020December 30, 2020

Imagining the AI We Want: Towards a New AI Constitutionalism

Imagining the AI We Want: Towards a New AI Constitutionalism

Jun-E Tan

Imagining the AI We Want: Towards a New AI Constitutionalism

Jun-E Tan

Artificial intelligence (AI) technologies promise vast benefits to society but also bring unprecedented risks when abused or misused. As such, a movement towards AI constitutionalism has begun, as stakeholders come together to articulate the values and principles that should inform the development, deployment, and use of AI. This essay outlines the current state of AI constitutionalism. It argues that existing discourses and initiatives centre on non-legally binding AI ethics that are overly narrow and technical in their substance, and overlook systemic and structural concerns. Most AI guidelines and value statements come from small and privileged groups of AI experts in the Global North and reflect their interests and priorities, with little or no inputs from those affected by these technologies. This essay suggests three principles for an AI constitutionalism rooted in societal and local contexts: viewing AI as a means instead of an end, with an emphasis on clarifying the objectives and analyzing the feasibility of the technology in providing solutions; emphasizing relationality in AI ethics, moving away from an individualistic and rationalistic paradigm; and envisioning an AI governance that goes beyond self-regulation by the industry, and is instead supported by checks and balances, institutional frameworks, and regulatory environments arrived at through participatory processes.

1. Introduction

The ability of machines to learn from the past and make predictions about the future promises vast improvements to our individual and collective lives. With artificial intelligence (AI), we are able to rapidly detect patterns and anomalies in data, discover new insights, and inform decision-making. Better public health and transportation, more efficient services and increased accessibility, climate change mitigation and adaptation, etc. are part of a long list of the potential benefits of AI.

Governments and companies, eager to deploy and employ these technologies, often cite these potential benefits to frame the adoption of AI as a matter of inevitable progress. The possibilities of ‘AI for good’ are endless, we are told, as long as we provide the machines with enough data to churn. The technology is neutral, we are assured, and AI experts are working on perfecting these systems, complete with ethical considerations, so that negative impacts are minimized. Yet, as more AI-enabled systems are rolled out and adopted, accounts of unintended consequences and intentional abuse continue to accumulate at an alarming pace. Cautionary tales of the unintended consequences of AI abound – machines exacerbating racial biases,1 exam grading algorithms turning out to be hugely erroneous,2 and automated social protection schemes failing society’s most vulnerable, leading to death by starvation in extreme cases.3 Then there are egregious cases of intentional abuse – state and non-state actors leveraging AI capabilities to surveil entire populations,4 manipulate voter behavior,5 or produce highly realistic manipulated audio-visual content (also known as deepfakes) that can undermine the foundations of trust in society.6

Amidst these promises and anxieties, a movement towards AI constitutionalism has begun in recent years, as stakeholders from the market, state, and civil society put forth visions of what ethical AI should constitute and how these technologies should be governed. By AI constitutionalism, we mean the process of norm-making or the articulation of key values and principles which guide the design, construction, deployment, and usage of AI technologies. The concept is inspired by the more established body of work on digital constitutionalism, defined by Dennis Redeker and his colleagues as “a constellation of initiatives [including declarations, magna cartas, charters, bills of rights, etc.] that have sought to articulate a set of political rights, governance norms, and limitations on the exercise of power on the Internet”,7 8 9which are not only important for political and symbolic reasons, but also for shaping laws and regulations in the digital era.

Indeed, the process of shaping norms is exceedingly important as it entails a reckoning with our collective values. Norms are a sort of moral compass that guide us towards an imagined future. Especially in the context of AI, a nascent technology whose direction and implications are not yet fully known, some big picture questions need to be discussed. What are our goals and principles as a society? Where do we draw the line between possible trade-offs and values that are sacred and must be protected at all costs? What behaviors do we reward or sanction? And depending on the answers to these questions, what types of AI should we build (or not build) to aid our progress as a civilization?

In this essay, I outline the current state of AI constitutionalism, and provide arguments about why existing discourses and initiatives in this space will not lead us towards a future that is cognizant of human dignity and sustainable development. Based on these arguments, I imagine a new AI constitutionalism that imbues technological discourses with socio-political relevance, thus opening up discussions rooted in specific applications and contexts. Finally, I put forth three principles that should guide future initiatives in AI constitutionalism:

1) AI must be viewed as a ‘means’ instead of an ‘end’,
2) AI ethics must emphasize relationality and context, and
3) AI governance must go beyond self-regulation by the industry.

2. AI ethics: Why it is not enough

In the last five years, the area of AI ethics has become increasingly active, with stakeholders at various levels and in different geographic locations issuing policy statements or guidelines on what ethical AI is or should be. Together, these provide a fertile ground for analyzing the underlying priorities and assumptions that mark the current state of AI constitutionalism and shape the character of norm-making in the field.

Anna Jobin and her colleagues at ETH Zurich gathered at least 84 institutional reports or guidance documents on ethical AI in their 2019 analysis of the global landscape of AI ethics guidelines and principles.10 Most of these documents come from private companies (22.6 percent), government agencies (21.4 percent), academic and research institutions (10.7 percent), and intergovernmental or supranational organizations (9.5 percent). Prominent examples at the government level include the OECD AI Principles and the European Commission’s Ethics Guidelines for Trustworthy AI. Corporations, civil society, and other multistakeholder groups have also come up with their own non-legally binding positions and manifestos. Examples include Google’s AI principles,11 the Universal Guidelines for Artificial Intelligence developed by The Public Voice,12 the Tenets of Partnership on AI to Benefit People and Society,13 and the Beijing AI Principles.

There is some convergence in the values or principles that emerge as paramount in these ethical AI guidelines and statements. In Jobin and her colleagues’ analysis, the most commonly articulated principles are those of transparency, justice and fairness, non-maleficence (causing no harm), responsibility, and privacy. Six others appear less frequently, and in the following order: beneficence (promoting good), freedom and autonomy, trust, dignity, sustainability, and solidarity. However, despite the convergence in the values that are prioritized by existing AI policy documents, the picture becomes increasingly complex when we look beyond the terms themselves, and focus on their interpretation and implementation. At this point, some divergence or lack of consensus begins to emerge.

Most articulations on AI ethics tend to focus on narrow technical problems and fixes. An evaluation by Thilo Hagendorff from the University of Tübingen14 of 22 ethical AI guidelines, finds that the most popular values (such as accountability, explainability, and privacy) tend to be the easiest to operationalize mathematically, while the more systemic problems are overlooked. These systemic problems, Hagendorff suggests, include the weakening of social cohesion (through filter bubbles and echo chambers, for instance), the political abuse of AI systems, environmental impacts of the technology, and trolley problems (in which there is no clear decision on which choice is more ethical; for instance, having to choose between killing a pedestrian or the driver of an autonomous vehicle). Moreover, very little attention is paid to the ethical dilemmas plaguing the industry itself – the lack of diversity within the AI community or the invisible and precarious labor that goes into enabling AI technologies, such as dataset labeling and content moderation.

Technology is framed as an inevitable step towards progress; its application is taken for granted regardless of the context. In other words, being ethical only entails “building better”; “not building” is not an option.

Discussions on AI ethics are also based on certain assumptions and framings – “moral backgrounds” according to Daniel Green and his colleagues15 – which set the scope and direction of AI constitutionalism. Green and his colleagues’ critical review of seven high-profile value statements in ethical AI finds that the discourse is in line with conventional business ethics but sidesteps the imperatives of social justice and considerations of human flourishing. Technology is framed as an inevitable step towards progress; its application is taken for granted regardless of the context. In other words, being ethical only entails “building better”; “not building” is not an option. Furthermore, scrutiny of the ethicality of AI technologies is restricted to the design level, and does not extend to the business level. A design-level approach to ethical AI, for instance, looks only at reducing the racial bias of facial recognition software, without questioning the ethics of deploying this technology for mass surveillance in the first place. Another implicit assumption is that ethical design is the exclusive domain of experts within the AI community (for instance, tech companies, academics, lawyers). Product users and buyers are just stakeholders who “have AI happen to them”. Seemingly ironclad values and principles start to show cracks when these assumptions are questioned. What can we expect from ethical AI that is techno-deterministic and does not take a critical view of what the technology is used for? For whom and in whose interest are AI technologies being built and deployed?

More challenges emerge as we move away from the substantive content of AI ethics discourses and start putting principles into practice. First, AI ethics is, at best, seen as good intentions with no guarantee for good actions, and at worst, criticized as deliberate attempts to ward off hard regulations. Ethics whitewashing is a real concern as corporations eschew regulations and put forth self-formulated ethical guidelines as sufficient for AI governance. In practice, ethical considerations come in only after the top priorities of profit margins, client requirements, and project constraints have been resolved.16 It is difficult to rely on the goodwill of corporations which have arguably co-opted the academic field of AI ethics in an attempt to delay regulations.17 The existence of ethical guidelines does not guarantee that companies will be ethical. There are well-documented instances of companies resorting to ethics dumping and shirking wherever convenient, most obvious in the precarious work conditions of content moderation workers in the Global South.18

Ethics whitewashing is a real concern as corporations eschew regulations and put forth self-formulated ethical guidelines as sufficient for AI governance. In practice, ethical considerations come in only after the top priorities of profit margins, client requirements, and project constraints have been resolved.

Mainstream discussions on AI ethics assume that technologies exist in a vacuum, devoid of context. These assumptions are often made by a very small and privileged group of people in the Global North,19 who do not see the need to engage people outside of their own community even though the tools they build significantly impact the world at large. When AI technologies are designed and deployed without attention to context, systemic harms are amplified, and entire populations, especially in the Global South, can be rendered more vulnerable.20 Above all, discussions on ethics remain just that – discussions – not legally binding and enforceable. AI ethics, in its current state, does not lead to ethical AI. If we are serious about making technology work for the people and the planet, our efforts towards AI constitutionalism need to look beyond dominant discourses. This is what I attempt to do in the following section.

3. Towards a new AI constitutionalism

Already, there is mounting resistance against corporations and their maneuvering of ethical self-regulation. Carly Kind, Director of the Ada Lovelace Institute, observes a “third wave” of AI ethics, following a first wave comprising of principles and philosophical debates, and a second wave focusing on narrow, technical fixes. Kind argues that the third wave of AI ethics is less conceptual, more focused on applications, and takes into account structural issues. Research institutes, activists, and advocates have mobilized to effect changes in AI design and use, with some successes such as legislations and moratoria on the use of algorithms for applications such as test grading and facial recognition.21 An emerging body of work on “radical AI” aims to expose the power imbalances exacerbated by AI and offer solutions.22

The Covid-19 pandemic has laid bare these structural imbalances and triggered a renewed rush towards digitalization, with its associated concerns. Against this backdrop, we have also seen a shift towards a more critical view of AI and its implementation. It is precisely at this point that a new AI constitutionalism, or at least a significantly upgraded one, is needed and possible. We must seize this moment to take control of the narrative and determine what is important for our collective future, and how AI can help us achieve this vision. This is particularly urgent for communities that lie outside of the AI power centres, whose views remain underrepresented in global norm-making and standards-setting, and whose contexts may not be understood by those building the technologies and making the ethical decisions that underpin them. Some groups have already rallied together to collect and compile principles important to their communities, such as the Digital Justice Manifesto put together by the Just Net Coalition23 (a global network of civil society actors based mostly in the Global South), and the CARE Principles for Indigenous Data Governance by the Global Indigenous Data Alliance.24

Societal constitutionalism is a process of constitutional rule-making that starts from social groups like civil society, representatives from the business community, or multistakeholder coalitions. As noted by Redeker et al.,25 the process can be seen in three phases: “an initial phase of coming to an agreement about a set of norms by a specific group; a second phase in which these norms become law; and a third phase in which reflection about this builds up to achieving constitutional character”. Thus far, most of the norm-making in AI has been top down, coming from high-level policymakers, transnational Big Tech firms, or small groups of elites at national levels, reflecting the priorities of these groups. This is insufficient not only from a democratic point of view, but also because the vast applications of AI across different fields, from agriculture to zoology, necessitates the inputs of field experts who understand local contexts and implications.

