ETHICAL IMPLICATIONS OF USING ARTIFICIAL INTELLIGENCE IN EDUCATION
DOI:
https://doi.org/10.5281/zenodo.14860703Keywords:
artificial intelligence, education, algorithmic bias, algorithmic transparency, ethicsAbstract
Ethical Implications of Using Artificial Intelligence in Education.
The paper discusses the impact of artificial intelligence (AI) use in education. After presenting the concept of artificial intelligence, the paper details the numerous benefits of integrating AI into educational practices. The ability of computer systems to simulate human intelligence opens up significant opportunities for personalized learning, enhances the efficiency of instructors, provides rapid feedback to students, and much more. Using AI to perform various educational activities, whether in teaching or administration, involves employing algorithms trained on large datasets to automate different tasks. These tasks include grading, providing personalized feedback, predicting student behavior, selecting candidates in the admission process, and others. Despite their utility, these algorithms are often complex and not fully understood by the users, which presents certain challenges. In light of these challenges, the paper also addresses several ethical issues associated with AI in education, such as algorithmic transparency, privacy protection, algorithmic bias, and the digital divide. Various institutions and international organizations have responded to these concerns by developing guidelines to protect the beneficiaries of the educational system. However, implementing these guidelines in practical and effective ways remains a significant challenge. Moreover, the paper highlights the importance of continuous dialogue between educators, policymakers, and technologists to ensure that AI in education is used responsibly and ethically. It underscores the need for ongoing research and development to improve the transparency and fairness of AI systems and to bridge the digital gaps that may exacerbate educational inequalities.
References
• AFZAL, A., Khan, S., Daud, S., Ahmad, Z., & Butt, A., “Addressing the Digital Divide: Access and Use of Technology in Education”, in Journal of Social Sciences Review, 3(2)/2023, pp. 883-895. https://doi.org/10.54183/jssr.v3i2.326
• ALEVEN, V., Rowe, J., Huang, Y., Mitrovic, A., “Domain modeling for AIED systems with connections to modeling student knowledge: a review”, in B du Boulay, A. Mitrovic & K. Yacef (Eds.), Handbook of Artificial Intelligence in Education, Edward Elgar Publishing, 2023, pp.127-169.
• DU BOULAY, B., Mitrovic, A. & Yacef, K. (Eds.), Handbook of Artificial Intelligence in Education. Edward Elgar Publishing, 2023.
• BROOKS, C., Kovanovic, V.& Nguyen, Q., “Predictive modeling of students success”, in B du Boulay, A. Mitrovic & K. Yacef (Eds.), Handbook of Artificial Intelligence in Education, Edward Elgar Publishing, 2023, pp. 350-369.
• CASPARI-SADEGHI, S., “Learning assessment in the age of big data: Learning analytics in higer education”, in Cogent Education, 10(1)/2023, https://doi.org/10.1080/2331186X.2022.2162697
• CLOW, Doug, “An overview of learning analytics”, in Teaching in Higher Education, 18(6)/2013, pp. 683–695.
• European Commission: Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for Educators, Publications Office of the European Union. 2022, available at https://data.europa.eu/doi/10.2766/153756 (Accessed May 2024).
• European Parliament: Artificial Intelligence Act: MEPs adopt landmark law. Press releases. 13.03.2024, available at https://www.europarl.europa.eu/news/en/press-room/20240308IPR19015/artificial-intelligence-act-meps-adopt-landmark-law (accessed April 2024).
• KIZILCEC, Rene, Lee, Hansol, “Algorithmic fairness in education”, in Holmes, Wayne, Porayska-Pompsta Kaska, The Ethics of Artificial Intelligence in Education, Routledge, 2022, pp.174-202.
• OECD: Understanding the Digital Divide, OECD Digital Economy Papers, No 49, 2001, available at https://doi.org/10.1787/20716826, (Accessed April 2024).
• OECD: OECD Digital Education Outlook 2023: Towards an Effective Digital Education Ecosystem, OECD Publishing, Paris, available at https://doi.org/10.1787/c74f03de-en, (Accessed June 2024).
• PEICHEN, Lexie, Mar 1, 2024, Internet Usage Statistics 2024, available at https://www.forbes.com/home-improvement/internet/internet-statistics/, (Accessed June 2024).
• POZDNIAKOV, S., Martinez-Maldonado, R., Singh, S., Khosravi, H. & Gasevc, D., “Using learning analytics to support teachers”, in B du Boulay, A. Mitrovic & K. Yacef (Eds.), Handbook of Artificial Intelligence in Education, Edward Elgar Publishing, 2023, pp. 322-349.
• UNESCO: Recommendation on the Ethics of Artificial Intelligence, available at https://unesdoc.unesco.org/ark:/48223/pf0000381137/PDF/381137eng.pdf.multi (Accessed April 2024).
• YU, S., Lu, Y., An Introduction to Artificial Intelligence in Education, Singapore, Springer, 2021.