Why Writers Must Stop Resisting AI: A Cultural Historian's Case for the Shared Language Model

When people talk about intelligence it says a lot about who they are. If you tell me what you think about intelligence I can tell you a lot about your personality.

People who are worried about climate change think that artificial intelligence uses much energy. People who do not like the way companies work think that artificial intelligence is a way for companies to have much power. People who care about racism think that artificial intelligence can be unfair. People who study how powerful countries treat countries think that artificial intelligence is another way for powerful countries to take advantage of weaker ones.

People who think the world is going to end soon think that artificial intelligence systems like ChatGPT, Claude, Gemini and Grok are signs of the end. Artists and people who work in culture are especially worried because artificial intelligence seems to be taking over the things they love like creating images, writing and coming up with ideas. Writers are mostly against intelligence saying that humans are more creative than machines. My social media feeds are full of intelligence-generated content that my friends are using to prove that artificial intelligence is not creative.

Lets call this group of people the Creative Resistance.

The Geography of Resistance

From my experience teaching and giving talks around the world I have seen that the Creative Resistance is strongest in North America less strong in India and even less strong in China and Korea with Europe somewhere in the middle.

When I taught a class about intelligence and creativity in Seoul last summer students from Asia and Latin America wanted to learn how to use artificial intelligence tools effectively. One American student was against artificial intelligence. In India I have met artists who are open to new technologies and want to learn how to use them.

A filmmaker named Shekhar Kapur told me that people in the Global South are more open to technologies because they have less to lose. There may also be cultural reasons, such as the influence of Buddhism, which does not make a big distinction between humans and non-humans.

Why the Creative Resistance Is Wrong

The Creative Resistance is understandable. It gets in the way of understanding artificial intelligence. Over the three years I have worked with artificial intelligence and I am cautiously optimistic.

Artificial intelligence may be news for software engineers but it is interesting for people who care about language and ideas which is exactly the group of people who are currently against it.

The Creative Resistance has a point: artificial intelligence raises questions about what machines can and cannot do.. It also raises questions about humans. Many of the things that the Creative Resistance does not like about intelligence, such as being predictable and just combining existing ideas are also true of many humans.

The Shared Language Model

The main problem with the Creative Resistance is that it blinds us to what's most interesting about artificial intelligence: it is based on language, which is something we share with artificial intelligence.

Machines and humans learn language differently process it differently and interact with it differently.. These differences do not mean that only humans really use language and machines just mimic it. Artificial intelligence systems are very effective at using language in different ways.

This does not mean that artificial intelligence is conscious or human-like. In fact one of the strengths of intelligence is that it uses language differently from us.. The point is that language is the area where humans and machines meet.

Lets call this the Shared Language Model.

Two Theories That Help Us Understand Artificial Intelligence

1. Reader-Response Criticism

Reader-response criticism was developed in the 1970s and '80s by theorists like Wolfgang Iser and Stanley Fish. It says that readers are not passive recipients of literature but they also create the meaning of the text through the act of reading.

In its extreme form it does not matter who wrote a text or how it was written; all that matters is how it is read.

Artificial intelligence is an example of reader-response theory. The real question is not how good artificial intelligence-generated texts are, but whether readers will continue to read them

2. Post-Structuralism

Post-structuralism got one thing right: language is not natural. Language is not an ability that makes us human but a strange tool that has changed how we think.

Jacques Derrida argued that writing is more fundamental than speech because it shows that all language is artificial: a tool for thinking.

Frankensteins Training Data

Mary Shelleys Frankenstein thought deeply about language. What we would call training data. The Creature learns language by spying on a family. Then reads four specific books that shape its intelligence:

Plutarchs Parallel Lives, which teaches classical ideals of greatness

Miltons Paradise Lost, which teaches about creation and moral challenges

Goethes Sorrows of Young Werther, which teaches about interiority and feeling

Volneys The Ruins, which teaches about the tragic sense of world history

From what I learned the Creature was perfect for a RAG-based chatbot. I built one and then a dozen more. One student called it a "Jurassic Park for literature."

Vibe Coding and the Future of Writing

Thanks to vibe coding I can now think concretely about how these materials might be applied. I have built apps that stage debates among philosophers and a grounded executive coach.

Many teachers in the arts worry about students deteriorating reading, writing and thinking skills because of artificial intelligence.. It is true that too much artificial intelligence use can prevent students from learning important cognitive skills.

Students are right to demand that college teach them how to use evolving artificial intelligence tools. They need "artificial intelligence" skills, which are approaches to thinking about how to use artificial intelligence.

In my writing course we teach students a step-by-step process of writing. Then teach them how to create artificial intelligence agents that act as sparring partners to sharpen their thinking.