The whole world of Artificial Intelligence is beyond insane. Every single day, heck every single hour there is an update or something that is worth noting and learning. For a bit of July I hit a hard pause burning myself out thinking I needed to be on top of each new detail. I burned myself out on a lot of things so I hit the pause, took my son fishing in Canada, unplugged, and recalibrated with all the changes life has brought into my life this summer.

And what I want to do here and possibly in future aspects of sharing my learning is to help you not feel this type of way. As I sort my readings, research, and just general thinking around education and AI I am going to draft out a long write up of what I am reading, learning, processing, and condense things into a playlist of sorts for you to be able to navigate and filter easier for your own learning.

I hope it helps because there is simply too much to process and life is too short stressing about things that perhaps don’t need stressing over.

Enjoy my friends as I hope to provide more of these as I get back to writing and processing again.

Key Resources

Office of Educational Technology: Artificial Intelligence and the Future of Teaching and Learning** [1]
Developing Our Shared Compass: A Guide for Conversations on AI and Values by John Nash** [2]

This guide is designed to help you and your school community have productive conversations about AI and its impact on education. By reflecting on important questions and values, you can develop guidelines for responsible and ethical AI adoption. Here are three example questions to get you started:

– How can we ensure that AI is used in a way that aligns with our school’s values and mission?

– What are some potential risks and benefits of adopting AI in education, and how can we mitigate those risks?

– How can we involve students and other stakeholders in discussions about AI, and ensure that their voices are heard?

Research Papers

Paper Title: A comprehensive AI policy education framework for university teaching and learning** [3]

Key Findings:

The study on AI education policy in Hong Kong universities found that there is a need for a comprehensive AI education policy framework that addresses the multifaceted implications of AI integration in university teaching and learning[3]. The study proposes an AI Ecological Education Policy Framework organized into three dimensions: Pedagogical, Governance, and Operational. The Pedagogical dimension focuses on using AI to improve teaching and learning outcomes, while the Governance dimension tackles issues related to privacy, security, and accountability. The Operational dimension addresses matters concerning infrastructure and training[3]. The study also found that there is a need for universities to provide students and teachers with training in AI to ensure that graduates are equipped to contribute to the development of AI and to navigate the ethical, social, and economic issues that are likely to arise as AI becomes more widespread[3].

Five Key Ideas:

Develop an AI education policy for universities that teaches students about the ethical considerations surrounding AI, such as bias and fairness, as well as the potential consequences of using AI in academic contexts[3].
Encourage the development of local innovations in AI for education to ensure that it meets the specific needs of their communities[8].
Test and evaluate the use of AI in education through pilot projects to build an evidence base for its effectiveness[8].
Prepare students for the AI-driven workplace by teaching them how to use AI responsibly, ethically, and effectively[17].
Encourage students to use AI as a complementary tool to support learning rather than relying on them as a substitute for traditional teaching methods[17].

Questions to Consider:

– What are the potential benefits and risks associated with AI in academic settings, and how can we ensure that AI is used responsibly and ethically? [23]

– How can we develop an AI education policy framework that addresses the multifaceted implications of AI integration in university teaching and learning? [23]

– How can we ensure that students and teachers are equipped with the necessary skills and knowledge to use AI effectively and responsibly? [1]

– How can we ensure that AI is used to complement traditional teaching methods rather than replacing them? [13]

– How can we evaluate the effectiveness of AI in education through pilot projects and build an evidence base for its use? [23]

– How can we ensure that AI is accessible to all students, regardless of their socioeconomic background? [1]

– How can we ensure that AI is used in a way that respects privacy, security, and accountability?

General Resources for Further Learning and Reading

Getting Smart: AI In Education** [4]
Classroom Policies for AI Generative Tools** – all university level, but examples that could help K-12 schools to see how the university levels are trying to process the emergence of AI[5].
Instead of Banning AI, Schools Should Use It To Enhance Learning** [9]
AI and the Next Digital Divide in Education** [5]
AI Is Helping Us With Our Instructional Practice. Here’s How** [14]

I hope this blog post helps you navigate the world of AI in education more easily. Remember, life is too short to stress about things that perhaps don’t need stressing over. Enjoy learning and exploring the potential of AI in your educational practice!

Stay Awesome,

A-A-Ron

Citations:

Dislaimer: I used Perplexity to help me organize citations for this write up of my thinking and learning. The result was interesting as my write-up contained 7 hyperlinks to what I read and processed. However,the citations as you see below stand at 38. I did not read all 38. I decided to go ahead and link them all because it did give me new things to read, process, and people to follow so I thought perhaps it might help you. But wanted to be transparent that I did not read all these(only the links above) and used Perplexity to help organize and this is the result.

[1] https://tech.ed.gov/ai-future-of-teaching-and-learning/

[2] https://maven.com/p/92338f

[3] https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-023-00408-3

[4] https://www.gettingsmart.com/whitepaper/artificial-intelligence/

[5] https://www.brookings.edu/articles/ai-and-the-next-digital-divide-in-education/

[6] https://www2.ed.gov/documents/ai-report/ai-report.pdf

[7] https://www.linkedin.com/pulse/introducing-robocribbing-term-distinguish-unethical-ai-john-nash

[8] https://arxiv.org/abs/2305.00280

[9] https://www.gettingsmart.com/2022/12/16/education-is-about-to-radically-change-ai-for-the-masses/

[10] https://www.brookings.edu/articles/ai-is-coming-to-schools-and-if-were-not-careful-so-will-its-biases/

[11] https://content.acsa.org/artificial-intelligence-and-the-future-of-teaching-and-learning/

[12] https://www.linkedin.com/posts/andrewyng_had-an-insightful-conversation-with-geoff-activity-7073688821803978752-DO9h