Learning Objectives
At the end of this activity, students will be able to:
- Develop an understanding of the nature of generative AI and relates issues that have wider implications.
- Think critically about their understanding of generative AI.
Background
“[M]etaphorical projection is a mechanism through which a given culture perpetuates and reproduces itself in a steadily growing system of concepts.” (Sfard, 1998)
Education is a field full of metaphors. The Construction Metaphor situates learning as a process of building knowledge of the external world. Gardening is a metaphor often used for illustrating child-centred principles about teaching and children (Mintz, 2018). The ’transmission’ metaphor is perhaps one of the oldest, with teaching being considered ‘transmission,’ ‘facilitation,’ or ‘catalyst’ (Badley & Hollabaugh, 2012). Our metaphors also evolve and change. For centuries, we conceptualized “mind metaphorically in terms of a container image schema defining a space that is inside the body and separate from it” (Marcinkowska-Rosół & Sellmer, 2021). However nowadays, we no longer see mind as an empty vessel and we argue that teachers cannot pour knowledge into students’ heads.
Much like education, the field of computer science is rich with metaphors and the discipline of artificial intelligence is no different (Murray et. al.,2022). The term “artificial intelligence” itself is coined after human cognition and natural intelligence of human mind. Hence it is not by accident that the process of training the machines is called learning, and the algorithms responsible for the training are named neural networks. Likewise, scholars and researchers who are actively assessing the benefits and risks associated with the emerging AI tools and technologies employ metaphors to shape our understanding of this rapidly evolving field.
Amidst the hype and excitement of the transformative potential of AI, as critical producers and consumers of digital literacies, we must cultivate a holistic and rich understanding of the ethical concerns posed by these technologies. This understanding need to extend beyond the realm of academia, and encompass the broader societal and global implications. With this goal in mind, as a starting point, we take a dive into a few metaphors that can help us grasp the nature and risks of AI technologies.
We invite you to take a moment to reflect on these metaphors as a way to build critical understanding of the field of AI. Consider how these metaphors help us understand the tensions that are arising as a result of our engagement and relationship with these technologies and how they can empower us to become ethical, mindful and responsible digital citizens.
Your Turn
Share the metaphors you have come across. Is there a metaphor you would like us to include? Is there a new metaphor you would like to propose?
References
Badley, K., & Hollabaugh, J. (2012). Metaphors for teaching and learning. Metaphors we teach by: How metaphors shape what we do in the classroom, 52-67.
Marcinkowska-Rosół, M., & Sellmer, S. (2021). The mind as container: a study of a metaphor in Homer and Hesiod with a parallel analysis of the Sanskrit epics. Mnemosyne, 75(6), 873-897.
Murray-Rust, D., Nicenboim, I., & Lockton, D. (2022). Metaphors for designers working with AI.
Mintz, A. I. (2018). The present, past, and future of the gardening metaphor in education. Oxford Review of Education, 44(4), 414-424.
Sfard, A. (1998). On two metaphors for learning and the dangers of choosing just one. Educational researcher, 27(2), 4-13.””