A reimagination of AI constitutionalism should move the discourse from a purely technological approach to take societal considerations into account. It needs to move from the realm of the abstract to focus on application. Governance norms, political rights, and limitations of power within the field of AI should be democratically deliberated at different levels of a nested societal system and within different political jurisdictions (e.g. city, state, national, regional, international levels). This would allow all stakeholders and interest groups (e.g. professional associations, business associations, civil society networks, grassroots communities) to contribute meaningfully to the governance of AI from their own vantage points. This collective bottom-up approach, I propose, should be underpinned by the following considerations:

3.1. AI as a means to an end (and not an end in itself)

One prevalent assumption about AI is that it is an inevitable step towards progress, that AI technologies, if built well, can solve any problem. The tech industry’s optimism in this regard is echoed by the state. As a result, AI becomes an end in itself instead of a means to an end. Technological determinism is reflected in the willingness of governments to keep the AI regulatory environment minimalist, in order to not stifle innovation. In the rush to remain competitive in a high-tech, machine-enabled future, governments have outlined national AI strategies to promote research, talent, and investments in the sector, while remaining noncommittal about safeguarding against potential human rights violations.26 The possibilities of ‘AI for good’ begin to fall flat when seen from this perspective. If the objective of AI is indeed to bring social and economic benefits to the people, governments need to prioritize human rights over the needs of the industry and address the thorny issues that result from these technologies, including mass job displacements and a rapid concentration of wealth in the hands of a few.

For AI to be the means to an end, we need to first clarify our objectives and then critically assess if using AI is the best way to achieve them. In this, we can follow the lead of vision statements such as the UN Sustainable Development Goals and the Universal Declaration of Human Rights which have clearly-specified objectives, arrived at through extensive international consultations, negotiations, and agreements. The UN SDGs also come with a specific timeline (by 2030) as well as established indicators to help evaluate if the objectives have been met. Additionally, we can draw on relevant national27 and sectoral policies,28 or even organizational vision and mission statements which have often gone through contestations and consensus-building by multiple stakeholders. The use of AI needs to be grounded in such clearly-stated visions and blueprints for a better society.

Furthermore, it needs to be acknowledged that AI is only one tool in a full range of options, and not all problems should/can be solved by such technologies. In a presentation at Princeton University, titled ‘How to recognize AI snake oil’, Arvind Narayanan argued that while AI has become highly accurate in applications of perception (e.g. content identification, speech to text, facial recognition), and is improving in applications of automating judgment (e.g. spam detection, detection of copyrighted material, content recommendation), applications that promise to predict social outcomes (e.g. predicting criminal recidivism, job performance, terrorist risk) are still “fundamentally dubious”. Justifying the use of the term ‘snake oil AI’, Narayanan pointed to existing studies that show that AI backed by thousands of datasets is not substantially better at predicting social outcomes than manual scoring using only a few data points. Discussions on AI constitutionalism should, therefore, be grounded in clearly-stated objectives and feasibility studies, as well as allow room for rejecting AI usage, especially when there are potential risks for stakeholder communities.

3.2. AI ethics to emphasize relationality and context

According to Sabelo Mhlambi from Harvard University, Western ethical traditions tend to emphasize “rationality” as a prized quality of personhood – along the lines of “I think, therefore I am” – where humanness is defined by the individual’s ability to arrive at the truth through logical deduction.29 Not only is this an inherently individualistic worldview, it has also been used to justify colonial and racial subjugation based on the belief that certain groups are not rational enough, and therefore, do not deserve to be treated as humans. An AI framework that prioritizes rationality and individualism ignores the interconnectedness of our globalized and digitalized world, and serves to exacerbate historical injustices and perpetuate new forms of digital exploitation. The failure to recognize the relationality of people, objects, and events has left us hurtling towards countless crises and avoidable tragedies (such as man-made climate change exacerbated by nations’ inability to coordinate a multilateral response).

An AI framework that prioritizes rationality and individualism ignores the interconnectedness of our globalized and digitalized world, and serves to exacerbate historical injustices and perpetuate new forms of digital exploitation.

Scholars of technology and ethics have offered diverse philosophies anchored in relationality – such as Ubuntu,30 Confucianism,31 and indigenous epistemologies (e.g. Hawai’i, Cree, and Lakota)32 – that view ethical behavior in the context of social relationships and relationships with non-human entities such as the environment, or even sentient AI in the future. The moral character of AI must be judged based on its impacts on social relationships and the overall context and environment it interacts with. For example, evaluating AI-powered automated decision-making systems through the ethical lens of Ubuntu, Mhlambi points to a range of ethical risks. These include the exclusion of marginalized communities because of biases and non-participatory decision-making, societal fragmentation as a result of the attention economy and its associated features, and inequalities resulting from the rapid concentration of data and resources in the hands of a powerful few.33 In contrast, current ethical AI frameworks say very little about extractive business models of surveillance capitalism or the heavy carbon footprint of training AI.

The development and deployment of AI technologies take place in a complex, networked world. Discussions on AI constitutionalism thus need a paradigmatic shift in ethics from the individual to the relational, and must consider issues as diverse as collective privacy and consent, power and decolonization, invisible labor and environmental externalities in AI supply chains, as well as unintended consequences (for instance, when systems interact in unpredictable ways with their particular environments).

3.3. AI governance to go beyond self-regulation by the industry

The tech ethos of “move fast and break things” becomes much less persuasive if we make the connection that an algorithmic tweak in Facebook can lead to (or prevent) a genocide in Myanmar.34 Some friction in the system, by way of checks and balances, is necessary to make sure that any technology released is safe for society, and to guard against AI exceptionalism. Besides safety, AI can have significant systems-level opportunities and threats. An AI Security Map drawn by Jessica Newman at the University of Berkeley proposes 20 such areas – digital/physical (e.g. malicious use of AI and automated cyberattacks, secure convergence/integration of AI with other technologies), political (e.g. disinformation and manipulation, geopolitical strategy, and international collaboration), economic (e.g. reduced inequalities, promotion of AI research and development), and social domains (e.g. privacy and data rights, sustainability and ecology).35 It is difficult to imagine that self-regulation in the AI industry would carry us through all of these different areas, across different sectoral and geographical contexts.

The World Economic Forum defines governance as “making decisions and exercising authority in order to guide the behavior of individuals and organizations”.36 As AI constitutionalism is ultimately about governance of technology, discussions should not stop at AI ethics or be left to experts. Instead, we should explore other mechanisms such as institutional frameworks and regulatory environments to bridge principles and practice. Under the broad ambit of AI constitutionalism, diverse governance issues can be debated at various policy levels – for example, cross-border data flows and data sovereignty can be discussed at the international level; hard limits against malicious use of AI and data governance frameworks can be discussed at a national level; data privacy, especially in sensitive sectors such as finance and health, can be taken up at a sectoral level.

Broad participation in AI governance can have positive spillover effects such as trust-building, pooling multidisciplinary knowledge, and capacity-building across different domains. For this, a new AI constitutionalism needs to push for stakeholder participation at various levels. Underrepresented nations need to be invited and supported in norm-making initiatives at the international level; civil society must be consulted and engaged at national and city levels. These discussions should not focus only on the technical, and the onus should be on the AI community to make the information accessible to all. As a recent report by Upturn and Omidyar Network puts it, non-technical properties about an automated system, such as clarity about its existence, purpose, constitution,37 and impact, can be “just as important, and often more important” than its technical artifacts (its policies, inputs and outputs, training data, and source code).38

4. End reflections

AI constitutionalism needs to be squarely rooted in societal contexts and must make the connections between technology and the traditional fault lines of power and privilege. The resulting discourses will be complex and contested, reflecting the messy realities that the technology is embedded in, rather than the neat lists of values and principles that see the technology in a vacuum. The values of AI ethics (such as fairness, accountability, and transparency) will take on different, more consequential meanings when applied at a societal level, challenging actors in the Global North to explore ways to decolonialize AI and distribute its benefits based on solidarity, not paternalism.

By lifting AI constitutionalism from its narrow, technological focus to the societal and application level, we will find opportunities for greater participation and a more diverse range of perspectives to shape governance norms, power structures, and political rights in the field of AI. This will make space for actors in the Global South to deliberate on our own AI-enabled future, drawing from our cultural philosophies, and governing AI through our laws and institutional frameworks. It is critical that we claim this space to govern technology, as the unprecedented advances promised by AI can only be fulfilled if it is carefully controlled. Forfeiting this space would leave us stranded with a vastly different outcome of being controlled by technology and those wielding it.

