Presented by: Mary Loftus
AI is everywhere and we can’t ignore it in our classrooms. But how do we and our students engage critically with AI, rather than be passive consumers of AI platforms? How can we work with our students to enable our collective subjectification, and their emergence as ‘unique beings’ (Biesta 2015).
UNESCO has called for a global response in education to the emergence of AI (Miao et al., 2021) that features::
- Learning with AI – the application of AI within classrooms
- Learning about AI – teaching its techniques
- Learning for human/AI collaboration and preparing citizens to live in the AI era
We are working on a pedagogy which is designed to help students understand the inner workings of AI and build a critical consciousness around its use, while simultaneously building their own critical thinking skills.
We use Bayesian Networks and Causal Diagrams in the classroom to understand human problems as seen through the lenses of AI systems and data. We marry this approach with Brookfield’s framework for teaching critical thinking (2011), which in turn is influenced strongly by Freirean principles of praxis (Freire, 1970).
We also draw on previous research in the domain of Cognitive Psychology, which show that these approaches can reflect our thinking processes and enable learning through modelling, in even really young children, and in a relational context that also challenges teachers to think metacognitively:
“The central idea behind the Bayesian pedagogical models is that children not only model the causal structure of the world, they also model the mind of the person teaching them about the world.” Gopnik (2012)