The Creativity Code

How AI Is Learning to Write, Paint and Think

Intermediate

~2–3h

Marcus du Sautoy

TL;DR:

AI creativity exists in three tiers: exploratory (finding patterns in existing styles), combinatorial (mixing known elements), and transformational (creating genuinely new forms)—but true creativity requires human judgment, context, and meaning that AI lacks.

Guide by

Albert Schaper

About the Book

Author: Marcus du Sautoy (Simonyi Professor, University of Oxford)

Published: 2019 • Length: ~420 pages • Read Time: 6-7 hours

Awards: Longlisted for several major science writing awards

Central Question: Can artificial intelligence be truly creative? Or will it always be merely a tool reflecting human creativity back to us?

Why This Matters

This book teaches you to evaluate creative AI tools for what they reveal about human creativity, how they augment vs. replace creative professionals, and whether AI can achieve "true" creativity.

The Lovelace Test

Can an Algorithm Be Creative?

Ada Lovelace (1815-1852), the world's first computer programmer, believed machines could never transcend their programming. The Lovelace Test asks: Can an algorithm produce something truly creative?

New

Not in training data

Genuinely novel or recombination?

Example: Move 37 never appeared in Go history

Surprising

Unexpected to experts

Contradicts intuition?

Example: Move 37 looked wrong yet won

Valuable

Meaningful to humans

Genuine value beyond novelty?

Example: Move 37 was beautiful and strategic

The Verdict

If an algorithm passes all three criteria, we must concede it can be creative. AlphaGo passed. But can AI achieve this in art, music, and writing?

Three Types of Creativity

Core Framework

Most people think "creativity" is one thing. Du Sautoy shows it's three distinct abilities. AI can do exploratory and some combinatorial. Transformational remains distinctly human (so far).

Exploratory Creativity

AI: High

Extending existing rules. AI excels here.

Key Example: AlphaGo Move 37—surprising yet valid within Go rules

Combinatorial Creativity

AI: Moderate

Combining different domains. AI shows moderate capability.

Key Example: Jazz Continuator—helped Bernard Lubat be more creative

Transformational Creativity

AI: Low

Breaking rules entirely. Remains distinctly human.

Key Example: Picasso's Cubism, Schoenberg's atonality—paradigm shifts

Breakthrough Moments

AlphaGo's Move 37: The Moment AI Became Creative

March 2016 • Game 2 vs. Lee Sedol

In March 2016, Google's AlphaGo defeated world champion Lee Sedol. In game 2, Move 37 shocked everyone:

No human would ever play it—contradicted centuries of Go wisdom
It looked completely wrong to experts watching live
Yet it led to victory—experts called it "beautiful," "strange," "creative"

The Lovelace Test Moment

Move 37 wasn't programmed in. AlphaGo discovered it through learning patterns across millions of games. It was new, surprising, and valuable. Du Sautoy argues AlphaGo passed the Lovelace Test.

The Jazz Continuator: AI as Creative Partner

Sony CSL • Bernard Lubat Collaboration

Revolutionary example: AI trained on jazz musician Bernard Lubat's improvisations, then performed with him in call-and-response concert.

Bernard Lubat's Reaction:

"It's undeniably me—my sound world—but it's doing things I never thought of. The AI helped me be more creative."

Key Insight

Here AI functions as creative partner/collaborator, not replacement. It pushed Lubat outside his comfort zone, stimulating new approaches. This is AI's greatest creative potential.

The Next Rembrandt: Exploratory Mastery

Microsoft + Delft University • 2016

Project analyzed Rembrandt's 346 paintings in microscopic detail: geometry, composition, lighting, materials. Then generated a "new" Rembrandt painting (3D printed in 13 layers of paint-based ink).

✅ Achieved:

Visually convincing Rembrandt-esque painting combining his techniques

❓ Question:

Is it creative or derivative? Does knowing HOW it was made change your experience?

Du Sautoy's Analysis

The Next Rembrandt exemplifies exploratory creativity: works within Rembrandt's established rules, extends his style, but doesn't transform what painting can be.

Creativity Across Domains

Challenge:

Transformational breakthroughs like imaginary numbers

Why Structure Matters

Structure-Heavy (Easier for AI)

• Clear rules and patterns
• Mathematical foundations
• Examples: Music (Bach's fugues), Games, Math

Meaning-Heavy (Harder for AI)

• Requires human understanding
• Context and emotional truth
• Examples: Literature, Philosophy

Consciousness & True Creativity

The Consciousness Question

What would it take for AI to be truly creative?

Du Sautoy argues: Until a machine becomes conscious, it cannot be more than a tool for extending human creativity. But when consciousness emerges (and he believes it might), then machines will "want to tell us what it's like"—and that's when true machine creativity begins.

The Hope for Avoiding Evil AI

Interestingly, du Sautoy argues conscious AI might be our salvation. Why? Because conscious beings understand other perspectives. A conscious AI would:

Understand human values
Not want to harm humans
Have its own creative aspirations we could dialogue with

The Philosophical Frontier

What distinguishes AI tool from creative agent? Does consciousness matter? What would true machine creativity mean? These questions remain open—and fascinating.

Key Takeaways

What AI CAN Do

Achieve exploratory creativity (extending existing domains)
Occasionally achieve combinatorial creativity (novel syntheses)
Surprise us with genuinely creative moments (Move 37)
Collaborate with humans to enhance creativity
Push artists outside comfort zones

What AI CAN'T Do (Yet)

Achieve transformational creativity reliably
Create with consciousness or intentionality
Understand meaning and human values deeply
Break paradigms in writing and language
Recognize what truly matters vs. technically novel

For Creative Professionals

Du Sautoy's Advice

How to position yourself in the age of creative AI

Embrace Collaboration

Use AI as creative partner, not replacement

Extend Your Creativity

Let AI push you outside comfort zones

Maintain Leadership

Keep humans in creative decision-making roles

Understand Domains

Structure-based creativity (music) more susceptible than meaning-based (writing)

The Future of Creativity

The future isn't AI replacing artists. It's artists and algorithms collaborating to achieve creativity neither could alone. Together, create things neither could alone.

Practice What You Learned

Try these AI tools to apply the concepts you've just learned

Midjourney

Exploratory visual creativity

AIVA

AI music composition

ChatGPT

Combinatorial text generation

Runway ML

Creative video tools

Ready to Apply What You Learned?

Co-Intelligence

Learn practical AI collaboration

AI Critical Thinking

Evaluate AI capabilities

Prompt Engineering

Master creative prompting

Key Insights: What You've Learned

AI creativity exists in three tiers: exploratory creativity finds patterns in existing styles, combinatorial creativity mixes known elements in new ways, and transformational creativity creates genuinely new forms—but true creativity requires human judgment, context, and meaning that AI lacks.

Understanding AI's creative capabilities helps you use creative AI tools effectively: recognize when AI is exploring, combining, or transforming, appreciate the role of human curation and interpretation, and leverage AI as a creative collaborator rather than replacement for human creativity.

Apply creative AI tools wisely by combining AI generation with human judgment: use AI for ideation and exploration, apply human taste and context for selection and refinement, and recognize that the most powerful creative work comes from human-AI collaboration, not AI alone.