SAIL: Change vs Becoming, AI Lecture Series
Welcome to Sensemaking, AI, and Learning (SAIL) - a focus on how AI impacts teaching, learning, and education.
Many years ago, I started doing talks on the impact, at that time, of blogs on education. Then wikis. Then podcasts. Then flickr. All of which became web 2.0 and eventually, social media. These talks were as much about explaining the current technology as they were about getting to application, impact, and implications. Things are different now. We are all aware of major developments, almost immediately, due to being tightly connected to one another. As a result, novelty flows rapidly through digital networks. Generative AI is an example: in a span of a few months, everyone seems at least partially informed.
This simple observation hides an important reality: we need to focus less on the change and more on the becoming. The ease of tracking new developments in technology and society requires that we advance from trying to describe what's happening and focus instead on what we (in this case, the education sector) is becoming.
With colleagues Pete Smith (UTA) and Lin Lipsmeyer (SMU) we have pulled together a year long lecture series to do address the challenge of surface level awareness of trends vs deeper focus of implications. The AI and education sensemaking lecture series is now open for registration (free). The intent is deep, sustained dialogue - communal sensemaking.
Education and AI
Edtech sector is going crazy for AI (via OLDaily): "the frenzy is unprecedented: this is bigger than the excitement at the launch of the i-Phone." In education, I've seen only limited response from university leadership recognizing how consequential this point in time is (I've met exactly two leaders who I'm confident "get it").
ChatGPT and AI in Education This has received a fair bit of attention online, offering a short introduction to AI and related challenges and opportunities. There is nothing new here, but it does pull together a broad series of conversations.
We all contributed to AI When people first start playing with ChatGPT, the experience is one of "oh wow, this is pretty coherent". After spending more time, it becomes clear that the tool is actually somewhat boring in output...which is sensible since it's trained on the aggregate writing that we've all done online. It seems sensible because we wrote it.
OECD AI Principles A good list. Education systems need to plan for and adopt variations of this (or one of the many other principle lists available online).
AI Advancements
AI Research Non-Profit announced. OpenAI is not excessively open. A small group of companies and organizations have decided to go the open route, but details are still scarce, but will be an extension of EleutherAI
A-Z terms to keep up with AI Another glossary of terms related to AI.
Ecosystem graphs If you're still trying to wrap your head around foundation models, the underpinning of our current AI hype, this is a good resource. Ecosystem graphs are defined as "as a centralized knowledge graph for documenting the foundation model ecosystem"
AI Impact
Generative AI at Work This is worth considering in more detail. A mostly positive assessment of AI, providing opportunities to employees (especially those with less skills) but overall, increasing productivity. Caveats are offered in the conclusion that the paper doesn't account for longer term impact on skill demand. Pairs well with An Early Look at the Labor Market Impact Potential of Large Language Models (shared previously) that has a more ominous assessment of impact on work.
Why I'm not worried about AI causing mass unemployment "Many technologists worry that AI will get so powerful that it will be capable of performing most of the jobs currently performed by humans, leading to mass unemployment. I don’t buy it."
The ethics of AI are going to be enormously challenges. "Michael Schumacher's family are planning legal action.over an "interview" with the seven-time Formula One champion that was generated by artificial intelligence."