Images Shifted Three AI Models’ Coding Choices in a Study

Researchers affiliated with Google DeepMind and Stanford University found that simple images shifted three AI models toward recursive code on a binary-tree task, showing that visual cues can affect answers to an unrelated programming prompt. The team tested Anthropic’s Claude Opus 4.7, OpenAI’s GPT-5.4 and Google’s Gemini 3.1 Pro on inorder traversal of a binary tree. A recursive solution uses a function that calls itself; an iterative solution uses loops. In the main setup, each model produced 20 solutions per configuration after a prompt directed it to inspect an image.

Source: TokenPost