Notes

1 https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.
2 https://blogs.lse.ac.uk/impactofsocialsciences/2020/08/26/fk-the-algorithm-what-the-world-can-learn-from-the-uks-a-level-grading-fiasco/.
3 https://www.theguardian.com/technology/2019/oct/14/automating-poverty-algorithms-punish-poor.
4 https://www.nytimes.com/2019/04/14/technology/china-surveillance-artificial-intelligence-racial-profiling.html.
5 https://www.theguardian.com/technology/2019/mar/17/the-cambridge-analytica-scandal-changed-the-world-but-it-didnt-change-facebook.
6 https://www.forbes.com/sites/robtoews/2020/05/25/deepfakes-are-going-to-wreak-havoc-on-society-we-are-not-prepared/#50a7daf57494.
7 Other researchers have also found it useful to adopt Redeker et al.’s conceptual framework of digital constitutionalism into the context of AI, such as a mapping effort on ethical and rights-based approaches to principles of AI, conducted by Jessica Fjeld et al. in Harvard University’s Berkman Klein Center for Internet and Society. See Fjeld, J., Achten, N., Hilligoss, H., Nagy, A., & Srikumar, M. (2020). Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI (SSRN Scholarly Paper ID 3518482). Social Science Research Network. https://papers.ssrn.com/abstract=3518482.
8 Redeker, D., Gill, L., & Gasser, U. (2018). Towards digital constitutionalism? Mapping attempts to craft an Internet Bill of Rights. International Communication Gazette, 80(4), 302–319. https://doi.org/10.1177/1748048518757121.
9 Even though this is by no means the only interpretation of what digital constitutionalism means, it is the definition that I find to be helpful for the purpose of the essay. For more discussions on how others have defined the term, see more at Celeste, E. (2018). Digital Constitutionalism: Mapping the Constitutional Response to Digital Technology’s Challenges (SSRN Scholarly Paper ID 3219905). Social Science Research Network. https://papers.ssrn.com/abstract=3219905.
10 Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2.
11 https://ai.google/principles.
12 https://thepublicvoice.org/ai-universal-guidelines/.
13 https://www.partnershiponai.org/tenets/.
14 Hagendorff, T. (2020). The Ethics of AI Ethics: An Evaluation of Guidelines. Minds and Machines, 30(1), 99–120. https://doi.org/10.1007/s11023-020-09517-8.
15 Greene, D., Hoffmann, A. L., & Stark, L. (2019, January 8). Better, Nicer, Clearer, Fairer: A Critical Assessment of the Movement for Ethical Artificial Intelligence and Machine Learning. Hawaii International Conference on System Sciences 2019 (HICSS-52). https://aisel.aisnet.org/hicss-52/dsm/critical_and_ethical_studies/2.
16 Orr, W., & Davis, J. L. (2020). Attributions of ethical responsibility by Artificial Intelligence practitioners. Information, Communication & Society, 23(5), 719–735. https://doi.org/10.1080/1369118X.2020.1713842.
17 https://theintercept.com/2019/12/20/mit-ethical-ai-artificial-intelligence/.
18 Floridi, L. (2019). Translating Principles into Practices of Digital Ethics: Five Risks of Being Unethical. Philosophy & Technology, 32(2), 185–193. https://doi.org/10.1007/s13347-019-00354-x.
19 Increasingly, researchers are arguing that “Global South” and “Global North” are not defined by geographical boundaries. There can be multiple “Souths”, even within developed contexts, where communities are oppressed, under-developed and marginalised. Similarly, “Norths” can exist in developing countries among the privileged and powerful. See Arun, C. (2019). AI and the Global South: Designing for Other Worlds (SSRN Scholarly Paper ID 3403010). Social Science Research Network. https://papers.ssrn.com/abstract=3403010.
20 Arun, C. (2019). AI and the Global South: Designing for Other Worlds (SSRN Scholarly Paper ID 3403010). Social Science Research Network. https://papers.ssrn.com/abstract=3403010.
21 https://venturebeat.com/2020/08/23/the-term-ethical-ai-is-finally-starting-to-mean-something/.
22 https://radicalai.net/.
23 https://justnetcoalition.org/digital-justice-manifesto.pdf.
24 https://www.gida-global.org/care.
25 Citing from Teubner (2012), in Redeker, D., Gill, L., & Gasser, U. (2018). Towards digital constitutionalism? Mapping attempts to craft an Internet Bill of Rights. International Communication Gazette, 80(4), 302–319.https://doi.org/10.1177/1748048518757121.
26 https://www.gp-digital.org/wp-content/uploads/2020/04/National-Artifical-Intelligence-Strategies-and-Human-Rights%E2%80%94A-Review_April2020.pdf.
27 An example would be Malaysia’s Shared Prosperity Vision 2030, accessible at https://www.pmo.gov.my/wp-content/uploads/2019/10/SPV2030-summary-en.pdf.
28 Some examples from Malaysia: the National Policy on Biological Diversity (2016-2025), the Malaysia Education Blueprint (2013-2025), the National Policy on Industry 4.0 (Industry4WRD).
29 Mhlambi, S. (2020). From Rationality to Relationality: Ubuntu as an Ethical and Human Rights Framework for Artificial Intelligence Governance (No. 2020–009; Carr Center Discussion Paper Series, p. 31). Harvard Kennedy School Carr Center for Human Rights Policy. https://carrcenter.hks.harvard.edu/files/cchr/files/ccdp_2020-009_sabelo_b.pdf.
30 Ibid.
31 Wong, P.-H. (2012). Dao, Harmony and Personhood: Towards a Confucian Ethics of Technology | SpringerLink. Philosophy & Technology, 25(1), 67–86.
32 Lewis, J. E., Arista, N., Pechawis, A., & Kite, S. (2018). Making Kin with the Machines. Journal of Design and Science. https://doi.org/10.21428/bfafd97.
33 Mhlambi, S. (2020). From Rationality to Relationality: Ubuntu as an Ethical and Human Rights Framework for Artificial Intelligence Governance (No. 2020–009; Carr Center Discussion Paper Series, p. 31). Harvard Kennedy School Carr Center for Human Rights Policy. https://carrcenter.hks.harvard.edu/files/cchr/files/ccdp_2020-009_sabelo_b.pdf.
34 https://time.com/5197039/un-facebook-myanmar-rohingya-violence/.
35 Newman, J. C. (2019). Toward AI Security: Global Aspirations for a More Resilient Future (CLTC White Paper Series). Centre for Long-term Cybersecurity. https://cltc.berkeley.edu/wp-content/uploads/2019/02/CLTC_Cussins_Toward_AI_Security.pdf.
36 http://www3.weforum.org/docs/WEF_Global_Technology_Governance.pdf.
37 A mapping of its technical elements, human participation, governing rules, and how these all of these interact.
38 https://www.data.govt.nz/assets/Uploads/Public-Scrutiny-of-Automated-Decisions.pdf.

Jun-E Tan is an independent researcher based in Malaysia, currently working on the topic of AI governance in Southeast Asia. Her research interests are broadly anchored in the areas of sustainable development, human rights, and digital communication. More information on her research and projects can be found on her website, https://jun-etan.com.

October 31, 2020November 3, 2020

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by Francois Soulard

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The Covid-19 pandemic has put health, political, and economic systems under considerable strain, accelerating a phenomenon already at work in the digital continent and, more broadly, on the security front.

This has exposed a deeply fragmented multilateral stage, torn between geopolitical rivalries and nationalist reflexes while allowing for medium-intensity scientific cooperation. On the one hand, as with the previous health crises of the 2000s such as Ebola, MERS, and SARS, the coronavirus pandemic has created – on a whole new scale – a sense of urgency that has forced the adaptation and invention of innovative responses. On the other, it has provided alibis for certain actors to impose their will, strengthen their control, and manipulate opinions if needed to conquer economic markets, all in the name of efficiency to meet the demands of the healthcare spiral.

The cascading effects of the Covid crisis are not entirely new. Despite the many imperfections in the multilateral framework, the World Health Organization (WHO) has provided the basis for countries to develop crisis responses, with some adaptations to suit their local contexts. And yet, the current crisis remains marked by extreme operational vulnerability, irrespective of the degree of material development in societies.

While the initial sources of the pandemic may have been easily identified and secured, the absence of a steering function for risk modeling, effective response mechanisms, and a coordinated global action required in the face of a threat of this magnitude has landed us in the current debacle. In short, our international system stands bare and archaic, with the G20, the WHO, and other players unable to orchestrate any transnational efforts. As the current crisis has unfolded, it has exposed the flaws in our socio-economic systems and modes of action adopted to cope with the situation.

The absence of a globally coordinated response to the pandemic is a missed opportunity to move towards better models than the ones we are currently stranded with. Our current models, relying on a rigid vertical segmentation of productive activities, resulting in the concentration1 and optimization of economic costs in long delocalized chains, have proved to be less resilient to the crisis. Some cards have also been reshuffled in the realm of perceptions, geopolitical relations, technologies, and economics. One of the consequences of the pandemic has been a crude sketching of the world canvas in which we will operate in the decades to come, in which the traditional balance of power, the lack of cooperation, and the assertion of national interests will be the linchpins. New stress points arising from the pandemic and the acceleration of previous trends are likely to seal medium-term arrangements. The crisis has favored a wave of sovereign posturings and affirmations which were already underway at the global level. Big Tech corporations are taking the place of fossil-fuel producers in the stock market podium while clean power shares are up by 45 percent so far in 2020.2

However, unlike the global financial collapse of 2008, the pandemic is an external accident which originated outside the current economic and political matrix. This diagnosis is often challenged on the grounds that the circulation of the virus could have been facilitated by the no-holds-barred extraction of natural resources, unregulated globalization, experimental manipulation of living beings, or even by the authoritarian nature of the Chinese state. Besides, the emergence of every new climate or security risk3 increasingly forces us to re-evaluate existing notions of economic efficiency and pay attention to the long-term variables of resilience and adaptation.

Be that as it may, beyond the ideological sensitivities and despite the intensity of the global economic slowdown, we can see that current responses to the pandemic are not built on the identification of an endogenous fracture in global capitalism. For states and other actors engaged in international exchanges, there has been no real questioning of the engines of the economic status quo. Rather, attention has been focused on the imperative to manage the health contingency and promote recovery, possibly accompanied by certain corrective measures. The focus has also been on a certain strategic reorientation, in particular on the decoupling and relocation of sectors. The recovery plans have been criticized for reinforcing earlier standards of productivism and not taking into account, for example, the new climate commitments4 resulting from the Paris Agreement of 2016.

This initial diagnosis of the origins of the crisis is central because it has determined the forms taken by recovery strategies and their interactions with the digital sphere. We are at a stage where many – including sections of the global economic elite5 – are rushing to underline the contradictions exposed by the pandemic. And yet, there are few signs that it has led to a fundamental shift in the nature of recovery models.6 There is an intensified use of digital technologies to support post-pandemic recovery without any particular awareness of an endogenous crisis in the digital sphere. There are neither new insights in the governance of the digital nor a reorientation in decision-making, only an acceleration of previous tendencies. The computerization of the real economy is one of them.

In this respect, the digital continent, the primary focus of this essay, is perhaps one of the most fertile areas to explore in the present landscape. The shockwaves of the pandemic have brought to the forefront the ethos and physiognomy of “digitization”. This physiognomy needs to be approached carefully through a lens and a vocabulary that can accurately describe the processes at work. Instead of “digitization”, for instance, which only refers to the sub-process of data encoding in a binary format, I will evoke the process of “computerization”. The latter raises the idea of a transformation of the old technical system, constituted by the alloy between the human workforce and machines, into a new one based on the alloy between programmable automatons and the human brain. In this context, the question of cognitive registers is of primary importance. A new understanding is needed to grasp these manifestations in depth and see beyond the parameters defined by the spirit of the times. The difficulty in envisioning computerization as a phenomenon that goes beyond a mere technical disruption is a crucial part of the agenda. This is at the root of the current digital imbalance that exacerbates the impacts in terms of predation and threats, and reduces the potential for a social justice-oriented digital economy. Through negative and positive shocks, the pandemic is offering us a sort of radiography of the characteristics of the new digital economy. This new economy is not merely a new industrial sector, it is “upgrading” the current industrial economy and shaping a new matrix.

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October 30, 2020November 17, 2020

Food for All or Feeding the Data Colossus? The Future of Food in a Digital World

Food for All or Feeding the Data Colossus? The Future of Food in a Digital World

Action Group on Erosion, Technology and Concentration
(ETC Group)

The Covid-19 pandemic has accelerated the global resource grab in our food and agriculture systems. The encompassing digitalization of the core ecological and social components of these systems is the new means of making vast profits. Approaches that claim precision through efficient utilization of resources are, in fact, forms of power grab by the data colossus – the world’s largest corporations such as Google, Amazon, Microsoft, and Alibaba – from the fields and fishing grounds of farmers and fisher folk. In response to these incursions, some groups of smallholder and peasant farmers have been either struggling to benefit in the fringes of digitalization or attempting to create their own open source alternatives. Ultimately though, the principles of food sovereignty can only be protected by democratic processes that challenge the monopolistic powers of these corporations. To develop alternatives to a corporate-controlled ‘fourth industrial revolution’ and regain control over our food and agricultural futures, we need to assert peasant farmers’ sovereignty over their data, promote agro-ecology and bottom-up technologies, and build a comprehensive global system of participatory technology assessment.

