Speaker
Description
Githui, F.
KCA University
githui@kcau.ac.ke
Track: AI, Emerging Technologies and Future Learning
Background
Institutions of higher education in Africa Sub-Saharan region are rapidly adopting AI-driven systems for their admissions, educational analytics, and student support services. But, at present, there is hardly any concrete data showing if these digital technologies will assist Lastly the digital divide or if they might be the ones that deepen it further. Despite the active discussions around AI, issues such as bias in algorithms, data privacy, and uneven distribution of infrastructure leading to inequality have been hardly addressed in higher education in the region.
Objective
This study investigated how algorithmic governance practices influence digital equity in East African universities. Specifically, we examined: (1) the prevalence and types of AI tools currently deployed; (2) perceived barriers to equitable access and outcomes; and (3) strategic institutional capabilities that mediate the relationship between AI adoption and inclusive learning environments.
Methods
A convergent mixed methods design was employed. Phase 1: Survey of 284 academic staff, administrators, and students from six universities in Kenya and Uganda (stratified by public/private and technology maturity level). Phase 2: Semi structured interviews with 24 university leaders, EdTech coordinators, and policy officers. Quantitative data were analysed using descriptive statistics and ordinal logistic regression; qualitative data underwent thematic analysis. The study drew on Githui’s algorithmic sovereignty framework and Njuru’s higher education partnership model.
Results
Most institutions surveyed admitted to using at least one AI tool, for example, automated admissions, plagiarism detection, or predictive analytics. Yet, only a few had a formal algorithmic governance policy. Significant equity gaps were unveiled: students from low-income backgrounds and those with limited digital access at home were much less inclined to consider AI tools fair or helpful. Three main barriers to institutional adoption of AI came out of the research. Firstly, lack of AI literacy among faculty. Secondly, absence of locally relevant datasets. Thirdly, lack of stakeholder engagement in the design of the tools. But, universities which set up multi-stakeholder AI oversight committees saw a dramatic increase in student satisfaction with digital services and a decrease in the number of dropouts in courses mediated by AI. Essential strategic enablers included providing staff and students with inclusive AI training, using transparent data consent protocols, and forming partnerships with government, EdTech companies, and civil society for the co-design of affordable solutions.
Conclusion
Algorithmic governance does not bring equality by default. If there is no deliberate strategic intervention, the use of AI in African higher education could worsen the digital divide. But, the data reveals that universities are able to close these disparities through inclusive governance, skills enhancement, and co-innovation. In this paper, we recommend a Strategic Digital Equity System based on three main elements: Policy & Ethics, Infrastructure Sensitive to Local Context, and Participatory Design. This research gives a roadmap that university administrators, government officials, and international development agencies can use to prepare inclusive and future-ready higher education ecosystems in Africa.