Using AI to Augment Reading
Advancements in large language models (LLMs) and large multimodal models (LMMs) have granted generative AI tools the ability to process larger amounts of input text and interact with users based on the AI tool’s “understanding” of that text (or texts). Put simply, generative AI tools are able to “read” more successfully (though imperfectly) and engage with students in making sense of texts that are assigned for a course, identified as part of a literature search, encountered during casual perusing, etc.
This session will introduce the affordances and constraints of using AI to engage with readings for different purposes and demonstrate how this works with different AI tools, including strategic ways of engaging with AI for optimal output. Additionally, we will explore how instructors can integrate AI-assisted reading in students’ learning while fostering the development of critical thinking and literacies, identifying and foregrounding the shortcomings of AI, and considering when it may not be appropriate or productive for learning.
Facilitators: