Evaluating the Ethical Practices in Developing AI and Ml Systems in Tanzania - Lazaro Inon Kumbo; Victor Simon Nkwera; Rodrick Frank Mero (ABUAD Journal of Engineering Research and Development)
Artificial Intelligence (AI) and Machine Learning (ML) present transformative opportunities for sectors in developing countries like Tanzania that were previously hindered by manual processes and data inefficiencies. Despite these advancements, the ethical challenges of bias, fairness, transparency, privacy, and accountability are critical during AI and ML system design and deployment. This study explores these ethical dimensions from the perspective of Tanzanian IT professionals, given the country's nascent AI landscape. The research aims to understand and address these challenges using a mixed-method approach, including case studies, a systematic literature review, and critical analysis. Findings reveal significant concerns about algorithm bias, the complexity of ensuring fairness and equity, transparency and explainability, which are crucial for promoting trust and understanding among users, and heightened privacy and security risks. The study underscores the importance of integrating ethical considerations throughout the development lifecycle of AI and ML systems and the necessity of robust regulatory frameworks. Recommendations include developing targeted regulatory guidelines, providing comprehensive training for IT professionals, and fostering public trust through transparency and accountability. This study underscores the importance of ethical AI and ML practices to ensure responsible and equitable technological development in Tanzania.