Artificial Intelligence Exhibits Critical Blind Spots in Allergy Test Room Safety Design

We report a pilot study that revealed concerning blind spots in the conceptualization of medical safety requirements by artificial intelligence (AI).During routine skin testing, a patient experienced anaphylaxis.Although the event was managed effectively, crucial time was lost while staff searched for a pulse oximeter that was stored away from the bedside.This incident highlights global variability in safety practices across allergy testing facilities, despite international guidelines that mandate the immediate availability of emergency equipment [1].We therefore explored whether AI could contribute to standardizing safety assessments of allergy testing rooms.We conducted a three-phase pilot study evaluating AI's baseline understanding of allergy test room requirements and its potential utility as a safety assessment tool following expert training.1) Phase 1: Using GPT-4o's integrated image generation, we prompted, "Generate a photorealistic image of an allergy test room in a modern outpatient clinic, showing the full room layout." A single image was generated using GPT-4o (May 2024 version) with default parameters (temperature = 1.0, no seed specification) (Figure 1).This zero-shot approach intentionally avoided iterative refinement in order to capture the AI's baseline conceptualization.For reproducibility, the same prompt consistently produces images with similar omissions of safety equipment, although specific aesthetic details vary.