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Generative AI Beyond the Bubble: Looking Ahead to the 24/25 Academic Year

In this episode of Generative Dialogues, Mark Carrigan and Helen Beetham reflect on the past year of discussing generative AI and look ahead to future conversations. Key topics include:

  1. Shifting perspectives: Both hosts discuss how their views on generative AI have evolved over the course of their conversations, moving from initial techno-optimism to a more nuanced and critical stance.
  2. The “AI bubble”: Mark and Helen explore the idea of an “AI bubble” and consider the implications of its potential “bursting” or gradual unwinding for practice and policy in higher education.
  3. Disciplinary differences: The conversation touches on how different academic disciplines approach and utilize generative AI, highlighting the importance of considering disciplinary contexts when discussing AI’s impact on education.
  4. Theoretical frameworks: The hosts discuss plans to explore various theoretical approaches to understanding AI, including posthumanism, philosophy of technology, and sociology of knowledge.
  5. The role of theory in digital education: Mark raises questions about how theory is used in digital education research and suggests exploring this topic further in future episodes.
  6. Practical applications: The conversation touches on the importance of balancing theoretical discussions with practical examples, including teaching prompting techniques and examining student use of AI tools.
  7. Future plans: Mark and Helen outline plans for upcoming episodes, including theory-focused discussions and interviews with practitioners in the digital education space.
  8. Parallels with social media: The hosts draw comparisons between the current AI discourse and past conversations about social media in higher education, suggesting that AI might follow a similar trajectory of integration and normalization.

Throughout the discussion, Mark and Helen emphasize the need for a balanced approach to generative AI in education, combining critical analysis with practical exploration. They express cautious optimism about the potential for more grounded and nuanced conversations about AI as the initial hype subsides.

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