Introduction

Food and agriculture has always been a key battleground for the deployment of new technologies. The sector has often acted as a vehicle to win over to industrial models of production, the hearts, minds, stomachs, and pockets of people who produce food and those who consume it – which is everyone. It is also a big business. The World Bank estimates that the food system accounts for at least a tenth of the global economy, making food a natural target for technology titans seeking new speculative investment opportunities for the development and deployment of new technologies.1

Technology has transformed the global food system several times in the recent history and big technology firms (whether in chemicals, genetics, or machinery) have been especially active in exploiting this field. Far from being politically neutral, technology is always introduced within an ideological framing and advanced by powerful players who use it as a lever to shift or retain power in the food system and, thereby, over populations. As it was for industrial chemistry pioneers in the last century, so it is today for data colonialists who smell profits in the fields and the fishing grounds.

The power vested in technology to transform the global economic system has never been greater. The exponential technological changes ushered in by the so-called fourth industrial revolution have the potential to upturn all economic sectors including food and agriculture. This essay argues that any alternative to this corporate-led technological food future will have to contain strategies to counter this tsunami and challenge the ideologies behind it. These alternatives must centre the interests and livelihoods of peasant farmers, small farmholders, and indigenous communities who feed 70 percent of the world’s population, and yet, have been perennially pushed to the margins by previous technological waves and their disruptive consequences for the food system.

The essay is structured as follows. In Section 1, we outline how mega-corporations have identified food and agriculture systems as sources of data and then proceeded to harvest this data for financial gains. Sections 2, 3, and 4 identify some of the most dangerous features of this data colossus. Finally, Section 5 proposes the strategies and components of an alternative new deal for food and agriculture based on a democratic process of technology assessment and the principles of food sovereignty.

1. The flawed food system as a ‘data problem’

While food producers traditionally consider seeds, breeds, soil, and cultural practices as the bedrock of the food system, corporate players are increasingly regarding data as the key strategic resource. A great mapping is underway, reimagining every aspect and challenge of the food system as a big data enterprise – from soil, climate, and genetic data, to logistics, trade, consumer, and health data. The streaming of big data from farm machinery, grocery shopping, or agro-biodiversity is now an increasingly valuable commodity in its own right, leading to the rapid economic ascendancy of data platforms in the agri-food industry and the ‘datafication’ of all aspects of food, agriculture, human health, environment, and other related domains.

Data surveillance, processing, and manipulation is transforming each ‘link’ across the food chain – beginning with breeding and genetic engineering strategies at one end, followed by data-mediated food logistics and commodity delivery systems in the middle, and digital consumer retail and health technologies at the other end.2 But reframing the challenges faced by the food system as a ‘data problem’ only suits the interest of investors such as asset management firms with horizontal shareholding across the food chain.

To be sure, this overarching system of control enabled by the datafication of the global food system did not happen overnight. The decades-long struggles of family farmers in the Global North to defend their ‘right to repair’3 was a subtle warning of the technological slavery that would come with the corporate takeover of data and technology on the farm. Farmer groups have cried foul on digital ‘turnkey’ agreements where the user of data-enabled tractors legally surrenders rights by the act of turning on the machine. They have locked legal horns with farm machinery giants to protect their right to repair farm machinery. In this digital Wild West, many governments and regulators have been persuaded to allow corporations to reap vast profits from e-commerce and digital trade without ever being required to pay taxes. In the post-pandemic economy, unmitigated corporate influence on the food chain, facilitated by big data surveillance, is being repackaged as the harbinger of food safety, health, and personalization benefits to end consumers, and production cost efficiencies to farmers and fisherfolk. Over time, platform companies can boost their profits by utilizing big data patterns and machine learning (often called artificial intelligence or AI) to redesign the entire food system. The result would be a food system stripped of all direct human relations with the soil, plants, animals, rivers, or the oceans, and mediated by data and data-driven business strategies.

2. Food systems in a biodigital world: Old game, new tricks and traps

Food systems contain both the complex and diverse living world of biology and the hyper-rationalized behavioral world of economics. It is at this interface that biodigital convergence – the interactive combination of digital technologies and biological systems – has emerged.4 We see this trend in every step of the food chain – the development of robotic bees to aid pollination, the co-evolution of digital and biological technologies in the agricultural application of CRISPR-Cas9 technologies,5 and synthetic biology microorganisms ‘programmed’ to secrete industrial proteins. Beyond the individual ‘apps’, a digitally-enhanced agro-ecosystem is being envisaged as a bio-digital system – a living, food-growing landscape shaped and nudged by robotic and data-driven machines.

Biodigital convergences across the food system are paving the way for new players, from sectors that are not traditionally associated with food and agriculture, to wield power over food production and consumption. This includes everything from digital technology platforms to companies manufacturing drones and hyperspectral sensors, and oil, energy, and finance majors that want to biodigitally reshape landscapes and farming practices, marketing them as climate change mitigation initiatives and reaping carbon credits to offset emissions from their fossil fuel-dependent businesses. These biodigital interventions will have profound and long-lasting impacts on the global food system, hunger, food sovereignty and farmers’ rights to seeds, and development. They will displace rural labor, undermine traditional and local knowledge systems, further marginalize farmers, and expand extreme industrial agriculture.

For agri-food giants, data strategies are not just a means to uncover and capture new efficiencies in food. These strategies form the basis for shifts in the economy toward ‘surveillance capitalism’6 as data giants amass and leverage datasets from both food producers and consumers as a new form of capital. The agricultural and food data thus collected can be profitably combined with environmental, health, security, and consumer data to deliver real-time insights with exploitable value beyond the food system. This means that the big names in food in the coming decades are most likely to be data processors. Amazon with its data trove, data-led insights, and AI capacity to understand the consumer grocery end of the food chain is now stepping into what its supporters call ‘precision agriculture’. Its web services subsidiary is partnering with major seeds and agrochemical companies as well as genomic data initiatives like the Earth Biogenome project. Similarly, Alibaba is aggressively moving into the digital food and agriculture space through its ‘ET Agricultural Brain’.7 Meanwhile, giant agribusinesses such as Bayer (now incorporating Monsanto), Yara, and John Deere are reinventing themselves as data providers, crunching data generated from farmers’ fields in strategic alliance with digital platforms.8 Corporate behemoths in poultry and livestock have also embraced big data, machine learning, and the internet of things (IoT) to make their operations more ‘efficient’, which is often code for reducing dependence on human labor while maximizing profit at every stage.

For agri-food giants, data strategies are not just a means to uncover and capture new efficiencies in food. These strategies form the basis for shifts in the economy toward ‘surveillance capitalism’ as data giants amass and leverage datasets from both food producers and consumers as a new form of capital.

The industrial agricultural system, comprising long food chains that depend on fossil fuel, leaves food availability vulnerable to energy shocks and trade disruptions. The emerging data-dependent agri-food system will find itself confined by limitations and vulnerabilities arising from data infrastructures. On-farm data, consumer food data, genomic data, among others, will constitute an ever-larger driver of the data colossus enabled by massive networks of supercomputers, servers, data centers, fiber optic cables, and 5G wireless systems. No-holds-barred mining of lithium, copper, silicon, and other rare earth minerals necessary to create the infrastructure for this colossus will increasingly place a hard physical limit on the ability of digital food systems to feed people. The possibility that deliberate cyberattacks, ill-designed algorithms, or network outages could cause food shortages in the digitally-mediated food chain is yet to be reckoned with, as is the vulnerability of our complex food system. With industrial farming and food provisions increasingly designed and directed by machine learning, the potential for unexplained (and unexplainable) points of failure in the food system is growing.

Energy and material limits on data systems will also drive interest in low-energy biological modes of computation, data transfer, and storage — such as molecular communication developed to process and carry digital information on biological and chemical molecules such as DNA or pheromones. Farmers and fisherfolk may find themselves recast as literal data farmers and synthetic molecular communication may interfere with natural ecological modes of communication and other mutually beneficial relationships between living things, such as gene flow and pollination processes.9 10

Biodigital investments are additionally flowing into biotech strategies that do not modify the food itself but, instead, either modify elements of agro-ecosystems such as soil microbes, weeds, and insects, or do not incorporate modified DNA into the final product such as ‘transient modification’, RNAi sprays, biosynthesis, and big data breeding strategies.11 By avoiding the legal definition of genetically modified organisms (GMOs), these kinds of technologies could allow the industry to sidestep regulations that have safeguarded most consumers from genetically engineered foods for the last 25 years.

3. Creating illusions of ‘choice’

Corporations attempt to ‘nudge’ or persuade consumers towards specific behaviors – for instance, into accepting GMOs – while giving them the illusion of choice. During the pandemic, online sellers enticed consumers to save time and avoid social contact by using different ‘hyper-nudging’ techniques.12 Such techniques include consumer-targeted discount e-coupons, products placed strategically at the online point of sale, and leveraging insights from a consumer’s shopping history in order to offer new products according to taste, lifestyle, and income.13 Needless to say, these hyper-nudging techniques have very little transparency and even lesser regulatory limits on the purposes of algorithmically-driven desire-modification and to what end.

The manipulation of consumer behavior can generate real-time profit opportunities in genetics or farm conditions. Technology platforms with interests across the food chain can leverage consumer insights to redesign seeds, farming patterns, and logistics in ways that maximize short-term profit at great cost to ecosystems, health, justice, and people’s rights.

4. Corporate megabytes for lunch?

The future of our food system thus stands compromised. With technology companies making inroads into the system, digital technologies are at the forefront of shaping the present and the future of food and agriculture. As the digitalization tsunami sweeps across farming communities, landlessness, land grabbing, exploitative market relations, and the lack of social protections will likely worsen. The knowledge and agency of farmers and peasant families will be pushed further into the margins as robotic agriculture moves into their lands, obliterating the role of women farmers, wiping out livelihoods, and transforming economies. The underclass of people living in economically precarious circumstances in rural and urban areas will keep rising, exacerbating income and social inequalities.

As the digitalization tsunami sweeps across farming communities, landlessness, land grabbing, exploitative market relations, and the lack of social protections will likely worsen.

The trillion-dollar companies Amazon, Apple, Microsoft, and Alphabet have already become so powerful that governments and multilateral organizations like the United Nations (UN) heed their advice on public health, education, and digital cooperation policies. These firms and their political surrogates claim that digital technologies can solve the world’s problems, ranging from diseases and aging to energy and food crises. They echo the false promise of small-scale solutions – that utilizing big data, sensors, and machines could render diverse smallholdings and fishponds more profitable. Instead of giant autonomous combine tractors rolling across enormous fields, they advocate for swarms of small robots to be deployed in smaller disaggregated plots. Catchy labels like ‘climate-smart’ digital and genomically-enhanced agriculture are promoted as consistent with demands that industrial modes of production be replaced with more democratic approaches that give local communities more control. In reality, such shifts merely entrench the power of the already-dominant megacorporations that own these technologies and thus control the infrastructure of an increasingly digitalized food system.

