“Cyborg writing must not be about the Fall, the imagination of a once-upon-a-time wholeness before language, before writing, before Man. Cyborg writing is about the power to survive, not on the basis of original innocence, but on the basis of seizing the tools to mark the world that marked them as other.”
~
Donna Haraway’s “A Cyborg Manifesto” challenges traditional notions of identity and boundaries between humans and machines. It invites us to view ourselves as “cyborgs” – entities that merge human and machine elements. In the context of generative AI in education, Haraway’s perspective might encourage us to explore the symbiotic relationship between humans and AI technologies. Rather than fearing AI as a replacement for teachers, we can envision a future where educational cyborgs, consisting of humans and AI working together, empower learners to thrive in an interconnected world.
While this may seem an overly optimistic viewpoint, it is clear that generative AI presents numerous opportunities and, at risk of sounding cliche, might even help to transform education. Generative AI has the potential to support personalized learning, assist with content creation, provide language support, and, even foster creativity and critical thinking.
Of course, if we are to harness the full potential of generative AI in education, it is essential to address the challenges of ethical use, data privacy, teacher-student relationships, and assist educators in developing essential AI competencies so they can effectively utilize AI, design assessments and assignments and guide their students.
Perhaps, by embracing generative AI responsibly and ethically, we can help to create a future where education is more inclusive, engaging, and tailored to the needs of every learner.
I recently had the opportunity to facilitate a panel discussion on this topic at UBC. Below you will find resources, including a recording and links shared by presenters as they responded to our prompt:
What is the biggest opportunity and the biggest challenge you’ve found with respect to Generative AI’s, such as Chat GPT, in your context?
- Reid Patterson, BA Cognitive Systems: Professional Development Educator, UBC Geering Up
- Emma Gray, Product Manager, Microsoft Education
- Wendy Traas, Education Research Librarian, UBC Library
- Danny Leeming, UBC WKTEP Instructor, Classroom Teacher, Nelson, BC
A concise resource describing ‘what is AI’ and what are some potential implications on education, shared by Reid, Geering Up
A few links shared by presenters:
- One Useful Thing: The Homework Apocalypse by Ethan Mollick
- What is Microsoft Edu doing with Generative AI?
- One-hour Generative AI for Educators introductory course
- Clickable demos: Interactive Demos for Education | Microsoft Education
- Short courses on each Learning Accelerator tool: Learning Accelerators: A new category of learning tools included in Microsoft 365 for Education | Microsoft Learn
Some Tools mentioned:
Further Reading:
- Davis, V.L. (2023). WCET Primer for Higher Education: General Brief on Generative AI. WCET
- Academic Integrity and AI: thanks to the team in LDDI, Learning Design Digital Innovation, at UBC for their comprehensive work and emerging resource collection)
Please continue to watch this blog for future posts about Artificial Intelligence as I work with colleagues across campus and in K12 to learn more about this emerging edtech issue.
My first post on this topic Winter 2022: Preliminary Thoughts & Resources
NOTE:
I have recently begun some research into the environmental impacts we need to consider (and address) as part of an essential global response to climate change (more on this in another post!). A starting point is this article in Scientific American, A Computer Scientist Breaks down Generative AIs Hefty Carbon Footprint.
Reference:
Haraway, D. (1991) A Cyborg Manifesto: Science, Technology, and Socialist-Femi- nism in the Late Twentieth Century. Simians, Cyborgs and Women: The Reinvention of Nature, Routledge, New York, 149-181.
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