Navigating the Ethical Challenges of Artificial Intelligence in Higher Education: An Analysis of Seven Global AI Ethics Policies
Navigating the Ethical Challenges of Artificial Intelligence in Higher Education: An Analysis of Seven Global AI Ethics Policies

Summary/Abstract: AI use in higher education raises ethical concerns that must be addressed. Biased algorithms pose a significant threat, especially if used in admission or grading processes, as they could have devastating effects on students. Another issue is the displacement of human educators by AI systems, and there are concerns about transparency and accountability as AI becomes more integrated into decision-making processes. This paper examined three AI objectives related higher education: biased algorithms, AI and decision-making, and human displacement. Discourse analysis of seven AI ethics policies was conducted, including those from UNESCO, China, the European Commission, Google, MIT, Sanford HAI, and Carnegie Mellon. The findings indicate that stakeholders must work together to address these challenges and ensure responsible AI deployment in higher education while maximizing its benefits. Fair use and protecting individuals, especially those with vulnerable characteristics, are crucial. Gender bias must be avoided in algorithm development, learning data sets, and AI decision-making. Data collection, labeling, and algorithm documentation must be of the highest quality to ensure traceability and openness. Universities must study the ethical, social, and policy implications of AI to ensure responsible development and deployment. The AI ethics policies stress responsible AI development and deployment, with a focus on transparency and accountability. Making AI systems more transparent and answerable may reduce the adverse effects of displacement. In conclusion, AI must be considered ethically in higher education, and stakeholders must ensure that AI is used responsibly, fairly, and in a way that maximizes its benefits while minimizing its risks.

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