AI and Education: Opportunities and Challenges

The podcast discusses an article about the need to adapt education in response to the integration of artificial intelligence (AI). The authors define AI as a black box that makes untraceable judgments. They emphasize the importance of meaningful interactions with AI systems and suggest developing critical understanding and digital literacy towards AI judgments. The article focuses on designing tasks to develop evaluative judgment and understanding of AI's social and contextual aspects. It provides a practical framework for educators to prepare students for AI's impact. However, AI has limitations, such as biases and misleading information. Overall, the article offers insights into the role of AI in education and provides guidance for educators. Hello everyone, welcome to our podcast, AI and Education, Opportunities and Challenges. Today we are going to discuss the article, Learning to Work with the Black Box, Pedagogy for Work with Artificial Intelligence by Margaret Bellman and Rola Adjavi. This article by Margaret Bellman and Rola Adjavi, published in the British Journal of Educational Technology, discusses the necessity of adapting higher education pedagogy in response to the increasing integration of artificial intelligence in society. The authors define AI from a relational epistemology perspective, describing it as a computational artifact that makes untraceable judgments in specific interactions, thus functioning as a black box. The focus is on developing pedagogies for an AI-mediated world that enables students to work with a pig of partial and ambiguous information. This approach considers AI as socially bounded and understood within the context of its use. Adding to the stellar point, the article also places special emphasis on the importance of meaningful interactions with AI systems. The authors suggest we develop a critical understanding with digital literacy towards AI judgments and discuss the role of emotion, like trust and debate in interactions with AI. Moreover, the article focuses to two essentials, how tasks can be designed to develop students' evaluative judgment and understanding of GEI, with a particular focus on the social and contextual aspects of AI usage in academic settings. A major strength of this article is that it provides a practical framework to help educators prepare students for awards permitted by AI. By emphasizing relational understanding and critical engagement with technology, it offers a clear direction for developing students' capabilities in an ever-changing technological landscape, particularly in the understanding of quality standards in systems and the critical evolution of AI judgment equips students with skills for effectively using AI in their future work and life. However, as mentioned in the article, the artificial intelligence has its limitations. Students tend to take the cognition which they acquire through AI for granted, instead of view it critically. Quality standards of AI systems need assessment. On the one hand, it may have some blind spots of knowledge which may not provide effective help to the learning process. Sometimes it can be misleading to learners. On the other hand, according to Work, an AI artifact may embed and promote unacceptable discrimination on the basis of race or gender or disability, because it is built on a particular knowledge system that holds these biases. If the learners cannot understand those biases existing in the society, they cannot adapt to the bias of AI. In summary, the article offers profound insights into the role of AI in education. Despite some challenges in implementation, this article provides valuable guidance for educators exploring this field. That's all for today. Thanks for your listening.