Navigating algorithm bias in AI: ensuring fairness and trust in Africa - Pasipamire, Notice; Muroyiwa, Abton (Frontiers in Research Metrics and Analytics, 2024)
This article presents a perspective on the impact of algorithmic bias on information fairness and trust in artificial intelligence (AI) systems within the African context. The author's personal experiences and observations, combined with relevant literature, formed the basis of this article. The authors demonstrate why algorithm bias poses a substantial challenge in Africa, particularly regarding fairness and the integrity of AI applications. This perspective underscores the urgent need to address biases that compromise the fairness of information dissemination and undermine public trust. The authors advocate for the implementation of strategies that promote inclusivity, enhance cultural sensitivity, and actively engage local communities in the development of AI systems. By prioritizing ethical practices and transparency, stakeholders can mitigate the risks associated with bias, thereby fostering trust and ensuring equitable access to technology. Additionally, the article explores the potential consequences of inaction, including exacerbated social disparities, diminished confidence in public institutions, and economic stagnation. Ultimately, this work argues for a collaborative approach to AI that positions Africa as a leader in responsible development, ensuring that technology serves as a catalyst for sustainable development and social justice.