Lawmaker pushes adoption of AI to limit corruption in nurse and teacher recruitment
By Staff Writer
The Zimbabwean Parliament has been formally petitioned to implement a centralized, automated recruitment system for student nurses and teachers to combat widespread allegations of corruption and bribery within the current manual hiring process.
In a motion tabled before Parliament, Luveve-Makhandeni Member of Parliament Hon. Descent Bajila warned that the country’s training recruitment processes are no longer just competitive, but increasingly vulnerable to manipulation.
“There are moments when the credibility of our public systems must be confronted with candour,” the MP said. “The recruitment of student nurses and trainee teachers is one such moment.”
Each year, demand for training places far exceeds supply. More than 100,000 applicants compete for approximately 1,200 nursing spots nationwide, while teacher training institutions face similar constraints. The result is a high-stakes process where a single decision can shape a lifetime.
“In such a context, the shortlisting process ceases to be a mere procedural step,” the MP told Parliament. “It becomes the decisive gateway through which merit must be rigorously assessed and seen to prevail.”
Citing investigations by the Zimbabwe Anti-Corruption Commission (ZACC), Hon. Bajila pointed to allegations of bribery, leaked interview questions, and manipulated shortlists. In the most troubling cases, aspiring student nurses were reportedly asked to pay between US$1,200 and US$1,500 to secure placements.
“What emerges is not an isolated lapse, but a pattern of irregularity,” the MP said. “Opportunity is being commodified, transformed from a merit-based system into a transactional exercise.”
At the heart of the proposal is a shift toward Artificial Intelligence-assisted recruitment systems. The aim is not to replace human judgment, but to reduce discretion at the most vulnerable stages of the process.
“Artificial Intelligence has the capacity to process large volumes of applications with a uniformity that manual systems cannot reliably sustain,” said Hon. Bajila. “It introduces a level of consistency, transparency, and resistance to manipulation.”
Under such a system, applications would be assessed using predefined criteria, such as academic performance and eligibility requirements. AI tools could also flag irregularities, including fraudulent qualifications, creating what the MP described as “a system that is both systematic and auditable.”
Mlungisi Dube, an Anti-corruption activist shared experiences between 2019 and 2020 assisting young people with applications into nursing programmes.
“In one intake, Mpilo Central Hospital reportedly selected only 4 students out of 25 expected places, raising serious questions about how final selections were made. We also encountered numerous cases of qualified applicants who were not allocated places without clear justification. These patterns are consistent with broader allegations of irregularities, including bribery and preferential treatment.” said Dube.
An aspiring nursing student, who commented on the condition of anonymity, expressed deep frustration with the current state of affairs. “I have lost hope in the application process; it has been three years trying to secure a place at the nursing schools,” they said. “At some point, I travelled to Harare just to submit my application. Until today, there has been no joy.”
Nursing recruitment in Zimbabwe remains a structured process primarily managed by the Ministry of Health and Child Care (MoHCC).
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