The main goal of this study was to analyze and consolidate existing research on ethical implications of artificial intelligence in education, focusing on identifying key concerns, evaluating implementation frameworks, and determining research gaps.
Methods: The study conducted a comprehensive literature review analyzing multiple research papers and publications. It employed comparative analysis of relevant literature, evaluated existing AI tools in education, and examined ethical frameworks through systematic review of academic papers, policies, and guidelines.
Key Findings:
- Power dynamics in algorithm design can significantly influence young minds
- Privacy concerns and data security remain major challenges
- Academic integrity issues arise with AI accessibility
- Bias in AI systems can perpetuate educational inequities
- Teacher-student relationships are significantly impacted by AI integration
- Cost and accessibility create potential digital divides
Implications: The findings emphasize the need for transparent, accountable AI implementation in education while highlighting the importance of ethical training for educators. This contributes to developing better frameworks for AI integration in educational settings.
Limitations: The study relies solely on literature review without empirical research, lacks practical implementation data, and doesn't address varying educational contexts across different regions or institutional types.
Future Directions: Future research should explore student learning outcomes, teaching methods impact, training strategies, classroom dynamics, and development of comprehensive ethical frameworks. Additional studies needed on long-term effects of AI integration in education.
Title and Authors: "Ethical Implications of Artificial Intelligence in Education" by Janhavi Walvekar and Dr. Ameet Chate
Published on: December 2023 Published by: ANUSANDHANA - Journal of Science, Engineering and Management