Paper by Chinasa T. Okolo: “The increasing development of machine learning (ML) models and adoption of artificial intelligence (AI) tools, particularly generative AI, has dramatically shifted practices around data, spurring the development of new industries centered around data labeling and revealing new forms of exploitation, including illegal data scraping for AI training datasets. These new complexities around data production, refinement, and use have also impacted African countries, elevating a need for comprehensive regulation and enforcement measures. While 38/55 African Union (AU) Member States have existing data protection regulations, there is a wide disparity in the comprehensiveness and quality of these regulations and in the ability of individual countries to enact sufficient protections against data privacy violations. Thus, to enable effective data governance, AU Member States must enact comprehensive data protection regulations and reform existing data governance measures to cover aspects such as data quality, privacy, responsible data sharing, transparency, and data worker labor protections. This paper analyzes data governance measures in Africa, outlines data privacy violations across the continent, and examines regulatory gaps imposed by a lack of comprehensive data governance to outline the sociopolitical infrastructure required to bolster data governance capacity.
This work introduces the RICE Data Governance Framework, which aims to operationalize comprehensive data governance in Africa by outlining best measures for data governance policy
reform, integrating revamped policies, increasing continentalwide cooperation in AI governance, and improving enforcement actions against data privacy violations…(More)”
Operationalizing Comprehensive Data Governance in Africa
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