Google DeepMind and Stanford study finds simple images can steer how AI writes code

A red heart pushed two frontier models to write recursive code every time, and the models mostly didn't notice why Show an AI model a red heart, and it might start writing recursive code. That is the headline finding of a new paper from researchers at Google DeepMind and Stanford University. The paper is titled “A Heart Means Recursion: Exploring Visual Meaning and Communication in VLMs.” It was posted to arXiv on October 27, 2026. It suggests that unrelated pictures attached to a prompt can quietly change how vision-language models solve programming problems. The images had nothing to do with the task. The models changed their behavior anyway. A heart, a checkmark, and a coding test The study is led by Alexa Tartaglini, a researcher affiliated with both Google DeepMind and Stanford. The team focused on vision-language models, or VLMs. These are AI systems that can take in images alongside text, which describes most of today’s flagship chatbots. The test was a classic programming exercise: binary tree traversal. Picture a family tree where every person has at most two children. The job is to write code that visits every person in that tree. There are two broad ways to do it. A recu...