“To extend our abilities to think and perceive in new ways, and to translate those into tools that enable others to think and perceive in new ways, is probably the essential part of the human story.” – Howard Rheingold and Petar Jandric, 2015
I can build things I only dreamt of even a few months ago. This is both liberating and a bit intimidating because it opens whole new questions about what is possible.
If you look at technology as an evolution towards simplicity, we may have crossed a milestone in recent months or years. It used to be that coding was confined to a relatively exclusive elite. You had to have a certain kind of mindset for it, and then acquire the skills.
We need to consider how AI fits into the broader technological and societal picture. I don’t tend to believe in revolutions, either as a political scientist or as a technologist. They don’t really fit the patterns of human behavior. People are naturally conservative unless they see no other way out and change.
The same thing is true with technology adoption. There are a few who delight in doing things no one else can do, but most are more interested in getting through their workload.
This doesn’t mean they don’t have ideas or needs that technology (or writing) can express for them. It is our responsibility to continuously lower barriers to access those technologies.
Most people fear technology because it wastes their time and takes tasks out of their control. Yet this fear has never been about a lack of imagination. It’s about the barriers between them and their ideas. AI, like the PC in the 1970s, represents a massive lowering of those barriers.
For decades, education has focused on technical skills rather than logical ones, because the technology itself was hard to master. But AI changes that. We don’t think about “technical skills” when we pick up an iPhone, and soon we won’t think about them when we build with AI either.
The true revolution with AI will come with making. There are so many projects that I have thought of over the years that I have discarded because I don’t have the technical skills to code them properly. No matter how much I wanted these tools, they required prohibitive opportunity costs to realize.
A few weeks ago, I was on the T is for Training podcast where I’m a regular panelist. We were discussing the use of escape rooms for teaching and training with Laura Gehringer and Madeline Shellgren.
It suddenly struck me that I could generate escape room scenarios for my classes using a generative AI Chatbot. This is not just about games. The escape room example showed me how AI doesn’t just speed up existing workflows. It makes previously impossible things practical. That shift in feasibility is the real revolution.
I have built games for learning before. The challenge in constructing games in an educational setting is that to do it well is incredibly time-consuming. Most teachers don’t have time for that.
You also want to tailor the game around your instructional goals and style as much as possible. Therefore, sharing games across multiple subjects or pedagogical styles doesn’t always scale well.
I have been writing over the last couple of months about how AI can be used to significantly speed up logistical tasks in my teaching and classroom management. I had not thought of using it to construct games until my conversation with Laura and Madeline.
The next day, I was speaking to a fellow professor at a startup meeting, and we started talking about escape rooms. He brought up the idea of coding a game that would have the same effect but would be interactive and repeatable. My first reaction to the suggestion was that I thought it would be too hard. My brain was still in the manual coding world.
However, I recognized the connection between that and what I was already doing with the Knowledge Navigator project, which is far more complex. Given what I’ve learned about meme coding over the last couple of months I realized that this might be technically and logistically feasible for me.
It is amazing to me how much progress I’ve made on a relatively sophisticated technology project. However, with this progress, I’ve unlocked new, much tougher, questions than the technical aspects of the project.
My priority has always been focused on the task, whatever that task may be. When the tasks don’t align with the software, I inject the human element (usually me) into the equation. I’m always considering the time investment into any task and, if I can use technology to save me time, I do it.
If technology wastes my time, I have no patience for it. I am here to help my students, not fight with technology, much of which was never designed to work in a learning environment in the first place.
Thinking about AI in this way will open whole new possibilities for human employment. I’m not talking about prompt engineering here. I’m talking about operationalizing dreams.
Augmenting ourselves with AI tools will unlock creative forces that will accelerate all economies forward at a rapid pace that need not come at the expense of killing the climate. That’s because this will be an acceleration of ideas, not products.
The revolution will come in the form of human potential. AI will make it easier for everyone to define their future. We just need to recognize and grasp that (and show others the way). But realizing that future will require a different kind of literacy: learning how to think like makers.
…next up: life in a Maker World (Part III)
Part I: Democratizing Imagination
Part III: The Maker World