Hyperbolic promises of ‘technology for good’, involving public-private partnerships such as the World Economic Forum (WEF), proclaim that digital technologies can deliver higher income, better living conditions, and more equitable status for peasants and smallholders in the post-pandemic world. And some small enterprises, farmers’ groups, and civil society organizations do indeed venture into harnessing the potential of digital technologies in good faith from their position in the fringes, relying on smartphones and open operating systems as tools for digital leverage. But more often than not, the pro-poor narratives are propagated by self-styled digital saviors and the vested interests behind these technologies.

5. An alternative new deal for food and agriculture

Reversing the corporate capture of the global food system and reclaiming it for people and the planet calls for building an alternative new deal for food and agriculture. This is a task already being undertaken by some farmers’ groups and popular movements which are actively discussing alternative digital technologies, based on a set of premises different from those espoused by corporate interests. Ultimately, whether or not, how, and which technologies may be beneficial for peasant farmers, pastoralists, and fisherfolk on whose backs the global food system is built, will depend on the conditions, requisites, and sincerity in building this new deal. But at its core, it should take into account the following components:

5.1. Peasant farmers’ sovereignty over data

Data giants are already forcing a new, poorly understood reality upon food systems. There is an urgent need to interrogate and expose who controls and benefits from this evolving digital reality. Without a doubt, the digital food system is being reconfigured to benefit data processors, industrial agricultural giants, biotechnology players, commodity and grain behemoths, the global logistics machinery, and retail giants that are, in turn, gradually being swallowed by digital platform giants.

It is, therefore, more urgent than ever to talk about food sovereignty, the right of peasant farmers, peoples, and countries to define their agriculture and food policies in ways that establish direct, democratic control over how they feed themselves, and how they maintain land, water and other resources for the benefit of current and future generations. It is a vision that animates all food movements struggling for justice. In the post-pandemic world, where digital technologies are ubiquitous, peasants and smallholder movements globally will have to consider if farmers’ control over data has a place in the tenets of food sovereignty. Some argue that limited digitalization could be useful in agriculture and is compatible with food sovereignty. This especially if peasant farmers decide to digitize information and data on their practices and resources for the benefit of their communities, based on free, prior, and informed consent and full knowledge. Others question whether this new, fleeting, and seemingly fungible ‘economic commodity’ approach to data and associated disruptions have any place in a resilient food system that privileges life processes, communities, and place.

Key to this debate is the recognition and defense of the central role of farmers and fisherfolk in creating the knowledge, relationships, and harvests that nurture the majority of the population, and that are now being reduced to data without their consent. Irrespective of whether farmers consciously generate these datasets, taking back control over data is critical to determining their community’s future. These debates need to be part of a collaborative effort to reimagine and reconfigure digital relations in ways that can protect and advance the rights of peasants, smallholder farmers, women farmers, agricultural and food chain workers, cooperative markets, local breeders, and fishing communities.

Just as farmers’ movements and civil society fight for seeds and associated knowledge to remain free from proprietary rights and enclosures, publicly-generated environmental data, genetic data, weather data, and agronomic data must, at the very least, remain in the public sphere, free from enclosures or commercial exploitation. Some initiatives offer free and open source software in which algorithms and data are not proprietary, but controlled by those who create the data. These are steps in the right direction but not, in themselves, sufficient.

Just as farmers’ movements and civil society fight for seeds and associated knowledge to remain free from proprietary rights and enclosures, publicly-generated environmental data, genetic data, weather data, and agronomic data must, at the very least, remain in the public sphere, free from enclosures or commercial exploitation.

A promising example of a redefined model for generating, developing, and sharing data – digital and otherwise – in the agriculture sector is the Farm Hack initiative, a global collaborative platform for exchange of knowledge and people-centred farm tools among farmers across the world.14 The right to repair movement, of which Farm Hack is an example, is an important spoke in redefining the role of data in food systems and asserting people’s right and control over data and data-driven technologies. Data tools in production systems should be regarded as a means for peasant farmers and smallholders to better understand their own environment, consider options, and develop skills, capacities, and potentials based on their needs and self-determination. However, even in such models, we need to ask who is doing the data aggregation, through which ideological lens, and what kind of power does the aggregator acquire in relation to farmers and the community.

Farmers and communities should expose and challenge ostensibly attractive deals and free apps extended by technology companies to suck up knowledge and data to improve their algorithms and machine learning capacities. Google, for example, is distributing AI tools for crop identification to African farmers which, like its core search technology, does not make it clear that data from users – purportedly the recipients of a ‘free’ service – are being used to improve the company’s algorithmic capabilities. There is no agreement to return that value to the farmers whose crop data are being digitally pirated to improve neural nets in North America. Many agricultural technology start-ups are, with good intentions, establishing similar collaborations with communities and non-governmental organizations to generate big data that power proprietary algorithms. These collaborations are based on the premise that data is a free and worthless commodity at the extraction stage, but gains in value immeasurably once processed by algorithms developed by data colonialists.

If we are to counter such extractivist practices, the principle of free, prior, and informed consent to be sought from farmers and communities before collecting data from their fields and agricultural practices, should be inviolable. The terms ‘free’, ‘prior’, and ‘informed’, when taken seriously, would mean that the real costs and implications of engaging in data relations are transparently and fairly spelt out before farmers give their consent.

5.2. Agroecology and the fight for ‘wide tech’

Socially just forms of ecological food production that build on existing practices by smallholders and peasant farmers, often termed agroecology, are practiced by hundreds of millions of farmers who feed the majority of the world’s population.15 16 These practices are developed by communities across generations through shared and collaborative knowledge systems that incorporate local, traditional, and indigenous knowledge and practices, in addition to being informed by institutional knowledge. While the pandemic has provided an opportunity for digital technologies to make significant inroads into our food systems, agroecological approaches, particularly those based on the principles of food sovereignty, are also growing in popularity and can provide a counterweight. However, bottom-up agroecological technologies and innovation including open source platforms – collectively referred to as ‘wide tech’ – need to safeguard against potential corporate appropriation that can undermine local innovators and prey on local knowledge and resources.

The fight for agroecology should be undertaken on all fronts, local to global. The UN’s Food and Agriculture Organization (FAO) is an important and legitimate arena for such a fight. Over the past few years, civil society has made much headway in advancing the agroecology agenda at this forum. However, the misappropriation of the concept of agroecology is also underway, with industrial agriculture interests advancing their own corporate interpretation and lobbying for an expansion of agroecology deliberations to include ‘other innovative practices’ which are barely defined. It is only a matter of time before digital farming lobbyists start expounding the gospel of ‘cyber-ecological’ or ‘robo-organic’ farming. While peoples’ movements have successfully pushed for a recognition of agroecology as an organizing framework for food systems, the corporate push for digital agriculture is now taking centerstage. The proposals to create a Digital Council for Food and Agriculture at the FAO and convening of a Food System Summit by the UN in 2021 are driven by agribusiness proponents who have elevated digital solutions as an organizing theme with agroecology as an add-on.

5.3. Cutting the bots out: Creating shorter food supply chains

Against this backdrop of increasing corporate concentration, globalization, and digitalization of the food system, has emerged a countervailing trend among food producers and consumers. Since the pandemic, many smallholder food producers in the Global South have reconnected with local consumers in the midst of disruptions in export markets and commercial supply chains during lockdowns.17 Some surveys suggest that up to a third of consumers in the United Kingdom are buying more locally-produced foods.18 Policy responses imposing social distancing during the pandemic have ironically fostered mutually supportive relationships between producers and consumers in many countries. Communities have witnessed the emergence of shorter supply chains through direct producer-consumer links, community-supported agriculture, and even systems of bartering. Disruption in jobs and livelihoods have also engendered social innovations and entrepreneurship across communities in various contexts, especially among women and youth. The flourishing mutual aid and stronger local networks often have a digital character, enabled largely by existing communication technologies and rudimentary, often non-proprietary, software for social collaboration and micropayment.

The counter-trend towards short supply chains and less industrialized systems could continue and even increase in the coming years, strengthened by demands for greater nutrition, diversity, a healthier environment, and mutual support among peoples. However, given the huge amounts of capital being invested in the digitalized industrial food system, and the disregard for its ecological and social impacts, there is a real risk that an increasing proportion of the global food system will become locked into industrial models.

5.4. Interrogating techno fixes: Participatory technology assessment

Technology assessment (TA) is fundamental to the debate on fair, just, and ecologically sustainable use of digital technologies that serve the common good. Participatory TA is a process that enables people to evaluate new and emerging technologies and allows them to examine the interests and powers behind the introduction of new technologies, the ways in which they are applied, and their potential impacts on the environment and communities. The active involvement of civil society, indigenous peoples, local communities, farmers, fisherfolk, popular and social movements is fundamental in participatory TA, which is aimed at democratic control over technologies, grounded in the precautionary principle and the rights of communities to free, prior, and informed consent.

Respecting collective decisions to adopt or reject a technology or putting conditions on its development and application is a key element of TA. The process could focus on scientific research linked to the development of future technologies that may directly impact communities, as well as existing technologies that were imposed without such consent. It could foster food sovereignty and even conflict reduction in communities19 through peasant agroecological approaches. It could provide a powerful platform for communities to examine the relevance of digital technologies in the food system, explore the desirability of non-digital options, and consider a variety of options and innovations beyond the technological sphere.

6. End reflections

Innovation and technological developments can take many paths, each involving intrinsically political choices. Precaution requires an understanding of the real nature of uncertainty by avoiding the scientific error of mistakenly assuming safety or harm. Reclaiming our future in a way that is guided by precaution and democratic accountability, rather than abandoning it to the data colossus, is not only possible, but also a moral imperative.

