Africa’s AI Hopes Rest on Shaky Data Grounds, Warns Expert
African countries are rapidly embracing artificial intelligence, but their efforts may be crippled by poor data quality and weak governance structures, says a leading expert.
Dr. Olatunji Dare, a prominent figure in Africa’s AI landscape, highlighted the need for robust data foundations to support AI adoption across the continent. “Without strong data underpinnings, AI applications are unlikely to deliver the promised benefits,” he emphasized.
Data Quality: A Major Obstacle
Dr. Dare pointed to several factors contributing to poor data quality in Africa, including out-of-date datasets, inadequate data standards, and a lack of transparency in data collection processes. He argued that these issues can lead to AI systems that are biased, incomplete, or simply don’t work as intended.
Weakened Governance Frameworks Compound the Problem
The expert also underscored the importance of effective governance frameworks in supporting AI development. He noted that Africa’s data governance structures are often fragmented, poorly funded, and lacking in coordination, which can hinder the creation of high-quality datasets.
A Path Forward
Dr. Dare recommends that African governments, institutions, and organizations prioritize building stronger data foundations through initiatives such as data standardization, data quality assessments, and transparency in data collection processes. “By prioritizing data quality and governance, we can create a solid foundation for AI development and ensure that its benefits are equitably distributed,” he said.
What this means: If left unchecked, poor data quality and weak governance could undermine Africa’s AI ambitions, limiting the continent’s ability to unlock the full potential of AI for economic growth, improved services, and better lives for citizens.
