Engagement in Data Protection Ethical Practices Among Users of Artificial Intelligence Systems in Higher Education Institutions in Mwanza City, Tanzania
DOI:
https://doi.org/10.33687/ijef.003.02.00172Keywords:
Data Protection, Engagement, AI Ethics, Higher EducationAbstract
Data protection ethical practices represent the behavioral dimension of data privacy literacy the extent to which users actively take steps to safeguard their personal information when engaging with Artificial Intelligence (AI) systems. This study analysed users' engagement in data protection ethical practices when using AI systems in Higher Education Institutions (HEIs) in Mwanza City, Tanzania. An explanatory sequential design was employed, with 200 respondents consisting of 163 students and 37 academicians, surveyed through a five-point Likert scale questionnaire, supplemented by 6 key-informant interviews with institutional administrative staff. Descriptive statistics and Braun and Clarke's thematic analysis were applied to quantitative and qualitative data respectively. Findings revealed uniformly low engagement across all protective behaviours for both user groups. Among academicians, the most frequently practiced behaviour was checking privacy terms before recommending an AI tool (sometimes, often and always 48.6%), while informing students in the syllabus about AI data collection (sometimes, often and always: 18.9%) and consulting the Data Protection/Legal Office before deploying a new AI system (sometimes, often and always: 21.6%) were near-absent. Among students, the highest-engagement behaviour was avoiding uploads of personal files to public AI without checking policy (sometimes, often and always: 59.5%), while reporting suspicious data requests to the university was the least common (sometimes or more: 30.7%). The absence of institutional policies, Data Protection Officers, privacy training, and reporting mechanisms is identified as the structural cause of this poor engagement. The study recommends mandatory privacy training, institutional AI policy development, and a functioning Data Protection Officer (DPO) mechanism as urgent priorities for Mwanza HEIs.
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Copyright (c) 2026 Cesylia Robert Shangal, Demetria Mkulu, Raymond Ndomba (Author)
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