SafetyFairnessEthicscs.CY
Toward an African Agenda for AI Safety
Samuel T. Segun, Rachel Adams, Ana Florido, Scott Timcke, Jonathan Shock, Leah Junck, Fola Adeleke, Nicolas Grossman, Ayantola Alayande, Jerry John Kponyo, Matthew Smith, Dickson Marfo Fosu, Prince Dawson Tetteh, Juliet Arthur, Stephanie Kasaon, Odilile Ayodele, Laetitia Badolo, Paul Plantinga, Michael Gastrow, Sumaya Nur Adan, Joanna Wiaterek, Cecil Abungu, Kojo Apeagyei, Luise Eder, Tegawende Bissyande
August 12, 2025
arXiv.org
4 citations
1 influential
Key Takeaways
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Africa faces unique AI risks that differ from global concerns: The paper identifies threats specific to the African context, including deepfakes used for electoral interference, data colonialism (where African data is extracted and controlled by foreign entities), labor market disruption, and disproportionate exposure to AI's environmental costs—risks that aren't adequately addressed in current global AI safety discussions.
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African voices are largely absent from global AI governance: Despite being significantly affected by AI development and deployment, African perspectives and stakeholders have minimal influence over emerging international AI safety standards and policies, leaving the continent vulnerable to decisions made without its input.
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Current AI safety infrastructure on the continent is insufficient: While Africa has computer incident response teams, it lacks dedicated AI Safety Institutes or offices, meaning there are no established institutions to monitor, research, or respond to AI-specific risks affecting African populations.
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A comprehensive five-point action plan is needed: The paper proposes establishing an African AI Safety Institute, developing AI literacy programs for the public, creating early warning systems in 25+ African languages, prioritizing human rights protections for vulnerable populations, and establishing an annual African Union-level forum to coordinate AI safety and security efforts.
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Language diversity requires tailored AI safety approaches: The emphasis on benchmark suites for 25+ African languages highlights that generic global AI safety measures won't adequately protect African communities without localized solutions that account for linguistic and cultural contexts.