ARTIFICIAL INTELLIGENCE AS AN EMERGING CHALLENGE TO DATA PROTECTION AND PRIVACY LAW IN UGANDA

• Ampulira Ronald

  Uganda Pentecostal University , Kampala International University

  Author

• Adenyuma Gabriel

  Kampala International University

  Author

• Ahmed Hussein Folrunsho

  University of Ilorin

  Author

The rapid proliferation of artificial intelligence (AI) technologies across Africa's public and private sectors has exposed fundamental inadequacies in the legal architecture governing data protection and privacy. In the particular context of Uganda which is the focus of this study  the Data Protection and Privacy Act, Cap 97 (DPPA) enacted in 2019 provides a foundational framework for the regulation of personal data, yet it predates the mainstream adoption of AI and conspicuously fails to address the distinctive risks that AI-driven systems pose to the rights of data subjects as is the case in many other parts of the continent. This article critically examines the interface between artificial intelligence and Uganda's data protection law, focusing on three principal concerns: the erosion of data minimisation, transparency, and accountability principles by AI systems; the proliferation of algorithmic bias and its discriminatory effects on marginalised populations; and the deployment of AI-enabled mass surveillance technologies by state and non-state actors without adequate legal safeguards. Drawing on the DPPA, comparative jurisprudence from the European Union, Kenya, Rwanda, and India, and enforcement decisions of the Personal Data Protection Office, the article argues that Uganda's current legal framework is structurally ill-equipped to govern AI-driven data processing. It proposes targeted legislative reforms, including the enactment of dedicated AI governance provisions within the DPPA, mandatory algorithmic impact assessments, and the strengthening of the PDPO's institutional independence and technical capacity. The study sets the pace for similar studies in other parts of the African continent where similar studies have not been carried out.

• Ronald, Gabriel and Hussein Article

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