What Was the First AI-Generated Image? History and Origin

The Brush and the Binary: Uncovering the First AI-Generated Image

When we think of AI-generated images today, our minds instantly flash to hyper-realistic photographs, surreal digital paintings, or hyper-stylized graphics whipped up in seconds via text prompts. It feels like a futuristic phenomenon born entirely in the 2020s.

Yet, the lineage of artificial intelligence creating art stretches back far further than most realize. Long before diffusion models and deep learning neural networks dominated tech headlines, a quiet revolution was taking place in a university lab.

The story of the very first AI-generated image is not a tale of a supercomputer scanning the internet, but of an artist, a programmer, and a pioneering software program named AARON.

Meet Harold Cohen and AARON

In the late 1960s, Harold Cohen was a successful, internationally acclaimed British painter who represented his country at prestigious global events like the Venice Biennale. At the height of his traditional career, Cohen developed a radical curiosity: What is the core essence of the act of drawing?

To answer that, he decided to turn to computing. In 1968, Cohen left his traditional canvas behind and moved to the United States, eventually landing at the University of California, San Diego, to explore computer science and programming.

By the early 1970s—specifically starting to produce breakthrough outputs around 1973—Cohen created AARON, a computer program widely recognized as the world’s first true artificial intelligence art system.

How the First “AI Artist” Worked

AARON’s mechanism of creation was fundamentally different from how modern AI works today.

• No Neural Networks: Modern AI tools are trained on billions of images scraped from the web, learning to recognize patterns and pixel relationships through deep learning. AARON had no access to a dataset of photographs or prior artworks.
• Symbolic Rules: Instead, AARON operated on Good Old-Fashioned AI (GOFAI)—a rule-based system. Cohen painstakingly translated his own understanding of cognitive drawing rules into computer code.
• Autonomous Decision Making: AARON was taught the rules of geometry, perspective, proportions, and how objects overlap. Crucially, Cohen didn’t pre-draw the images for the computer; he gave the software the rules and let AARON make its own compositional decisions in real-time.

The very first iterations of AARON produced minimalist, abstract, black-and-white line drawings. Connected to a specialized mechanical drawing machine (a flatbed plotter), the computer would physically guide a pen across a sheet of paper, bringing its internal code into the physical world.

From Lines to Landscapes: The Evolution of AARON

As decades progressed, Cohen continuously updated AARON, making it far more sophisticated.

• The 1980s–1990s: AARON learned to handle color, filling in its own shapes and eventually generating recognizable human figures, foliage, and complex organic shapes.
• Exhibitions: AARON’s creations evolved so profoundly that they were eventually exhibited in world-class institutions like the Tate Modern in London and the Whitney Museum of American Art in New York.

Cohen often described his relationship with AARON as a collaboration. He provided the cognitive framework, but the software executed the creative spark.

Why the First AI Image Still Matters

Looking back at AARON’s primitive line drawings offers a profound perspective on the modern AI boom. While today’s tools give anyone the power to conjure breathtaking visuals with a sentence, they stand on the shoulders of pioneers like Harold Cohen.