Overview:
AI's current free accessibility mirrors Uber's early pricing strategy, and that once users become cognitively dependent on LLMs, companies will start charging heavily for what they made indispensable.
Artificial intelligence is commonly touted as a way to increase accessibility into various fields: art, reading, coding, math – if we are to trust Sam Altman, the list of LLM applications is seemingly endless. And anyone who has so much as dabbled with the tech by asking Chat GPT to come up with a sample lesson plan will know that you can use most LLMs for free. There are limits, but upgrading to higher tiers for more access is optional…for now.
There are two stories I tell my students when we discuss A.I. in the classroom. One is a simple analogy that tries to help them understand what they lose when they refuse to do their own thinking. I ask them if they’ve ever gone to the gym, or seen what people do when they work out with weight lifting exercises. How often, I ask, are you lifting objects in your day to day life the way you lift dumbbells for bicep curls? How often are you squatting with something on your back? How often are you doing pushups in everyday life? When they admit that the answer is “almost never,” I say “so does that mean weightlifting doesn’t matter? Should we stop lifting weights at the gym?”
And the gym rats in my class say “Hell no, Ms. Adams! I gotta get my gains up!” And finally, I ask them the sinker question, to bring it home. “Would you expect to get any gains if you hired a trainer to lift all your weights for you? To do the bicep curls, and the weighted squats, and the pushups? Because that’s what you’re doing to the most important muscle in your body, your brain.”
This is a simple analogy, and it resonates well. But this isn’t the story I tell that scares me.
The other story I tell in my classroom is the legend of Uber. Once upon a time, a new tech company hit the market, and had lower prices than any other publicly available transportation services anywhere. You could get all the way across LA for less than 15$! You could take Ubers as far as you needed, and not feel it burn your wallet when you had to take one back.
But how could this be?
It’s not a secret… Uber was undercutting the competition – mainly, taxi services. When their market share had been secured and most of their competition snuffed out, they began steadily raising prices to recoup their subsidized losses, roughly 18% each year for the past 4 years. Now if you want to take an Uber, it’ll cost you more than it likely would have to get a taxi before Uber entered the market.
Now it may sound like I am entering tinfoil hat territory here, but I would like to ask how AI companies, which are currently hemorraging cash from every orifice (Open AI lost $1.22 for every dollar it made in the first financial quarter of 2026, with a total estimated loss of around $38.5 billion last year), are going to plan on making any money from this technology that the world’s wealthiest elites have backed as their fighter in the market?
The cognitive offloading that using artificial intelligence like LLMs produces has been well documented, even for the relatively short amount of time that the technology has existed. Teachers are increasingly hesitant to use it in their classrooms, seeing firsthand the cognitive atrophy of giving a language model the responsibility of your cognitive tasks.
When Sam Altman says intelligence will one day be sold like a utility, I believe him – at least I believe that’s his goal. I believe it is not a coincidence that this technology is being promoted to teachers and students, and that once we have handed over the market share of our processing abilities to A.I. companies, once our students are unable to write an email, dare I say a complete sentence without the help of an embedded LLM, that is precisely when these companies will begin charging hand over fist for the solution to a crisis that they created.
I am begging my fellow teachers to continue pushing back in their PLCs on the implementation of A.I., to stand by the principles of good education that you know are reliable. But most importantly, as a rookie in the profession, I am begging us to keep thinking, keep making mistakes, and keep trying to solve problems on our own. Because one day, sooner than we may think, we might have to.
