Artificial intelligence is rapidly reshaping editorial decision-making, content production, and audience targeting across African newsrooms. Yet most organisations are adopting AI without formal governance structures, gender safeguards, or institutional accountability. This course equips media leaders to treat AI not as a technical experiment, but as a strategic organisational transformation that requires policy, oversight, and inclusive leadership. This course translates complex AI governance challenges into practical institutional tools that media executives can implement immediately.
Curriculum
- 6 Sections
- 13 Lessons
- 6 Weeks
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- Training ObjectivesParticipants will be able to: - Assess organisational risks related to AI adoption, including algorithmic bias, opacity, labour displacement, and technology-facilitated gender-based violence - Identify how AI systems may reproduce gender inequality in hiring, promotion, content generation, and audience targeting — grounded in empirical research from African media contexts - Develop a newsroom-specific Gender-AI Integration Roadmap using structured diagnostic tools and governance templates - Establish governance mechanisms for ethical, transparent, and accountable AI use, informed by international frameworks and locally grounded standards - Design reskilling and leadership pathways to ensure women’s meaningful participation in AI decision-making at editorial and institutional levels0
- Training ApproachThe course combines multiple pedagogical modes to maximise practical application and peer learning: • Self-paced modules with short video lectures, practical guides, and structured readings drawn from current AI governance literature and African media research • Real-world case studies from African and Global South contexts, including Quanta’s own research on digital media ecosystems, information manipulation, and climate discourse across the continent • Interactive templates and policy drafting exercises designed for immediate institutional application • Weekly live sessions focused on peer learning, organisational problem-solving, and expert Q&A • Capstone project: a draft AI governance framework tailored to each participant’s newsroom, reviewed by Quanta’s team of data scientists, media scholars, and governance specialists0
- Week One: AI in the Newsroom as a Governance Challenge• Mapping AI use across editorial workflows: content generation, audience analytics, moderation, and distribution • Risk assessment frameworks for AI adoption in resource-constrained newsroom environments • Organisational AI maturity diagnostic tool (provided as interactive template) • Case study: Lessons from Project Maai’s computational analysis of climate content across 35,000+ global outlets4
- Week Two: Gender, Power, and Algorithmic Decision-Making• Gender bias in automated content generation, recommendation algorithms, and analytics pipelines • Technology-Facilitated Gender-Based Violence (TFGBV) risks in AI-mediated newsroom environments • Case studies from African media contexts, including computational analysis of gendered discourse patterns in Southern African news media • Practical session: Auditing an AI tool for gender bias using structured evaluation frameworks3
- Week Three: Building Gender-Responsive AI Policy• Drafting internal AI governance policies: accountability structures, transparency requirements, and ethical standards • Audit and accountability mechanisms: how to evaluate AI procurement, vendor claims, and algorithmic outputs • Ethical procurement and vendor assessment using structured evaluation guides • Drawing on Quanta Intelligence’s experience developing the University of Eswatini’s Generative AI Guidelines as a governance case study3
- Week Four: Leadership and Implementation• Gender-AI Integration Roadmap development: participants draft tailored roadmaps for their newsrooms • Reskilling and workforce transition strategies to ensure equitable AI adoption • Institutional oversight structures: decision committees, review boards, and reporting mechanisms • Capstone presentation: Participants present draft AI governance frameworks for peer review and expert feedback3
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