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AI's Role in K-12 and Higher Education: Takeaways from Zoomtopia 2023

Yesterday, I had the honor of participating on a lively panel discussion at Zoom's annual conference, Zoomtopia. Ted Brodheim, Zoom's Global CIO Advisor for Education, facilitated the chat . The force of irrepressible optimism, Jeremy Schifeling, Marketing Director from Khan Academy, was beside me on the panel.

A few of the main points about AI in education:

► Overcoming Inertia

In addition to the more obvious challenges of infrastructure, data privacy, and technical expertise, there’s a deeper impediment to AI adoption: inertia, anxiety, and not wanting to mess things up.

Pandemic Fatigue doesn't help. One initial step forward is to highlight the trailblazing educators who bring the energy to experiment. As we have in past waves of tech change, these evangelists bring the boldness (and suffer the scars) to pave the path forward.

AI: The Great Equalizer in Education.

Jeremy and I expressed optimism about AI's capacity to level the educational playing field. Imagine an AI-driven instructional assistant, perpetually awake, refining teaching strategies based on real-time feedback from each student. It's revolutionary and democratizing. Early moves in this direction include Khan Academy's Khanmigo and ASU's Primer Global. (thanks to Mark Naufel for his presentation).

Harnessing GenAI for Tailored Educational Outcomes.

We explored the potential of GenAI to devise engaging and pertinent assignments for students. Picture an AI system capable of crafting projects that resonate with each student's passions. Add to this the ability to leverage collaboration tools to engender a spirit of teamwork among students.

For the student struggling to justify their courses: Within seconds, ChatGPT can articulate the relevance of calculus and algebra to a student passionate about surfing and board design. Try it. Copy into ChatGPT, "I want to design surfboards; why should I study math?"

Predictive Analytics: A Double-Edged Sword

While data is an invaluable resource, navigating its use is crucial, especially concerning students. The nature of AI models means that the more diverse the data input, the richer and sometimes more counter-intuitive the insights.

However, discerning what data is pertinent can be elusive. Factors outside the classroom—such as sleep patterns, diet, home conditions, recreational screen time, household stressors, and physical activity—might significantly sway academic performance.

Attribution for AI Generated Content.

One of the educators asked about the tricky issue of attribution for AI-generated content. Afterward, we had a fascinating chat about what a taxonomy for describing the role of AI might look like. (let me know if you’re interested in that topic.)

Many thanks to Johann Zimmern and Matt Mandrgoc for creating such a rewarding experience.

(the graphic is what ChatGPT made from the text in the post).

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