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183: Hot Takes on AI with Amanda Bickerstaff from AI For Education
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In this episode, I am so excited to share this chat with Amanda Bickerstaff who is leading the way in processing AI for Education.
Amanda is the Co-Founder and CEO of AI for Education. A former high school biology teacher and EdTech executive with over 20 years of experience in the education sector, she has a deep understanding of the challenges and opportunities that AI can offer. She is a frequent consultant, speaker, and writer on the topic of AI in education, leading workshops and professional learning across both K12 and Higher Ed. Amanda is committed to helping schools and teachers maximize their potential through the ethical and equitable adoption of AI.
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Challenges & Goals
The main challenge discussed across all conversations was the complexity of adopting new technologies like AI into educational settings. This includes understanding how to use these tools effectively, responsibly, and without causing cognitive offload or dependence on technology. The goal is to develop a curriculum that not only educates students about AI but also encourages them to think critically about its uses and limitations.
Surprising Takeaways
It is surprising to learn that many believe prompt engineering—a key skill currently needed to interact with generative AI—will become unnecessary within 16-18 months due to advancements in technology interfaces. Another unexpected insight was the idea that generative AI could bring the marginal cost of creating to zero, democratizing access to computing.
Emerging Patterns
- The transformative potential of AI in education if used correctly.
- The need for curiosity, critical thinking skills when integrating these new technologies into teaching practices.
- Ethical considerations when implementing AI in education.
- Concerns about potential job losses due to automation and the impact on marginalized communities.
- The rapid proliferation of AI tools in education without a clear understanding of their foundational workings, potential biases, or ethical implications.
Key Moments
1) "This is one of those times where it's very hard to figure out what the question is to ask"
2) "This is power like you can actually create your own chatbot…you do not have to have a computer science degree."
3) "If you can teach us that vaping is bad for us, why can't you teach us that ChatGPT can be bad for us too."
4) "The majority of those, those 80% of those jobs…are going to be degraded or downgraded."
5) "…anyone that tells you that they have a tool that has no hallucinations and no bias and works all the time is not telling you the truth."
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