text: Discussions on digitalisation and datafication are often conducted within an economic frame, creating the perception that economic progress equates to social progress. While economic empowerment is inextricably linked to social progress, feminist research has shown that defining development agendas based solely on economic dimensions is often detrimental to marginalised groups.
  Understanding the value of data, however, is a complex matter not dissimilar from the challenges of defining empowerment/equality has been for diverse feminist groups. Data does offer oppressed and marginalised communities the opportunity to visualise their exclusion facilitating greater accountability, for example, as evidence for inclusive policymaking. However, the (emerging) data economy is not inherently neutral – it has developed in an extremely unequal world based on patriarchal, classist, sexist, colonial and imperial subjugation. These tropes do not disappear because of economic development. Although it is important to acknowledge that the data economy is founded in the context of these inequalities, being in its nascence creates the opportunity for malleable policy development.
  With the necessary political will and normative framing this provides an opportunity to redress these inequalities. Everyone benefits when we seek to understand digitalisation and datafication as change agents with the ability to effect positive economic change – but there are underlying political and social dimensions that determines the nature of this change and are therefore critical to consider as we deliberate the elements of the data economy. Which are: questioning power and interests, and how these relate to and reflect intersectional inequality and political, social and economic exclusion. It is this intersectional lens that enables policy makers and researcher to account for power asymmetries, vested interests and act in the public interest not only to enable inclusion but redress inequality.
  Who and what gets counted is decided by power
  Current policy responses to datafication prioritise the ravenous collection of data from which analysis can be derived, ostensibly to improve decision-making in various areas of society. However, we cannot ignore that what and who gets counted is decided by those in power. In his book, The Uncounted, Alex Cobham explains the problem as a long history of women being socially, politically and economically disempowered because they are excluded from data systems, which inform policy and/or socio-economic initiatives.
  Consequently, the old trope that ‘what is measured can be managed’ is not always true. For example, gross domestic product (GDP), commonly used as the singular measure of economic progress, typically ignores women’s contribution to economic development through care work because it does not fit into common indicators. As Cobham explains, “…GDP is a gender-biased measure of a reality that is itself already deeply, structurally unequal. Women’s participation in the labour force globally is estimated to be 26 percentage points lower than that of men”.
  Ignoring the hegemonies which define useful data and information is a recipe for disaster, as we risk not only transposing existing structural inequalities onto the digital economy, but also having those very inequalities exacerbated. Feminist research shows to aim for sustainable impact policy makers should prioritise interventions exposing existing power disparities. Over the years, the feminist agenda has shifted from a development focused paradigm of playing catch-up, to one which seeks justice by exploring new paradigms – a case in point is the United Nations Data2x initiative which seeks to get all data disaggregated by sex.
  The data economy requires an intersectional approach
  Although data can aid in drawing analysis for justice, feminists are not naïve to the network effects of data. Gender research itself operates within a binary which defines privileged women and men from the global North as thinkers and activists while those from the global South are viewed as the lucky recipients or beneficiaries of this thought leadership. Data can be carefully curated to sustain the production and coproduction of these two groups. bell hooks interprets this as the ‘politics of location’, where the privileged are at the centre while those who exist at the margins are hidden from society, spoken for and at, and mostly disempowered by those at the centre.
  In the 2020 docudrama Social Dilemma, the transdisciplinary nature of the data economy lays bare the position of a small group of individuals as all-knowing thinkers. They are all working tirelessly to ensure the benefits of this data-intensive world is inclusive and ‘leaves no one behind’ – while systematically excluding and pushing black and poor people to the margins.
  Fortunately, most feminist researchers and activists are not too concerned with fitting into the paradigms built by phenomena, which engendered the existing structures of inequality in the first place. For example, African feminist researchers are prioritising an approach in which each voice is heard. Genuine efforts are underway to ensure that data and digital spaces are inclusive by exploring alternative concepts for a transdisciplinary definition of the data economy. Evidence of this can be found in Pollicy’s latest Data Feminism report, which maps how feminist organisations across the African continent are collecting, sharing and using digital data to achieve social justice objectives that are pivotal to women’s empowerment. The study rejects the normative assumption that data or technology is neutral, while highlighting how power prevents women from achieving justice. It calls for an Afrofeminist approach to data collection within a decolonial framework that is sensitive to indigenous knowledge.
  What is the way forward?
  Adopting an intersectional praxis approach, I believe, allows us to understand the interlocking systems of structural inequalities. Viewing the elements of the data economy through a single dimension inhibits us from devising interventions whether strategies, policies or governance frameworks, which are accommodating enough of understanding and preventing the structural injustice beyond economic (or any other single set of indicators) with in complex global systems. We ought to move beyond debating the nationalisation of data with the hope of receiving short-term financial gains to dealing with the structural problem of exploitative extraction by empowering communities to be able to exercise their rights and preferences. More broadly there should be room to explore the underlying notions of privacy which includes new forms of data stewardship safeguarding both personal and collective rights.
  The data economy should garner insights from those who know by experience; those resisting and fighting from the margins. It is important to realise that while there are universal harms, the impacts and risks may be very uneven. For instance, it is an injustice to black women to assume platforms (powered by data) have positive network externalities – black women are often the target of abuse on the internet, their voices are silenced and they are the least likely to benefit as micro-workers. These experiences are only starting to be foregrounded, as black women’s voices in tech are heard.
  As African governments race to respond to the datafication and digitalisation of society, questions of power should foreground discussions on data accessibility and availability, classification, and its protection. The public voice should also be heard in addressing issues related to data rights and ethics. Ultimately, there’s no easy way forward, as there is no one single way of viewing the data economy and no single voice that matters more than another. However, prioritising and exploring various segments of the African data economy through a feminist lens, including policy issues of data systems, data localisation and data sovereignty, is of vital importance for an intersectional and inclusive approach to development that starts to dismantle structural inequalities.