Last month, the U.S. Supreme Court declined to hear the final appeal in Thaler v. Perlmutter. The ruling reinforced a clear principle: copyright requires human authorship. If you type a prompt and publish the untouched output, you don’t own it.
It’s a sensible rule.
But it was written by people who weren’t thinking about all the people who use tools differently.
The Overlooked Scenario
The ruling assumes all prompting is the same activity: someone generates content from nothing. Generative use. Type a prompt, get words, publish.
But there’s another scenario the courts didn’t really consider: what happens when someone has complex thinking that’s already fully formed, but the barrier isn’t the thinking itself. The barrier is the translation.
Neurodivergent brains often work this way. Your thinking might be multidimensional, nonlinear, deeply patterned. But translating that into conventional written form? That’s not a gap in thinking. That’s a gap in access to the expression format most institutions demand.
This is where AI becomes assistive, not generative.
When someone with dyslexia uses text-to-speech, we don’t say the software owns the authorship. The thinking is theirs; the tool is the translation layer. When someone with dysgraphia uses dictation software, the ideas are still theirs. Why? Because we recognize the difference between “generating from nothing” and “accessing your own work.”
The Supreme Court’s ruling flattens that distinction. It treats all AI use as if it’s the same mechanism. It isn’t.
What Gets Lost When You Don’t Notice
Here’s what’s interesting about what a policy misses when it’s written without certain people in the room:
Every time you exclude a perspective from the frame, you create invisible rules that apply differently to different people.
Someone whose brain naturally outputs linear, sequential writing? They can think out loud on a page. The rule doesn’t affect them.
Someone whose complex thinking lives in patterns, layers, nonlinear connections? They need a tool to translate it into the linear format that institutions recognize. And now the rule says that tool owns their work.
That’s not a neutral rule. That’s a rule that advantages one way of thinking and disadvantages another.
And that happens everywhere. In copyright law. In AI policy. In how we define “work” and “productivity” and “creativity.” The framework gets built by people whose brains work a certain way, and it becomes the standard against which everyone else is measured.
The Difference Between Caring and Compliance
Here’s where tech companies come in. Specifically, here’s where advanced tech companies that are decades ahead of everyone else come in.
The minimum bar is compliance. Follow the rules. Don’t touch copyright law. Move on.
But there’s something far more powerful a company can do: actually think about whose experience isn’t in the room when the rules get written. Actually consider what happens when you build tools for translation, not just generation. Actually ask: how might this work differently for different kinds of minds?
That’s not complexity. That’s not extra cost. That’s just care.
And right now, in a field where everyone is racing for the same capabilities, that becomes the differentiator. Not faster. Not more parameters. Not the sexiest benchmark.
The company that says: “We thought about the neurodivergent person. The person whose thinking is deep but whose writing is blocked. The person who needs translation, not generation. And we built that into what we do.”
That’s leadership. That’s the thing that actually matters.
What This Means
The Supreme Court will eventually have to reckon with this more carefully. Courts evolve. They add nuance. They recognize distinctions.
But in the meantime, we don’t have to wait for the ruling to change to think about what’s right.
If you’re building tools, ask: are we thinking about everyone? Or just the people whose thinking style matches how we think?
If you’re using these tools, know this: your complex thinking is yours. Whether a court recognizes it yet or not. The translation is your work.
And if you’re watching the companies build these systems, watch who they’re building them for. Watch whether they notice the gap. Watch whether they actually care.
Because in the end, that’s what separates the ones just chasing numbers from the ones building for all of us.
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