Abstract
AbstractThis chapter traces the ethical issues around applying artificial intelligence (AI) in education from the early days of artificial intelligence in education in the 1970s to the current state of this field, including the increasing sophistication of the system interfaces and the rise in data use and misuse. While in the early days most tools were largely learner-facing, now there are tools that are teacher-facing, supporting their management of the classroom, and administrator-facing, assisting in their management of cohorts of students. Learner-facing tools now take into account the affective and motivational aspects of learning as well as the cognitive. The rise of data collection and its associated analytic tools has enabled the development of dashboards for the dynamic management and reflective understanding of learners, teachers, and administrators. Ethical issues hardly figured in the early days of the field but now they loom large. This is because of the legitimate fears that learners’ and teachers’ autonomy will be compromised, that learner data will be collected and potentially misappropriated for other purposes, and that AI will introduce extra biases into educational decisions and increase existing inequity and also because of the scary reputation that AI has in general.
Publisher
Springer Nature Singapore
Reference51 articles.
1. Acikkar, M., & Akay, M. F. (2009). Support vector machines for predicting the admission decision of a candidate to the School of Physical Education and Sports at Cukurova University. Expert Systems with Applications, 36, 7228–7233. https://doi.org/10.1016/j.eswa.2008.09.007
2. Alexandron, G., Yoo, L. Y., Ruipérez-Valiente, J. A., Lee, S., & Pritchard, D. E. (2019). Are MOOC learning analytics results trustworthy? With fake learners, they might not be! International Journal of Artificial Intelligence in Education, 29, 484–506. https://doi.org/10.1007/s40593-019-00192-0
3. Arroyo, I., Woolf, B. P., Burleson, W., Muldner, K., Rai, D., & Tai, M. (2014). A multimedia adaptive tutoring system for mathematics that addresses cognition, metacognition and affect. International Journal of Artificial Intelligence in Education, 24, 387–426.
4. Azevedo, R., & Aleven, V. (Eds.). (2013). International handbook of metacognition and learning technologies. New York: Springer.
5. Baker, T., Smith, L., & Anissa, N. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Retrieved from https://media.nesta.org.uk/documents/Future_of_AI_and_education_v5_WEB.pdf
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