Nigeria’s Use of AI to Locate Urban Poor Sparks Doubts Over Data Integrity and Real Impact

 

AI or Eye Wash? Questions Arise Over FG’s Tech-Driven Poverty Mapping Efforts

Despite bold claims by the Minister of Humanitarian Affairs and Poverty Reduction, Nentawe Yilwatda, that artificial intelligence is now central to Nigeria’s poverty reduction strategy, skepticism continues to trail the federal government’s use of advanced technology to identify and assist the urban poor.

During a recent interview on Arise TV’s Prime Time programme, Yilwatda announced that the national social register has expanded from 13 million to 19.7 million individuals, thanks to the deployment of AI. He explained that the system now includes not just rural Nigerians, but also those in urban slums—allegedly pinpointed using a combination of satellite imagery, telecom data, and financial behavior analytics.

However, the sweeping nature of these claims has raised eyebrows among observers who question the transparency and reliability of the data involved. The minister provided little detail on the exact AI models used, the validation process, or the metrics applied to determine whether someone is poor.

“To help someone, you must first know them,” Yilwatda stated. “That’s why we started by validating the social register.” He claimed that urban slum areas were identified through satellite imaging, after which mobile numbers within those areas were tracked via telecom base stations. These were then processed by AI to identify the “urban poor” based on indicators such as access to financial services.

While this techno-driven narrative may sound impressive, it remains unclear how data privacy was handled or how consent was obtained from those being digitally profiled. Questions are also being raised about whether such methods can truly capture the nuanced realities of poverty in a country as complex and diverse as Nigeria.

The minister’s announcement that the federal government is now targeting 15 million households—about 75 million Nigerians—further complicates the picture. With 43 million households nationwide, the implication is that over one-third of the population is being targeted for intervention. Yet, critics say there is still no comprehensive, independent audit of the social register to verify these numbers.

Yilwatda made further claims regarding the distinctions between food poverty and multidimensional poverty—terms commonly used in policy circles but often loosely applied in public discourse. He stated that around 42% of Nigerians suffer from food poverty, which translates to about 80 million individuals. From this pool, the government hopes to reach 15 million households through conditional cash transfers of N75,000 each.

Though the cash might offer some relief, especially in rural areas, the minister’s confidence in its transformative power may be overstated. A joint study with the World Bank and civil society groups reportedly showed that 18% of recipients started small-scale businesses, while others used the funds for food and school fees. However, the government has not made this research publicly available for scrutiny, and it is unclear whether the sample size or methodology used justifies such broad conclusions.

Meanwhile, the government insists that structural reforms are underway. Yilwatda said N1.5 trillion has been made available through the aggregate bank for agricultural loans and that student scholarships are being offered to ensure education access for poor households. He also claimed that food inflation has stabilized—an assertion many Nigerians might find difficult to reconcile with their everyday market experience.

Past poverty interventions, the minister noted, were largely humanitarian in nature—focused on relief materials and one-off payments. The new approach, he asserted, is designed to drive “actual poverty reduction” and move Nigerians out of poverty entirely.

But critics warn that replacing one opaque system with another dressed in digital jargon doesn’t guarantee better outcomes. For many Nigerians, the real test will be whether these AI-powered solutions lead to tangible improvements or simply serve as another layer of bureaucracy in an already over-politicized welfare system.

Despite the minister’s optimistic tone, questions remain about how inclusive, ethical, and effective the government’s tech-based targeting methods truly are. Until the processes are independently verified and publicly accountable, many are likely to view the AI initiative with a healthy dose of skepticism—if not outright suspicion.