From Privacy Safeguards to Innovation Barrier: Assessing Tanzania’s Personal Data Protection Act in the Age of AI

Abstract

The rise of digitization has led to the widespread adoption of Artificial Intelligence (AI) technologies, driving efficiency and innovation across sectors. AI systems rely on vast datasets to enhance accuracy, but their deployment raises concerns over data privacy, misuse, and bias. In response to the growth of technology and the collection of personal data, different jurisdictions have enacted data protection laws. This study focuses on Tanzania’s Personal Data Protection Act (PDPA), which aims to regulate the processing of personal data, and critically examines its implications for AI implementation in Tanzania. This study analyses key provisions of the PDPA, such as restrictions on data sharing, privacy safeguards, and the role of Data Protection Commissions (DPCs) in comparison with global and regional data protection frameworks to assess their implications for AI implementation. Findings suggest that, while the PDPA is not an AI-specific law, its stringent data access controls and compliance burdens may limit AI-driven advancements. The study also highlights how excessive personal data restrictions can reduce AI accuracy and fairness, as models require diverse datasets for effective learning. The study recommends potential strategies Tanzania could adopt, including regulatory sandboxes and risk-based compliance approaches, to balance privacy protection with AI innovation. This study advocates for the adoption of AI-specific guidelines that promote ‘privacy by design’ in AI models and introduces flexible policies that support responsible AI implementation. While the PDPA establishes a crucial framework for data governance in Tanzania, its applicability requires continuous assessment to prevent unintended barriers to AI growth.