Notes

1 https://blogs.worldbank.org/voices/do-costs-global-food-system-outweigh-its-monetary-value.
2 Pat Mooney, “Blocking the Chain – Industrial Food Chain Concentration, Big Data Platforms and Food Sovereignty Solutions” ETC Group, GLOCON, Inkota and Rosa Luxembourg Stiftung, 2018. https://www.etcgroup.org/content/blocking-chain.
3 Matchar, Emily (2016). “The Fight for the Right to Repair”, Smithsonian Magazine, 13 July 2016. https://www.smithsonianmag.com/innovation/fight-right-repair-180959764/.
4 Policy Horizons Canada (2020). “Exploring Biodigital Convergence”, 11 February 2020. https://horizons.gc.ca/en/2020/02/11/exploring-biodigital-convergence/.
5 Zhu, H. et al (2020). “Applications of CRISPR-Cas in agriculture and plant biotechnology. Nat Rev Mol Cell Biol (2020). https://doi.org/10.1038/s41580-020-00288-9.
6 Sam Bidle, “A Fundamentally Illegitimate Choice: Shoshana Zuboff in the Age of Surveillance Capitalism”, The Intercept, February 2020. https://theintercept.com/2019/02/02/shoshana-zuboff-age-of-surveillance-capitalism/.
7 Alibaba Cloud (2018). “Alibaba Cloud Launches ET Agriculture Brains at the Shanghai Computing Conference”, 7 June 2018. https://www.alibabacloud.com/press-room/alibaba-cloud-launches-et-agricultural-brain-at-the-shanghai-computing.
8 ETC Group, “Plate Tech-Tonics”, November 2019. https://etcgroup.org/sites/www.etcgroup.org/files/files/etc_platetechtonics_a4_nov2019_web.pdf.
9 Cotter, J., Kawall, K., Then C. (2020). “New genetic engineering technologies”. Report of the results from the RAGES project 2016-2019. www.testbiotech.org/projekt_rages.
10 Lundgren, J. G., & Duan, J. J. (2013). “RNAi-based Insecticidal Crops: Potential Effects on Nontarget Species. Bioscience, 63(8), 657-665.
11 Slade, AJ, Fuerstenberg, SI, Loeffler, D, Steine, MN, Facciotti, D. (Jan 2005). “A reverse genetic, nontransgenic approach to wheat crop improvement by TILLING”. Nat Biotechnol. 23 (1): 75–81.
12 Nudge is a particular form of choice architecture that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives. In Karen Yeung’s “‘Hypernudge’: Big Data as a Mode of Regulation by Design, Information, Communication & Society”, 20:1, 118-136, 2017. https://doi.org/10.1080/1369118X.2016.1186713.
13 “The 9 best sites for online grocery shop in 2020”. Lifewire. https://www.lifewire.com/groceries-online-3482646.
14 Farmhack website: https://farmhack.org/tools.
15 Didarali, Z., & Gambiza, J. (2019). “Permaculture: Challenges and Benefits in Improving Rural Livelihoods in South Africa and Zimbabwe”. Sustainability, 11(8), 2219.
16 Hirschfeld, S., & Van Acker, R. (2019). “Permaculture Farmers Consistently Cultivate Perennials, Crop Diversity, Landscape Heterogeneity and Nature Conservation”. Renewable Agriculture and Food Systems, 1-10.
17 IIED, “How COVID-19 is impacting and changing East Africa’s agri-food systems”, August 2020. https://www.iied.org/how-covid-19-impacting-changing-east-africas-agri-food-systems.
18 Forbes, COVID-19 Has Given Consumers Five New Reasons To Eat Local, July 2020. https://www.forbes.com/sites/daphneewingchow/2020/07/30/covid-19-has-given-consumers-five-new-reasons-to-eat-local/#6171d45c3ccc.
19 McAllister, G., & Wright, J. (2019). “Agroecology as a Practice-Based Tool for Peacebuilding in Fragile Environments? Three Stories from Rural Zimbabwe”. Sustainability, 11(3), 790.

ETC Group is a small, independent civil society organization that monitors the impact of emerging technologies and corporate strategies on biodiversity, agriculture, and human rights. It has offices in Quebec in Canada, Davao in the Philippines, Mexico City and the UK.

October 29, 2020April 23, 2021

A Digital New Deal Against Corporate Hijack of the Post-Covid 19 Future

A Digital New Deal Against Corporate Hijack of the Post-Covid 19 Future

Gianluca Iazzolino, Marion Ouma & Laura Mann

Our essay focuses on the political context in which the consolidation of the dominant digital paradigm takes place. It is structured into three parts: we first describe the role of technology companies in restructuring the global economy and creating the economic and social vulnerabilities that have been exposed by the current global health crisis. We then identify some trends that are likely to be exacerbated by the pandemic, specifically the growing public reliance on tech firms for basic services, the influence of tech firms on public debates, and the attempts by tech firms to capture civil society organizations and social movements through their philanthrocapitalism. We eventually sketch a policy framework to help address these dangers and to avoid a corporate hijack of the post-Covid 19 future, arguing that state regulatory and fiscal capacities must be strengthened and that independent research must be funded by the tax revenues extracted from tech giants. Civil society organizations could contribute by forming transnational alliances to keep tech giants in check and help engage citizens in public debate.

Introduction

It is hard to fathom what kind of social and economic future lies on the other side of Covid-19. In the early days of the pandemic, some were hopeful that the crisis might usher in a new economic order. Others cautioned that the long-term economic and social impacts would be grave. One group, however, seems to be having an unambiguously ‘good crisis’. Amidst dismal GDP figures, mass layoffs, hiring freezes, and bankruptcies, the world’s top seven tech giants – Amazon, Microsoft, Apple, Tencent, Facebook, Alphabet (Google), and PayPal – added an overall market capitalization of $1.2 trillion during the first six months of 2020. Amazon alone, despite spending $4 billion on logistical upgrading, saw its value climb by $401.1 billion, boosted by the expansion in online shopping and cloud computing. The second biggest winner, Microsoft, has likewise benefited from the mass shift of work from office to home, and the growing reliance of workers and households on its cloud services.1

In addition to hefty market capitalizations, these tech Leviathans have also used the Covid moment to strengthen their political capital, positioning themselves as reliable actors in the face of government shortcomings. In several US states, health departments are leveraging the data power of Google, Facebook, and Apple for contact tracing. Amazon Web Services (AWS) is helping support CommCare, a mobile data collection platform developed by Dimagi, a for-profit social enterprise, which initially sought to provide e-health solutions in Africa and Asia, but has since branched out to the US and Ireland. And Facebook CEO Mark Zuckerberg published2 an op-ed in The Washington Post to burnish his company’s public utility credentials.

This moment of potential consolidation risks unsettling the precarious balance between tech giants on the one hand, and the public sector, labor organizations, independent research, and civil society, on the other. Yet, the current crisis is not a watershed; for these tendencies have been long in the making: the platformization of public services, the creation of corporate-led economic ecosystems, the restructuring of production, and the datafication of workers and customers. While most governments were caught by surprise, tech giants were ready, and are now poaching smaller firms on the verge of collapse – a trend that is likely to accelerate after the pandemic. The world that lies on the other side may, therefore, be a world in which a handful of large companies can move capital, produce knowledge, and shape the political and public conversation in their favor.

While most governments were caught by surprise by the current crisis, tech giants were ready, and are now poaching smaller firms on the verge of collapse – a trend that is likely to accelerate after the pandemic.

This series has asked contributors to imagine a ‘Digital New Deal’ akin to Roosevelt’s Keynesian revolution. Our contribution draws attention to the varied political context of this paradigm contestation and the political strategies deployed by tech firms to thwart wholesale paradigm shifts. Section 1 describes the role of tech companies in restructuring the global economy and creating the economic and social vulnerabilities that have been exposed by the current global health crisis. Section 2 identifies some trends that are likely to be exacerbated by the pandemic, focusing on growing public reliance on tech firms for basic services, the growing influence of tech firms on public debates, and attempts by tech firms to capture civil society organizations and social movements through their philanthrocapitalism. The final section sketches a policy framework to help address these dangers and to avoid a corporate hijack of the post-Covid 19 future. In particular, it argues that state regulatory and fiscal capacities must be strengthened in order to tackle the opacity of their business operations and to extract tax revenue to fund more independent research. In pursuit of these policies, activists can help by forming transnational alliances to keep tech giants in check and help engage citizens in public debate.

1. An overview of the dominant digital paradigm

In explaining the role of intellectuals in driving long-term policy change, Milton Friedman3 once remarked, “Only a crisis – actual or perceived – produces real change. When that crisis occurs, the actions that are taken depend on the ideas that are lying around. That, I believe, is our basic function: to develop alternatives to existing policies, to keep them alive and available until the politically impossible becomes the politically inevitable.”

In the spring of 2020, many hoped that the Covid-19 crisis might precipitate a rupture in the fortress of free-market economics. Even the right-leaning Economist magazine asked if a new paradigm was at the gates.4 Pressure had been building for some time. Piketty’s book, Capital in the Twenty-First Century5 had laid bare growing economic inequalities that have been accelerating in high-income countries since the 1970s, when free-market policies were embraced as the dominant growth model.

After 1975, technology firms were at the forefront of this growing consolidation of wealth. The shareholder value business revolution put pressure on managers to lower their production costs,6 and so they introduced productivity-enhancing technology to rationalize production, increase worker surveillance, and restructure production beyond the boundaries of the firm. This restructuring gradually eroded the skill intensity of production and allowed managers to restructure production and redistribute tasks to cheaper workforces.7 In many cases, this unbundling of production resulted in offshoring, allowing firms and workforces in low- and middle-income countries to gain footholds in global production networks.8 Yet, for those services that required proximity to markets, employment was retained onshore, but with skills and wages restructured downward through digitization and platformization.

During the pandemic, the social vulnerabilities of this restructuring have been laid bare. In cities like London, where workers are concentrated in the service sector, the ‘lockdown’ and removal of high earners from city centers devastated the local low-skilled labor market. Meanwhile, other low-skilled ‘essential’ workers in food and healthcare provision were forced to work through the pandemic, exposing themselves and their families to higher rates of infection. In low-income countries like Kenya, lockdown measures devastated the livelihoods of urban residents working in the informal sector. For close to 80 percent of the world’s working population dependent on day-to-day earnings, staying at home is hardly an option, given that government assistance would be insufficient to cushion their livelihoods. While some may have hoped that the pandemic would reset the economic paradigm by revealing its structural vulnerabilities, politicians have, instead, turned to tech firms to help keep the existing economic paradigm afloat.

By and large, neo-classical economists have understood the role of tech companies as generating efficiency and productivity gains for individuals and markets as a whole.9 By lowering transaction costs, tech firms promise to lower entry barriers and forge more inclusive markets and financial systems. Furthermore, by facilitating the compulsion of market actors to make ‘better’ decisions through nudging and coded incentives, behavioral economists hope that digital technology will help enhance worker productivity and improve transparency in the overall investment climate. However, as many political economists have highlighted, these platforms have also reshaped the knowledge economy and altered the careful balance between public and private governance.10

First, these platforms aim to transfer knowledge requirements away from workers and onto the platforms themselves, thereby altering both the relative bargaining power of capital and labor within economies as well as the technological advantages of high-income economies relative to others within global production networks. Second, by virtue of their network effects and ability to facilitate “interoperability”– the ability of systems to share data and interact – these firms are slowly embedding themselves at the heart of both market structures and interfaces between public and private service provision. The legal scholar Frank Pasquale has developed the concept of “functional sovereignty”11 to describe the power that a private firm acquires when it rises above all other market participants to become the force shaping and organizing the market as a whole. Over the past decade, tech behemoths like Google and Amazon have accrued this power. They have nipped potential competitors in the bud and gained leverage vis-à-vis the state to become de facto alternative regulators, able to police disputes and interactions among the other market participants.

The legal scholar Frank Pasquale has developed the concept of “functional sovereignty” to describe the power that a private firm acquires when it rises above all other market participants to become the force shaping and organizing the market as a whole. Over the past decade, tech behemoths like Google and Amazon have accrued this power.

A growing community of intellectuals, activists, and politicians have pressed for greater scrutiny of these firms. In response, policymakers have begun to introduce digital taxes, basic income grants, and new kinds of antitrust regulation.12 Outside of the US, policymakers are additionally concerned by the dominance of US-based firms in new areas of economic development. For example, African trade negotiators have strongly pushed back against attempts by US trade negotiators to introduce binding regulation covering e-commerce into World Trade Organization (WTO) rules13. Likewise, European economies have sought to develop a common digital market in an effort to create opportunities for European firms to compete. However, the relative power of policymakers varies enormously across the world, and African countries, by virtue of their legacies of structural adjustment and continued dependence on aid and foreign direct investment, enjoy much narrower policy space than their European counterparts. These differences in the policy environment will no doubt shape the likelihood of countervailing policy responses in the form of Digital New Deals. In the next section, we examine how technology firms have tried to reshape the policy environment in both high- and low-middle income countries, positioning themselves at the center of government and donor-led attempts to restructure the economy and public services during the pandemic.

