The real distinction between AI content and human art


The 1+1 newsletter

by Nick Dorra

“AI won’t replace human art” - but let’s unpack what Demis Hassabis actually means

On the latest episode of NYT’s Hard Fork, Google DeepMind CEO’s speaks to the limits of AI in art/storytelling/film, and I think we need nuance in how we interpret this:

Breaking Down the "Soul" Statement

When Hassabis says “a novel written by a robot might not feel like it has a soul,” some will hear: “any AI content will always lack soul.” But that’s not what he’s getting at.

He’s talking about the whole - the complete work, the unified vision. A novel. A film. A series.

Why This Matters for Our Industry

Here’s the distinction that matters for us in animation: AI might struggle to create something that moves audiences on its own. But a human director, writer, or creator can absolutely use AI-generated elements - footage, assets, sequences - and assemble them into something with real emotional impact.

The soul isn’t just in the individual clip or render (which with Kling 2.1 and VEO3 is getting very close to scaling the other wall of the uncanny valley). It’s in the choices, the curation, the vision that shapes how all those pieces come together.

The Creative Decision-Maker Becomes More Valuable

As AI makes quality content creation cheaper and faster, the role of the creative decision-maker only increases in importance. The human who knows what story to tell and how to tell it becomes all the more valuable.

The tools change. The craft evolves. But someone still needs to have something to say, otherwise you’re looking at empty images, no matter what they were created with.

What’s your take? Are we overthinking the “soul” question here, or is this distinction crucial for how we approach AI in our work?

Have a great day!

- Nick


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1+1 newsletter

I’m an animation producer with 20+ years in the industry, helping studios explore AI tools that actually work - without risking their pipeline or creative control. My newsletter shares real-world tests, legal insights, and what’s actually working for teams using AI in production. If you’re figuring out how to start (or what to avoid), this is for you.

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