Legal and Ethical Implications of Data Privacy in Artificial Intelligence: A Review of Data Privacy Among Learners in Kenyan Secondary Schools
This academic literature review explores the legal and ethical implications of data privacy in artificial intelligence applications among secondary school learners in Kenya. It examines current data privacy frameworks, evaluates ethical considerations related to AI use in education, and identifies best practices for enhancing data protection. Grounded in human rights theory, the study highlights the vulnerabilities of students and the necessity of robust, localized legal and ethical guidelines.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, policymakers, and educational administrators interested in the intersection of AI, data privacy, and secondary education in developing countries.
What the document contains
The document addresses the legal and ethical implications of AI-driven tools in Kenyan secondary schools, focusing on student data privacy risks, existing regulatory frameworks, and best practices for data protection.
The document does not provide binding regulatory rules, a statutory code of conduct, or specific technical enforcement mechanisms, as it is structured as an academic literature review rather than a policy decree.
- The integration of AI in secondary schools raises significant legal and ethical concerns regarding student data privacy.
- Kenya's Data Protection Act (2019) requires more robust implementation and contextualization to effectively safeguard student data in educational settings.
- Human Rights Theory serves as a foundational lens for balancing technological innovation with the protection of learners' privacy rights.
- Schools should adopt advanced data protection technologies, such as encryption and anonymization, to secure sensitive information.
- Bridging the gap between policy creation and execution requires regular compliance audits and staff training.
· Abstract · Introduction · Theoretical Framework · Literature Review · Research Methodology · Findings · Discussion · Conclusions · Recommendations
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
2/5Clear responsibility for AI outcomes
The question of who is responsible when AI systems in schools violate students' privacy is particularly relevant, highlighting the need for clear legal guidelines.
Introduction
screening score · 2026-10-23
Fairness
1/5Non-discrimination and equitable treatment
fostering a safer and more equitable educational environment in Kenyan secondary schools.
Theoretical Framework
screening score · 2026-10-23
Human Dignity
3/5Respect for the inherent worth of persons
Such measures would help ensure that the deployment of AI in schools prioritizes the dignity, autonomy, and privacy of learners.
Theoretical Framework
screening score · 2026-10-23
Human Oversight
0/5Humans remain in control of consequential decisions
screening score · 2026-10-23
Privacy
3/5Protection of personal data and private life
This study explored the legal and ethical implications of data privacy in AI applications within Kenyan secondary schools
Abstract
screening score · 2026-10-23
Transparency
3/5Openness about how AI systems work and are used
Huang emphasizes the need for strong ethical frameworks that prioritize students' rights to privacy, highlighting the importance of transparency and accountability in AI’s use of student data.
Literature Review
screening score · 2026-10-23
Enforcement
2/5Consequences and compliance mechanisms with real force
While Kenya has enacted the Data Protection Act (2019), its implementation in secondary schools may face hurdles
Findings
screening score · 2026-10-23
Impact Assessment
2/5Required assessment of an AI system's risks/impacts before or during use
first, to assess the current legal frameworks and policies governing data privacy in Kenyan secondary schools; second, to evaluate the ethical considerations related to the use of AI technologies
Abstract
screening score · 2026-10-23