2. Fault lines of the dominant digital paradigm

As we have highlighted in the previous section, technology corporations are currently leveraging their logistics power to uphold the existing economic paradigm. Within the specific context of the Global South, the functional sovereignty of tech giants is further enhanced by the asymmetrical relationship between donors and governments. This context narrows the space for alternative models to emerge by allowing these firms to deepen public reliance on digital platforms for governmentality 14, to reshape the research agenda of domestic institutions and tech communities, and to alter the strategic focus of civil society organizations and social movements.

State over-reliance on corporate services

The myth of a dynamic private sector vis-à-vis the sluggish state continues to garner appeal despite concerted attempts by scholars such as Mariana Mazzucato to debunk it.15 In fact, the current pandemic has injected fresh lifeblood into its veins. Before 2020, public anger over austerity and the outsourcing of public services was gaining momentum, but the public health emergency triggered by Covid-19 has largely neutralized this conversation. The current pandemic provides a sort of Rorschach test for advocates of private sector efficiency, on the one hand, and those who blame austerity for undermining state capacity, on the other. Both sides see in this a confirmation of their belief system. Yet, free-market proponents appear to be prevailing, as several governments have awarded test-and-trace contracts to corporate giants. For instance, the UK government has signed deals with, among others, Google, AWS, and the controversial data analytics company Palantir to store NHS (National Health Service) patient data on their clouds.16 Such deals have sparked fears among data justice activists who worry that such data may be used for totally different purposes. This fear is particularly heightened in cases when firms such as AWS and Palantir remain active in sensitive fields such as border and immigration services. As Busemeyer and Thelen17 have theorized through the concept of ‘institutional source of business power’, the over-reliance of the public sector on “these arrangements foster(s) asymmetric dependencies of the state on the continued contribution of business actors in ways that, over time, tilt the public-private balance increasingly in favor of business interests”.

In low-income countries, the legacies of structural adjustment and aid dependence have further strengthened the dependence of the state on private, mostly foreign, firms. As Thandika Mkandawire18 has argued, aid dependence can make governments and civil society more accountable to donors than to their own citizens. Structural adjustment also results in the outsourcing of public services to non-governmental organizations and private actors. In recent years, international organizations like the World Bank and corporate-philanthropic actors like the Gates Foundation have argued that digital technologies can help bring about greater efficiency and accountability within social service provision, and have framed private companies as the repositories of sufficient technical and managerial capabilities to deliver donor-led programs more cheaply, effectively, and transparently.

For instance, in rural Kenya, over the past years, a whole host of agricultural tech firms has emerged to fill the void left by the retreat of public extension services to smallholder farmers, offering private services ranging from advice to credit to market access. One is Safaricom, a mobile network operator, which has been able to capture a large share of the market for financial and data services through its control over M-Pesa, its flagship mobile money platform. Its management has pursued a shrewd strategy to consolidate control over the market by exploiting regulatory loopholes and forging a privileged alliance with the country’s elite across the political spectrum.19 In the words of a Safaricom executive, its digital platform for farmers, Digifarm, and its network of agents, the Digifarm Village advisors, represent ‘an extension service that people can actually see’. Yet, this network also allows it to collect valuable and strategic agricultural knowledge, and demographic and value chain data for the Kenyan state and private companies. In social policy too, a growing number of banks and mobile network operators have positioned themselves as conduits for the delivery of social grants to citizens across Sub-Saharan Africa. The logic underlying these arrangements is steeped not only in ideas of efficiency and accountability but also in the financial inclusion agenda. As scholars working on financialization have warned,20 this convergence of social policy and financialization increases the vulnerability of public finance to the volatility of financial markets.

Shaping the research agenda and the public conversation

The awarding of contracts for test-and-tracing to tech firms represents not only a partial abdication of state responsibilities but also a further expansion of corporate players into the production of social knowledge. By hoarding large and diverse digital data, tech giants will no doubt play a critical role in the organization of scientific evidence.21 Tech giants have been particularly proactive in reshaping the research agenda and public conversation about how to regulate them. They have exerted influence through a myriad of ways. For example, large tech firms can soften or deflect criticism that may influence the attitudes of the general public, and eventually, the regulators. Particularly telling is the case of the Open Markets Foundation (OMF), a think tank at the forefront of the regulatory battle with large tech conglomerates. In 2017, it came into conflict with its then parent organization, New American Foundation, after it took a strong stance in favor of fining Google and breaking up Facebook and Amazon. The episode is recounted in an influential paper by Lina Khan, one of the most prominent OMF members.22

Such companies also use selective access to their data as a means to influence research agendas. For example, the ride-hailing firm Uber granted access to several high-profile economists including Steven Levitt and Peter Cohen, who collaborated with the company on a series of papers that depicted the company in a favorable light.23 African countries are even more vulnerable to these attempts by technology firms to shape the public conversation in their favor, due to the impact that structural adjustment had on research and higher education institutions.24 Recent initiatives such as Digital Earth Africa (DE Africa) illustrate the influence of cloud service providers in extracting and organizing scientific evidence through datafication. Supported by AWS, the platform uses Earth observation data from space agencies and the Open Data Cube technology to share insights on environmental changes and transformations of human settlements with policymakers. This initiative has the potential to contribute to policymaking and research. Nevertheless, we should be cautious about the long-term consequences of a private firm storing, analyzing, and commercializing Earth Observation data. This privatization of knowledge risks reinforcing AWS functional sovereignty vis-à-vis other sources of knowledge and the asymmetric dependency of local and international research institutions on the platform’s data power. Eventually, this company may acquire a monopoly of knowledge.

The corporate capture of civil society

The growing philanthropic engagement of tech giants adds a new layer to the so-called ‘NGO-ization of the civil society’,25 through funding and the provision of technological capabilities. Behemoths like AWS and Google are offering support to non-profit organizations in order to create a favorable ‘ecosystem’ for their business models. For example, Amazon’s Sustainability Data Initiative (ASDI) claims “to accelerate sustainability research and innovation by minimizing the cost and time required to acquire and analyze large sustainability datasets.”26 Likewise, Google has offered direct financial support to NGOs and community organizations during the pandemic, in addition to the package of services specifically designed for non-profit organizations through its Google for Nonprofits initiative, ranging from support to enhance visibility to data analytics tools. The writer Arundhati Roy27 points out that the NGO boom in countries like India (and Kenya) in the 1980s and 1990s coincided with the opening of the country to the market economy. According to her, this proliferation of NGOs led to a professionalization of resistance, depoliticizing social movements and locking them up into partnerships with market actors. In a recent article, the sociologist Ashok Kumbamu28 discusses how philanthropic giants such as the Rockefeller Foundation, the Ford Foundation, and the Gates Foundation are deploying dispossessing strategies to establish what he calls the “philanthropic-corporate-state complex”. His primary focus is on agricultural producers and their genetic varieties, but his analysis is also relevant to the field of digital humanitarianism and civil society where the philanthropic-corporate-state complex may become “an agency for the spread of neoliberalism in a ‘humane’ form across the globe”. This dependency of NGOs and humanitarian organizations on the technical and financial support of corporate players might inhibit criticism against them.

3. Fixing the fault lines

Addressing these fault lines as the world reels from the worst pandemic in a century presents additional challenges. With resources and efforts devoted to checking the spread of the virus and reversing its economic impacts, most states, research institutions, and civil society organizations are hesitant to scrutinize their relationship with corporate partners. And yet, this moment of reckoning is long overdue and has never been more urgent as the pandemic looks set to crystallize the dominance of a few tech giants.

The recipe for a Digital New Deal must not aim at a return to the pre-Covid-19 era, but fix the socio-economic rifts that have been laid bare and widened by the pandemic.

The pillars of the original Keynesian New Deal were the so-called three ‘Rs’: Relief for the unemployed and the poor; Recovery of the American economy; and Reform of the existing regulatory framework to avoid a repetition of the crisis. This time, however, the context is different: the challenge is not one of recovering an overheated domestic economy and reinstating it to its pre-crisis state, but one of fundamentally addressing the new international context of production. The recipe for a Digital New Deal must not aim at a return to the pre-Covid-19 era, but fix the socio-economic rifts that have been laid bare and widened by the pandemic. We suggest three critical steps to achieve this goal.

Strengthening the regulatory capacity of the state

Over the past years, big tech firms have formally become more accommodating to the idea of regulation. In reality, they have sought to water down any attempts to tackle their market power, holding on to the view that too-strict rules might curtail individual freedom, stifle innovation, and inhibit the benefits of digitization. As Big Tech firms gather more and more data, they must become transparent about their data points and their purpose. And yet, as these companies move into areas previously controlled by the state, it will become harder to enforce such accountability.

To address this power asymmetry, new regulatory frameworks will need to tighten the privacy rules of already vulnerable individuals, particularly as public health has been used to justify a rollback of existing legislation. As noted by Privacy international,29 regulators must track measures adopted during the pandemic including high levels of surveillance, data exploitation, and misinformation. Big Tech companies are likely to resist these demands when they see them as posing an existential threat to their business models. On the other hand, supranational entities might leverage access to the markets of their members to force tech firms to comply with such regulations.

A possible blueprint of this approach may be the draft of the EU Digital Services Act regulation – currently under discussion – which proposes that large tech companies like Amazon and Google “shall not use data collected on the platform…for [their] own commercial activities…unless they [make it] accessible to business users active in the same commercial activities”. The proposed regulation aims to tackle functional sovereignty by designating and targeting gatekeepers, that “shall not use data received from business users for advertising services for any other purpose other than advertising services”.30 If approved by the EU Parliament, this regulation would force digital platforms acting as gatekeepers in the single market to share the customer data they collect with smaller rivals and to stop giving preference to their services. Moreover, it will make tech giants liable for the products and services they market or embed in their platforms.

Taxing Big Tech to fund public research

Over the past few decades, education and research organizations have been starved of public funding, and become increasingly reliant on private companies for access to funding and data. We suggest an increase in public research funding, financed by a tax on tech firms, to counteract this reliance.

The idea of a digital tax is, of course, not new. In 2012, a series of tax scandals involving Apple, Google, and Amazon forced G20 leaders to launch the Base Erosion and Profit Shifting Project (BEPS), which was eventually extended to low- and middle-income countries.31 Nevertheless, BEPS has proven to be somewhat of a fig leaf; its financial reports are not publicly available and, therefore, not subject to the scrutiny of independent organizations. Moreover, the provision is toothless against ‘corporate regime shopping’, through which tech giants strategically structure their operations and shell companies so as to benefit from the most friendly and low-tax jurisdictions. More recently, supranational bodies such as the EU and national governments have taken a more aggressive stance. Since 2018, nine Asian countries, including India and South Korea, as well as Latin American countries like Mexico and Chile have been in discussions on how to tax revenues, rather than profits, of tech companies.32 In 2019, for instance, France had approved a 3 percent tax on revenues generated in its territory by digital corporations.33

The Independent Commission for the Reform of International Corporate Taxation (ICRICT), a think tank that includes among its members economists Jayati Ghosh, Thomas Piketty, and Joseph Stieglitz and the lawyer Irene Ovonji-Odida, suggests a BEPS 2.0, which will address regime shopping, the geographic allocation of global profits and associated taxes according to the business of the tech giants in each country, and the introduction of a 20-25 percent global minimum effective corporate tax rate on all profits earned by multinationals.34 These levies on services provided on national territories, and separate from corporate income taxes, may be used by national governments or supranational entities to increase public spending on research, improve publicly-owned data infrastructures, and minimize the reliance on corporate support.

