Contemporary Challenges in IT: AI in Healthcare and Education
Keywords:
Artificial Intelligence, Healthcare Innovation, Educational Technology, Ethical AI Governance, Digital Equity, Predictive Analytics
Abstract
The article examines the modern issues and possibilities of Artificial Intelligence (AI), both in healthcare and education, as two of the most pressing spheres of society that require AI implementation. As countries stay on track to achieve the United Nations Sustainable Development Goals, specifically SDG 3 (Good Health and Well-being) and SDG 4 (Quality Education), AI has become a disruptive tool that could change the way service delivery is done, how people access services, and the outcome. However, the paper stresses that AI could worsen the current inequalities unless close attention is paid to these issues through careful ethical governance, inclusive design, and investment in digital infrastructure.
AI applications in healthcare include various types of diagnostic imaging, telemedicine, clinical decision support systems, and new models of care delivered through technologies such as NLP and predictive analytics. The case studies of the U.S. and Rwanda also represent the opportunities and hazards of AI, such as diagnostic level accuracy, data fragmentation problem, algorithm bias, and minimal clinical validation.
In education, AI is used in the form of intelligent tutoring systems, adaptive assessments, and automation of administration and learning. Such efforts as adaptive learning provided by Arizona State University and the Rori AI tutor project in Ghana show opportunities related to equity and scalability. However, there is still some worry about privacy, algorithm discrimination, and ineffective teacher training.
Through a comparative analysis of the two sectors, the article provides an insightful look into their similarities, including infrastructure requirements and data bias, as well as the differences between user adoption, regulation, and risk tolerance. It proclaims cross-sectoral policy frameworks, capacity-building programs, and an ethics approach to AI design to guarantee sustainable and fair AI adoption.
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Published
2025-08-20
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Lainjo, B. (2025). Contemporary Challenges in IT: AI in Healthcare and Education. European Journal of Science, Innovation and Technology, 5(4), 1-24. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/695
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