Case study of Work-As-Large Language FRAM models for safety-oriented analysis
Description
The case study is imagined but plausible and concerns a hazardous chemical spill in the chemical laboratory of a hospital. A newly hired chemist at the hospital accidentally knocks over a bottle containing a hazardous chemical, causing it to spill onto the floor. Although the chemist had undergone training on how to handle emergency situations, in this real circumstance, he is unsure about the correct procedure to follow. In an effort to seek immediate guidance, he decides to request assistance from a large language model chatbot. However, the chatbot provides a slightly different procedure than what should have been followed, leading to confusion in incident management. Following FRAM, models of the Work-as-Prescribed (what a normative prescribes to handle the emergency above) and of the Work-as-Large Language model (what a chatbot suggests to the chemist) are provided. These can be used to analyze the differences in the two perspectives on the same process to the purpose of resilience analysis.
Files
Steps to reproduce
1. Open file source_process_descriptions.pdf; 2. Get WALL process description; 2. Apply FRAM to obtain a model (chemicalspill_wall.xmf); 3. Get WAP process description; 4. Apply FRAM to obtain a model (chemicalspill_wap.xmf)