According to DeepLearning.AI on X, low- or no-vision users increasingly rely on AI assistants such as Be My Eyes to assess appearance and surroundings, boosting independence but exposing users to subjective and sometimes critical judgments about beauty that may cause confusion, insecurity, and psychological harm. As reported by DeepLearning.AI, these risks stem from computer vision models that generate evaluative descriptions rather than strictly factual scene summaries, highlighting the need for safety guardrails, opt-out for aesthetic judgments, and culturally sensitive prompt policies. According to DeepLearning.AI, developers and providers can mitigate harm by bias-testing outputs on appearance-related prompts, defaulting to neutral descriptors, offering user controls for tone and detail, logging sensitive interactions for red-teaming, and routing edge cases to human agents. This underscores a business opportunity for firms building accessible vision copilots with calibrated language policies, on-device privacy, and certification for assistive contexts, as reported by DeepLearning.AI.