This research paper examines how large language models (LLMs) perpetuate covert dialect bias, affecting social judgments in housing-related contexts. The study reveals that LLMs associate certain dialects with negative adjectives, reflecting human housing discrimination. This finding highlights the need for AI developers to address this bias and ensure fair decision-making in AI-driven applications.