Research Examines Prompt-Induced Cognitive Biases in AI for Software Engineering

A study published on arXiv investigates how subtle wording changes in prompts can introduce cognitive biases into general-purpose AI systems used for software engineering decisions. The research introduces PROBE-SWE, a dynamic benchmark designed to test eight specific biases relevant to software development, including anchoring, availability, and confirmation bias. This benchmark pairs biased and unbiased versions of the same software engineering dilemmas while controlling for task logic and difficulty. The work focuses on whether practical prompt engineering techniques can mitigate this bias sensitivity in real-world environments. Researchers examined common strategies like chain-of-thought reasoning and self-debiasing methods. The findings address a critical issue in AI-assisted software engineering, where natural language problem statements and requirements are vulnerable to phrasing shifts. These shifts, such as including popularity hints or revealing potential outcomes, can push AI models toward suboptimal technical decisions. The study aims to provide actionable techniques that practitioners can apply directly without specialized infrastructure.