One of the newest threats to the sanctity of learning is artificial intelligence (AI), according to many professionals in the education community (and echoed by voices from non-related fields). The growing fear is that students will just use AI to instantly do every learning task, and they will never develop the ability to think for themselves. While this concern has some merit, those who voice these fears overlook the opportunity to use AI to strengthen the skill in question and how to navigate and effectively use the tool itself. AI is now part of society’s technological toolbelt, and expecting a student to move through life without ever using it or needing it would be a case of intentional ignorance on the instructor's part.
Instead, students should have
learning tasks that adapt to include and build on AI. For example, in the course I recently
completed (“Emerging Trends of Technology in Learning Design”), I was asked to
utilize AI to construct a narrative story, and then use another AI tool to craft
images related to the story that fit the scenes, and finally to use a voice
generator to automatically narrate the final product. The entire assignment was done with AI…and
it still required hours of work because I, the human, had to work to analyze
and connect the results together in a way that made sense. By the way, if you want to see the final
result, here it is:
This assignment, along with several
others that motivated me to draw on AI in many ways, helped me feel that
I was using the new technology effectively.
Unfortunately, it also brought on a bit of a guilt trip, because some new research suggests that the AI we are all using is being
powered by servers that are harming the environment(UNEP, 2024). I am the type of person who does not use
straws or grocery bags because I worry about the long-lasting harm that consumer
habits have on the planet, so finding out that such a useful tool can be doing
just as much—or more—damage is disheartening. I find myself currently on the
fence between halting the use of this tool and continuing to use it, albeit in
measured amounts, while I await more concrete data that can point me toward a
definite course of action.
Using AI
during this course provided me with a great opportunity to revisit my original
conclusions about how and when I adopt emerging technologies. I agree with the initial (unfavorable)
response from my instructor in regard to my previous assumption about my status
on the diffusion of innovation curve.
In my
initial evaluation of Rogers’ Diffusion of Innovations Theory (Rogers, 1983), I
implied that I felt I was an “Early Adopter” because I don’t necessarily create
original technology ideas but I don’t wait for the technology to become popular
before I start using it, either (Eve, 2024).
My instructor reasoned that this definition actually sounds more in line
with “Early Majority,” and while I hesitated to agree with her at first, I’ve
come to realize that is very accurate during this course. When re-analyzing the curve (shown below), “Early
Adopters” seem like they are very different from the innovators and thus are
using technology that is already tested and ready for widespread use—but actually,
these are probably more like the Beta testers.
These are the ones who discover all of the bugs, the glitches, and the
things that might accidentally, I don’t know, shut down the local power
grid. It’s not until after they’ve been
using the technology for a bit that the rest of the population starts to see
it, and that’s where I fit.
Although I would like to say
that I am an “Early Adopter” because it makes me feel like I’m not dragging my
heels and holding up progress…the truth is that I don’t have a lot of time to
do trial-and-error with new technology.
I am currently juggling more projects and obligations than I probably
should if I were honest, and trying to fit in “Product Tester” wouldn’t work
very well. In fact, I turned down an opportunity
to be at the forefront of a brand new classroom AI app recently because I didn’t
have time to devote to it! So, yes I am
comfortable with “Early Majority” for the time being—but if I start falling
behind and end up in “Late Majority” or even worse, “Laggard”, I hope somebody
lets me know!
References
Eve, H. (2024, October 27).
Necessity Is... Blogger. December 4, 2024,
https://heathereveldt.blogspot.com/2024/10/necessity-is.html
Rogers, Everett M. (1983). Diffusion
of innovations (3rd ed.). New York: Free Press of Glencoe. ISBN 9780029266502.
UNEP. (2024). AI has an
environmental problem. here’s what the world can do about that.
https://www.unep.org/news-and-stories/story/ai-has-environmental-problem-heres-what-world-can-do-about
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