AI technology is capturing the African imaginations as a gateway to progress and prosperity. There is a growing interest in AI by different actors across the continent including scientists, researchers, humanitarian and aid organizations, academic institutions, tech start-ups, and media organizations. Several African states are looking to adopt AI technology to capture economic growth and development opportunities. On the other hand, African researchers highlight the gap in regulatory frameworks and policies that govern the development of AI in the continent. They (...) argue that this could lead to AI technology exacerbating problems of inequalities and injustice in the continent. However, most of the literature on AI ethics is biased toward Euro-American perspectives and lack the understanding of how AI development is apprehended in the Global South, and particularly Africa. Drawing on the case study of the first African Master’s in Machine Intelligence program, this paper argues for looking beyond the question of ethics in AI and examining AI governance issues through the analytical lens of the raciality of computing and the political economy of technoscience to understand AI development in Africa. By doing so, this paper seeks a different theorization for AI ethics from the South that is based on lived experiences of those in the margins and avoids the framings of technological futures that simplistically pathologize or celebrate Africa. (shrink)

This special theme of Big Data & Society explores connections, relationships, and tensions that coalesce around data, power, and racial formation. This collection of articles and commentaries builds upon scholarly observations of data substantiating and transforming racial hierarchies. Contributors consider how racial projects intersect with interlocking systems of oppression across concerns of class, coloniality, dis/ability, gendered difference, and sexuality across contexts and jurisdictions. In doing so, this special issue illuminates how data can both reinforce and challenge colorblind ideologies as well (...) as how data might be mobilized in support of anti-racist movements. (shrink)

The proliferation of AI systems across all domains of life as well as the complexification and opacity of algorithmic techniques, epitomised by the bourgeoning field of Deep Learning (DL), call for new methods in the Humanities for reflecting on the techno-human relation in a way that places the technical operation at its core. Grounded on the work of the philosopher of technology Gilbert Simondon, this paper puts forward individuation theory as a valuable approach to reflect on contemporary information technologies, offering (...) an analysis of the functioning of deep neural networks (DNNs), a type of data-driven computational models at the core of major breakthroughs in AI. The purpose of this article is threefold: (1) to demonstrate how a joint reading of Simondon’s mechanology and individuation theory, foregrounded in the Simondonian concept of information, can cast new light on contemporary algorithmic techniques by considering their situated emergence as opposed to technical lineage; (2) to suspend a predictive framing of AI systems, particularly DL techniques, so as to probe into their technical operation, accounting for the data-driven individuation of these models and the integration of potentials as functionality; and finally, (3) to argue that individuation theory might in fact de-individuate AI, in the sense of disassembling the already-there, the constituted, paving the way for questioning the potentialities for data and their algorithmic relationality to articulate the unfolding of everyday life. (shrink)