Creating space for new forms of action

Beyond governments, activists must play a role in keeping tech giants in check and engaging with the public. We suggest that organizations such as consumer pressure groups and tech-savvy civil society organizations need to form a transnational alliance to help grassroots movements gain visibility.

Vigilant civil society organizations and advocates have a responsibility to ensure that regulators do not roll back regulations that were in place before the pandemic, and that the current emergency measures do not become permanent. Civil society organizations already participating in digital spaces must reach out to new partners including social movements involved in public services to help rethink their strategies, languages, and ways of engaging with the general public and policymakers. Meaningful collaboration requires the inclusion of consumer associations which can exert commercial pressure on digital platforms, and social movements which have a better grasp of grassroots’ calls for social change. For example, citizen-led organizations can help policymakers make a stronger case for BEPS and put pressure on corporations to make their financial and tax reports public. Not-for-profit organizations also have a critical role to play in backing up policymakers by offering feedback on and flagging off loopholes in draft regulations. This was the case in the above mentioned EU Digital Services Act, which was subjected to open consultation throughout the development process.

4. End reflections

The current pandemic is throwing into sharp relief and exacerbating structural inequalities that are steeped in past political choices. The risk is that the players that have benefited most from these choices, and are consolidating their dominance in the present, will eventually hijack the post-Covid 19 future. Avoiding a corporate capture of this moment of transformation requires a rethinking of the public-private relationship on the one hand, and the state-citizen relationship on the other.

By being more responsive to the needs of their citizens, governments can mend the fractures and faults related to digital tech and those brought about by Covid-19. Success will include shifting digitech power from extractivism to a place where this power is used for societal good.

Notes

1 Financial Times (2020a) Prospering in the pandemic: the top 100 companies. 19 June.
2 The Washington Post (2020) Mark Zuckerberg: How data can aid the fight against covid-19. 20 April. https://www.washingtonpost.com/opinions/2020/04/20/how-data-can-aid-fight-against-covid-19/.
3 Friedman, M. (1962/2002) Capitalism and Freedom Chicago: University of Chicago Press.
4 The Economist (2020) “The Covid-19 Pandemic is Forcing a Rethink in Macroeconomics” The Economist, July 25th 2020. Available electronically at: https://www.economist.com/briefing/2020/07/25/the-covid-19-pandemic-is-forcing-a-rethink-in-macroeconomics.
5 Piketty, T. (2013) Capital in the Twenty-First Century. Cambridge, MA: Harvard University Press.
6 Davis, G. F. (2009) Managed by the Markets: How Finance Re-shaped America. Oxford, UK: Oxford University Press.
7 Autor, D. H., Levy, F. and R.J. Murnane (2003) “The Skill Content of Recent Technological Change: An Empirical Exploration” The Quarterly Journal of Economics, 118(4): 1279-1333.
8 Kleibert, J. M. and L. Mann (2020) “Capturing Value amidst Constant Global Restructuring? Information-Technology-Enabled Services in India, the Philippines and Kenya” The European Journal of Development Research, 1-23.
9 Mann, L. and G. Iazzolino (2019) “See, Nudge, Control and Profit: Digital Platforms as Pervasive Epistemic Infrastructures” Working Paper, IT for Change.
10 Mann, L. and G. Iazzolino (2019) “See, Nudge, Control and Profit: Digital Platforms as Pervasive Epistemic Infrastructures” Working Paper, IT for Change; Langley, P. and A. Leyshon (2017) “Platform Capitalism: the Intermediation and Capitalisation of Digital Economic Circulation” Finance and Society 3(1), 11-31; Gurumurthy, A., Chami, N., Bharthur, D. and P.J. Singh (2019) “Tackling Online Inequality: Making Digital Platforms Work for Inclusive Development” IT For Change, Final Technical Report; Srnicek, N. (2017) Platform Capitalism. London: John Wiley & Sons; Zuboff, S. (2019) The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. London: Profile Books.
11 Pasquale, F. (2018) From territorial to functional sovereignty: the case of Amazon. Open Democracy. January 5th. https://www.opendemocracy.net/en/digitaliberties/from-territorial-to-functional-sovereignty-case-of-amazon/.
12 Khan, L. M. (2018) “The Ideological Roots of America’s Market Power Problem” The Yale Law Journal, June 4^th 2018.
13 Naidu, V. (2019) “Knowledge Production in International Trade Negotiations is a High Stakes Game” Africa at LSE Blogpost. June 14^th 2019. Available electronically at: https://blogs.lse.ac.uk/africaatlse/2019/06/14/knowledge-production-international-trade-digital/.
James, D. (2020) “Digital Trade Rules: a Disastrous New Constitution for the Global Economy, by and for Big Tech” Rosa Luxemburg Stiftung. Available electronically at: https://www.rosalux.eu/en/article/1742.digital-trade-rules.html.
14 The concept of governmentality was developed by the French philosopher Michel Foucault to indicate a set of practices and rationalities to govern subjects.
15 Mazzucato, M. (2013) The Entrepreneurial State: Debunking Public vs Private Sector Myths London: Anthem Press.
16 Williams, O. (2020) Revealed: Palantir secures £1m contract extension for NHS data store work. New Statesman. July 15. https://tech.newstatesman.com/coronavirus/palantir-nhs-datastore-contract-extension.
17 Busemeyer, M. R. and Thelen, K. (2020) ‘Institutional Sources of Business Power’, World Politics, 72(3), pp. 448–480.
18 Mkandawire, T. (1999) “Crisis Management and the Making of’ Choiceless Democracies’ in Africa” in Joseph, R. (Ed) The State, Conflict and Democracy in Africa. Boulder: Lynne Rienner; Mkandawire, T. (2010) “Aid, Accountability, and Democracy in Africa” Social Research: An International Quarterly 77(4): 1149-1182.
19 Tyce, M. (2020) ‘Beyond the neoliberal-statist divide on the drivers of innovation: A political settlements reading of Kenya’s M-Pesa success story’, World Development. 125.
20 Karwowski, E. (2019) ‘Towards (de-)financialisation: The role of the state’, Cambridge Journal of Economics, 43(4), pp. 1001–1027. doi: 10.1093/cje/bez023.
21 Mann, L. and G. Iazzolino (2019) “See, Nudge, Control and Profit: Digital Platforms as Pervasive Epistemic Infrastructures” Working Paper, IT for Change.
22 Vogel, K.P. (2017) Google Critic Ousted From Think Tank Funded by the Tech Giant. New York Times. August, 30. https://www.nytimes.com/2017/08/30/us/politics/eric-schmidt-google-new-america.html.
23 Cohen, P., Hahn, R., Hall, J., Levitt, S. and R. Metcalfe (2016) ‘Using big data to estimate consumer surplus: The case of Uber’ NBER Working paper No. 22627. Available electronically at: https://www.nber.org/papers/w22627.pdf.
24 Mamdani, M. (2007) Scholars in the Marketplace. The Dilemmas of Neo-Liberal Reform at Makerere University, 1989-2005. Dakar, Senegal: CODESRIA; Mkandawire, T. (2014) “The Spread of Economic Doctrines and Policymaking in Postcolonial Africa” African Studies Review, 171-198; Obamba, M. O. (2013) “Uncommon Knowledge: World Bank Policy and the Unmaking of the Knowledge Economy in Africa” Higher Education Policy, 26(1): 83-108.
25 Lang, S. (2013). NGOs, Civil Society, and the Public Sphere. Cambridge: Cambridge University Press; Choudry, A. and Kapoor, D. (2013) NGOization: Complicity, Contradictions and Prospects London and New York: Zed Books.
26 https://sustainability.aboutamazon.com/environment/the-cloud/asdi.
27 Roy, A. (2014) The NGO-ization of resistance. Pambazuka. September 23. https://www.pambazuka.org/governance/ngo-ization-resistance.
28 Ashok Kumbamu (2020) The philanthropic-corporate-state complex: imperial strategies of dispossession from the ‘Green Revolution’ to the ‘Gene Revolution’, Globalizations, DOI: 10.1080/14747731.2020.1727132.
29 Privacy International (2020) Telecommunication data and COVID-19. https://privacyinternational.org/examples/telecommunications-data-and-covid-19.
30 Espinoza, J. (2020) Brussels drafts rules to force Big Tech to share data. Financial Times, September 30. https://www.ft.com/content/1773edd6-7f1d-4290-93b6-05965a4ff0db.
31 Ocampo, J.A. (2019) Decision on future of Corporate Taxation. February 14. ICRICT. https://www.icrict.com/icrict-in-thenews/2019/2/14/decision-on-future-of-corporate-taxation.
32 Martin, T. W. and Schechner (2018) Facebook, Google May Face Billions in New Taxes Across Asia, Latin America. Wall Street Journal. October 28. https://www.wsj.com/articles/countries-push-digital-taxes-on-tech-giants-1540742400.
33 Swanson, A. (2019) U.S. Announces Inquiry of French Digital Tax That May End in Tariffs. New York Times, July 10. https://www.nytimes.com/2019/07/10/business/us-france-tariffs.html.
34 Ocampo, J.A. (2019) Decision on future of Corporate Taxation. February 14. ICRICT. https://www.icrict.com/icrict-in-thenews/2019/2/14/decision-on-future-of-corporate-taxation.

Gianluca Iazzolino is a post-doctoral research fellow at the Department of International Development, based at the Firoz Lalji Centre for Africa. His main research interests include informal economy, migration and ICTs. He is particularly interested in the political economy of digital innovation and in the Future of Work agenda in middle and low-income countries. He is currently working on two projects, one focusing on data-driven agro-innovation in California’s Central Valley and Kenya’s Rift Valley and another exploring how digitisation and datafication are reshaping public communications and the informal economy in East Africa.

Marion Ouma completed her doctoral studies in Sociology under the South Africa Chair Initiative (SARChl) in Social Policy at the University of South Africa in 2019. Her research interests include sociology, social policy, social protection, policy-making and the political economy of Africa’s development. She has published in Critical Social Policy and authored a book chapter in The African Political Economy edited by Samuel Oloruntoba and Toyin Falola. Currently, she is a research consultant for the project “A Tale of Two Green Valleys: Power Struggles over Data-Driven Agro-Innovation in Kenya’s Rift Valley and California’s Central Valley”.

Laura Mann is an Assistant Professor in the LSE’s International Development department and a research affiliate of the Firoz Lalji Centre for Africa. Her research focuses on the political economy of knowledge and technology. She is currently working on two projects, one examining the political economy of digital data value chains in agriculture (in the Rift Valley, Kenya and the Central Valley, California, USA) and a second examining the role of Western donors in social protection and higher education policy in post-revolutionary Sudan.