Trends in teaching and learning about ethics and digital technology with the use of artificial intelligence
DOI:
https://doi.org/10.51896/rilco.v7i26.860Keywords:
ethics, digital technology, artificial intelligenceAbstract
The rapid evolution of digital technology and artificial intelligence (AI) has created new opportunities and challenges in education. Current trends in teaching-learning about ethics and digital technology are explored, highlighting the integration of ethical principles in educational curricula and social responsibility. The methodologies used to incorporate ethics in technological training are addressed and conclusions are presented about the importance of these practices in the preparation of conscious and responsible professionals. This integration of artificial intelligence (AI) into digital technology has generated growing interest in teaching ethics related to these innovations. Current trends in the educational field reflect a renewed focus on incorporating ethical principles into technological curricula. It explores how educational institutions are addressing ethics in the digital age, highlighting the integration of topics such as data privacy and social responsibility. Additionally, emerging methodologies for teaching these concepts are examined and an overview of how these approaches are shaping the future of technology training is presented.
References
Binns, R., Veale, M., Van Kleek, M., Shadbolt, N., & Benford, S. (2018). "‘It’s Not You, It’s Me’: Understanding People’s Reactions to Algorithmic Decisions." Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. doi:10.1145/3173574.3174174.
Jobin, A., Ienca, M., & Vayena, E. (2019). "The AI Ethics Guidelines Global Inventory: A Survey of Ethics Guidelines and Principles for Artificial Intelligence." SSRN Electronic Journal. doi:10.2139/ssrn.3518482.
Lipton, Z. C. (2016). "The Mythos of Model Interpretability." Communications of the ACM, 59(10), 36-43. doi:10.1145/2998436.
O'Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group.
Selbst, A. D., & Barocas, S. (2018). "The Mythical Tradeoff Between Fairness and Accuracy." Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. doi:10.1145/3173574.3173973.
Tufekci, Z. (2015). "Algorithmic Harms Beyond Facebook and Google: Emerging Challenges of Computational Agency." Proceedings of the 2015 Conference on Fairness, Accountability, and Transparency. doi:10.1145/2807588.2809421.
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