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AI Exceptionalism

“AI is unethical, unless it helps me.”

That, increasingly, seems to be the guiding principle of the AI era. Not artificial intelligence. Not artificial general intelligence. Just… artificial exceptions .

There’s a growing tendency to apply one ethical standard when AI threatens our profession, our company or our livelihood, and a completely different standard when it happens to benefit us.

Call it AI Exceptionalism .

It’s the belief that AI should follow different rules depending on who is using it.

To be clear, this isn’t an argument that all uses of AI are equally good. Nor is it an argument that copyright doesn’t matter, or that artists, writers, actors and educators don’t have legitimate concerns.

They absolutely do.

But if we’re going to have an honest conversation about AI, we should probably try applying the same principles consistently.

Here are four examples where AI consistency disappears remarkably quickly.

On this page

AI shouldn’t write articles, but it can absolutely write code

Training on copyrighted books is fair use, but training on our AI is theft

AI shouldn’t replace actors, but replacing everyone else seems negotiable

Students shouldn’t use AI, but universities definitely should

The Uncomfortable Question

AI shouldn’t write articles, but it can absolutely write code

Some of the strongest criticism of generative AI has come from journalists themselves.

Take Kara Swisher . She has repeatedly warned about generative AI’s impact on journalism, describing concerns around misinformation, media quality and the erosion of trust. Yet she’s also spoken enthusiastically about AI’s potential in software development and has described AI coding tools as one of the genuinely transformative applications of the technology.

Or consider Kevin Roose of The New York Times. Roose has written extensively about the dangers AI poses to journalism and the creative industries, while also documenting his own experiences using AI programming assistants and exploring how dramatically they can improve developer productivity.

Technology journalist Casey Newton has similarly argued that AI presents profound challenges for writers and publishers, while frequently highlighting rapid advances in AI-assisted software engineering and discussing the remarkable capabilities of coding models.

None of these journalists are necessarily contradicting themselves. They may genuinely believe there are important differences between writing news articles and writing software. But those differences are rarely articulated.

Instead, an interesting pattern emerges.

AI writing is often discussed as replacing skilled creative professionals.

AI coding is often discussed as augmenting skilled creative professionals.

Which raises an awkward question:

Why is writing code fundamentally different from writing prose?

Both require creativity, experience, judgement and years of practice. Both are professional crafts. Both are capable of being partially automated. If AI assistance is acceptable because it makes programmers more productive, why isn’t the same argument valid for journalists?

Or, if AI-generated writing undermines professional creativity, shouldn’t AI-generated code raise exactly the same concerns?

Perhaps there is a meaningful distinction. If so, it’s a conversation worth having explicitly.

Because otherwise, to an outside observer, it can look suspiciously like AI is judged less by what it does and more by whose profession it affects .

Training on copyrighted books is fair use, but training on our AI is theft

This might be the clearest example of AI Exceptionalism currently playing out.

In early 2025, OpenAI publicly accused DeepSeek of improperly distilling OpenAI models into competing systems.

Anthropic has since made similar allegations against DeepSeek, Alibaba and other Chinese AI labs, claiming they created fake accounts to extract Claude’s behaviour at scale.

Both companies argue that model distillation unfairly copies years of research and billions of dollars of investment.

That’s a perfectly understandable position. Except…

Those same companies...