Artificial Assistance

Imagine a simple exchange between two writers. I hand a scene to a friend and ask him to read it with one question in mind.
“Tell me if I stay consistent in two areas,” I say. “First, tense. Do I remain in past tense throughout the scene? Second, perspective. Do I remain inside the same character’s point of view?”

He reads it carefully.

What I am asking him to check has specific grammatical names. The first is tense consistency. The second is point-of-view discipline, sometimes described as avoiding head-hopping. These are not matters of taste or interpretation. They are structural features of narrative grammar. A sentence either shifts from past to present or it does not. A paragraph either moves from one character’s internal thoughts to another’s or it does not

So my friend reads the scene with those two constraints in mind. He is simply watching for violations of two narrative rules.

Now imagine repeating this process with several friends.

One reads only for pacing. Another watches for character consistency. A third listens for tonal continuity. Someone else follows the shape of the mystery—whether the reader receives information at the right moment. None of them write the story. In fact, while each contributes insight, no one claims authorship.

Consider taking the experiment one step further. Instead of merely observing the rules they were assigned to watch, my friends begin contributing within those domains. The pacing reader proposes a sharper transition between two moments of action. The character reader suggests a line that better reflects a personality already established. The tone reader adjusts a phrase that breaks the atmosphere of the scene. Each suggestion arises from a narrow lens of attention, and the author remains free to accept or ignore it, but the scene gradually improves through the accumulation of these small, specialized contributions.

And still, no questions were raised about human creativity.

Before chatbots appeared, my research routine consisted of web searches and patient reading. I sifted through articles and technical papers on biological systems, electromagnetic devices, weapons, and the machinery of war, looking for the kinds of concrete details that lend weight and credibility to fiction. I spent just as much time studying the craft itself—essays on narrative technique, discussions of tropes, analyses of pacing, tone, and point of view. And eventually the search narrowed even further, into the quiet territory of market awareness: what had been written lately, which ideas had already saturated the field, what resonated with readers, and what had quietly failed to find an audience.

Although the intellectual roots of artificial intelligence stretch back to the 1940s, the same period that produced early computing machines and wartime codebreaking systems, no one begrudged a writer for doing this sort of research.

As the World Wide Web developed and machines grew ever more complex, few in creative circles objected to the artificial tools writers used to gather information. For over half a century, artificial intelligence existed mostly in research labs and niche creative experiments. Some artists even explored AI creatively as early as the 1970s, but it remained obscure and experimental. [2602.19754] Deep Else: A Critical Framework for AI Art

Suddenly, everyone is complaining about the artificial. What, exactly, drives concern about artificial intelligence?

No one objects to the use of spell checkers, grammar software, or tools that outline existing text. Because the author, the human, drives the process. Where is the boundary between creativity and assistance?

Spell checkers and research tools respond to a writer’s decisions; they help refine choices already made. They do not decide what a character wants, why a moment matters, or what truth a story should uncover. Generative systems can suggest such possibilities, offering lines of dialogue or alternative directions for a scene. Generative systems can suggest answers to those questions, but suggestion is not commitment. The decision occurs when the author selects one path and carries it forward into the manuscript.

Even if statistical analysis of word choice and pattern might indicate artificial generation, the determining act remains human: what the author chose to include. That act of selection is what establishes authorship—and ultimately what determines copyrightability.

“Artificial Assistance” is, therefore, irrelevant.