Machine Learning Reminds Us Of What Human Learning Really Looks Like
“The right way to talk to strangers is with caution and humility.”
― Malcolm Gladwell, Talking to Strangers: What We Should Know About the People We Don’t Know, 2019.
If you’ve had a chance to play with AI yet, you’ll have noticed how specific one must be with the prompt craft.
And, still, you’ll likely type in your prompt and still the AI won’t churn out exactly what you’re after.
Ever felt like that’s what happens with the young people in your classroom? Or perhaps that’s how you’ve felt in the classroom.
“Because we do not know how to talk to strangers, what do we do when things go awry with strangers? We blame the stranger.”
― Malcolm Gladwell, Talking to Strangers: What We Should Know About the People We Don’t Know, 2019.
When the correct image doesn’t show up from my well-crafted prompt in Midjourney — who do I blame? The tech, obviously.
And, what do we do when things go awry from our well-crafted lessons in the classroom? We blame the students.
“You weren’t listening properly.”
“I’ve already said that twice.”
“Please pay more attention.”
Perhaps it would be better to, like Gladwell suggests in his book, “talk with caution and humility,” in our classrooms.
I like to think I’m not big into explicit teaching. But, sometimes it’s necessary. So, perhaps, when we explicitly teach content and/or skills, we might expect that what we say may not be interpreted accurately… just like when we put a prompt into AI.
Knowing this, how might we “talk with caution and humility” to both AI and to humans?
- Learn through bite-sized trials.
When we explicitly teach, let it be in bite-sized chunks with which we might check the effectiveness of the message.
With AI, we might cautiously construct a prompt, then get feedback (through the image or response) and then adjust the prompt and try again. In Midjourney, if I’m after something specific, I find the ‘seed’ of the image to ensure that I’m getting something specific. The seed is “… the master key” of an image.
In the classroom, we can set a limit on how long we will speak. A useful tool is to find the ‘seed’ of our message — what do I really want students to know? When we do this, we’ll find that our message is quite short.
2. Ask, don’t tell. And, have students ask.
We need to spend time knowing our students and finding out what they know. By assuming that our students are more than capable and that they may know more about something than we thought (or that we do), we demonstrate humility and caution.
According to John Hattie (2015), students need to be asking more questions than the teacher for effective learning to take place. This is about proceeding with humility.
Teachers who use higher-level questioning will produce students who engage in higher-order questioning; they come to predict and internalize the language they hear every day (Renton, 2020).
With AI, many models, such as Chat-GPT, allow us to ask questions and even for the model to ask us questions.
3. Get feedback and pivot.
When we are using AI, it’s easy to assume every prompt is a prototype. Each time I put a prompt in, I assume that I will need to adjust. And, yet, in the classroom, we have a different attitude.
Rather, in a position of humility and caution, we benefit from having students give us feedback about our teaching (and making required adjustments).
Sometimes, like with AI, it’s worth just getting in there and “doing” straight away, rather than “front-loading”. We can make adjustments on the ground.
“First act and then think…We discover the possibilities by doing, by trying new activities, building new networks, finding new role models.” We learn who we are in practice, not in theory.”
― David Epstein, Range: Why Generalists Triumph in a Specialized World
In closing, let’s remember that learning, like AI prompting, is something to be crafted and adjusted with humility and caution.
To be able to meet the uncertain challenges of the contemporary world, we need to … expand our repertoire of ways of learning and knowing to reclaim the full gamut of cognitive possibilities.”
― Guy Claxton, Hare Brain, Tortoise Mind: How Intelligence Increases When You Think Less, 1997.
