Many developing countries are under pressure to adopt digital technologies like AI to increase government efficiency.
The short-term gains are real: streamlined services, faster decision-making, unlocking data siloes, and cost savings. But those benefits come with a greater cost. It deepens their dependence on foreign Big Tech infrastructure. The result is a new form of colonialism in which fragile or poorly regulated states become testing grounds for tools designed ultimately for repression.
What does this look like in practice?
Taking Kenya as an example. In November 2023, Kenya introduced the Maisha Namba, a digital ID card that replaced the previous generation of physical ID cards. The launch sparked public and judicial scrutiny amid accusations that it would create a central data store susceptible to political misuse.
Critics argue that the program was oversold and unnecessary. Roughly 90% of Kenyans already possess identification. The remaining 10% have historically struggled to access national IDs and birth certificates or live in areas with low internet coverage.
Maisha Namba thus discriminates against those without internet access, while offering little more than convenience to those who do. The lack of tangible benefits on an individual level suggests that programs such as the Maisha Namba serve broader interests.
Indeed, Kenya’s previous iteration of digital identification—the Huduma Namba—failed because officials failed to explain the system’s necessity to the public. Was this due to incompetence? Or were officials so enamored by the system’s surveillance capabilities that they forgot it actually had to be used by citizens?
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By GlobalDataWhile tools like the Maisha Namba can seem like signs of progress and advancement, exporters and home-country regulators often treat these transactions as purely commercial deals; meanwhile, the downstream harms—social exclusion, targeted surveillance, and erosion of local sovereignty—persist far longer.
The AI algorithmic west
Some observers now label these dynamics “digital colonialism”: the transfer of foreign technological infrastructure into developing countries in ways that deepen rather than address inequality.
Maisha Namba, like many digital ID projects in Africa, is backed by global entities like the United Nations Development Programme and the Gates Foundation, which lend legitimacy, advice, and funding. This raises uncomfortable parallels with past resource extraction by Western powers, except this time, data is the resource.
In return for “supporting” the digital transformation of developing countries, tech giants, global entities, and external donors are permitted to test and fine-tune their models.
Digital colonialism shares many other mechanisms with classic colonial patterns. For instance, these AI models are trained on data scraped from the global internet, which is dominated by Western languages, norms, and perspectives. When these models are deployed in non-Western settings, they bring those biases with them.
A healthcare chatbot trained on Western medical data might overlook local practices. Or a facial recognition model may exhibit higher error rates for people of color and women, as they are trained on datasets overwhelmingly composed of light-skinned males, as highlighted by various studies.
The resulting wrongful arrests and discrimination lead to an erosion of trust, which is used to justify further surveillance and harassment. Because many of these systems are opaque “black boxes,” affected individuals face steep barriers to contest automated decisions—whether being denied services or flagged as dissidents.
As AI models scale, they tend to flatten nuance, aggregating local cultures and data into homogeneous outputs shaped by Western values. The spread of digital ID frameworks and AI-driven surveillance is one vector by which Western values are becoming encoded into fragile states. There is a double standard here, too: Western democracies often criticise China’s use of surveillance technology while their own companies sell similar tools to undemocratic regimes.
Passing the blame and next steps
When governments rely on foreign platforms, it is unclear who bears responsibility for harms or policy choices. Vendors can claim technical neutrality or invoke contractual limits, while host states may simply blame external issues or the vendor itself. This allows involved parties to displace responsibility.
This diffusion of responsibility facilitates mission creep, where technologies sold for border control or public safety are redirected to political surveillance. The experience of firms such as Clearview AI, which quietly expanded facial-recognition deployments into Latin America and was later reported to have been used in conflict settings in Ukraine, highlights how these tools quickly travel beyond their intended use cases.
Ultimately, the issue is that these systems may be too effective for their own good. When private companies expand into regions that have weaker privacy protections or are experiencing instability, the immediate operational advantages their systems provide fast-track them into other government systems and projects.
In their wake, they leave a trail of questions over privacy, identification, profiling, and long-term mass surveillance. So what can be done? For one, there should be greater export controls on surveillance technology, such as continuous auditing of cross-border technology transfers.
Additionally, these deals must commit to prioritizing citizens’ rights to privacy, with clear vendor obligations and liability. Contracts should embed enforceable protections for citizens’ privacy, clear vendor obligations, and liability clauses—perhaps enforced through a global compliance framework. Governments should also prioritise investing in local, open, community-owned technology that builds domestic capacity rather than defaulting to multinational dealers. But above all, there needs to be more transparency: public disclosure of contracts, accessible complaint mechanisms for citizens, and independent oversight.
