African Creators Struggle to Secure Decent Income in Gig Economy
When money can’t cross borders
Stripe is a global financial services platform unavailable in almost all francophone Sub-Saharan African countries. The PayPal payment platform is partially available, though withdrawals are restricted. For creators based in Cotonou, Dakar, or Lomé, collecting payments from American or European customers poses obstacles that their counterparts in Berlin or Toronto couldn’t even imagine. This situation presents a structural bottleneck, preventing significant access to the global market.
In response to this exclusion, alternatives have emerged, including Selar, M-Pesa, and Chipper Cash. A blog post by software company Nestuge explains their real-world advantages and limitations. These tools have become the everyday infrastructure of an economy that official systems have refused to serve. Douglas Kendyson, the founder of Selar, explains that it aims to offer creators a direct and credible way to monetize their skills worldwide. According to a study published in the International Journal of Advanced Scientific Research, African creators who use these platforms have significantly higher levels of entrepreneurial autonomy than those who depend exclusively on Western platforms.
Ultimately, this informal economy operates outside any institutional framework, compensating for the lack of a structured and viable ecosystem. Much like the informal trade networks that serve the continent across national borders, it is blazing its own trail where the state and global market have failed to build connecting infrastructure. It’s a necessary infrastructure that’s as resilient as it is spontaneous.
Cultural data, profits elsewhere
A study on mapping the data labor supply chain in Africa found that thousands of workers, mainly in Sub-Saharan Africa, work as moderators, filtering traumatic content while annotating datasets to train artificial intelligence (AI) for major technology platforms, and that they contribute to systems that deny them any rights. The authors use the term “digital apartheid” to describe infrastructure in which access to tools, markets, and remuneration remains structurally unequal based on location.
Generative AI has added a layer of irony to the equation. Initiatives like Waxal, launched by Google to document some African languages, rely on thousands of African contributors. However, there is a structural problem. Once fed this open-source data, the machine generates content that circulates and is monetized, with the original language keepers receiving no revenue, shifting from digital inclusion to a new form of cultural extractivism.
A study, titled “Data Flows and Colonial Regimes in Africa: A Critical Analysis of the Colonial Futurities Embedded in AI Recommendation Algorithms in Africa,” shows that these same models are subsequently used to generate cultural African content, such as avatars, music, and visuals, which compete directly with the human creators whose work provided the source material. The system is restricted since value flows in only one direction.
The case of Shudu Gram is a prime example. This entirely digital supermodel, whose appearance mirrors that of a black South African woman, was created and marketed by a white British photographer, Cameron-James Wilson. She received substantial advertising budgets, imitating a culture with which she shares no origin.
