Large Language Models (LLMs), like ChatGPT, Claude and Deepseek, offer a significant shift for fire safety. Although they bring transformative opportunities, they also introduce profound risks. The challenge is to adopt LLMs without affecting core values, such as preserving lives and assets. Remember, our profession is built on values, codes, empirical evidence and accountability.
The promise: a powerful engineer’s toolkit
The impact brought by LLMs will surely be felt in fire safety. This is a result of LLM’s advanced language and pattern processing. They’re crucial in:
- Information Retrieval – LLMs can be used to quickly recall information or generate summaries at a superordinate level, saving time that would otherwise be spent on manual searching.
- Communication – LLMs can free engineers’ time from drafting texts and formal reporting for client communications.
- Ideation – It serves as a brainstormer, generating lists of possibilities (e.g., common sources of false alarms) for deeper human investigation.
The peril: illusions of competence and critical risks
The LLM’s fundamental operations on probabilities, not truths, are the greatest danger. LLMs focus on predicting the next word in the sequence instead of the next accurate technical fact. This creates critical risks such as:
- Hallucinations –The models can generate sections of technical documents that are fabricated, yet appear convincing.
- Outdated Knowledge –An LLM’s knowledge is stagnant after the model training data cutoff date, making it unaware of the latest updates.
- Content Blindness –They cannot physically grasp the unvoiced boundaries of the projects or the intent behind a code clause.
The difference between being a helpful tool and a serious risk hinges on one fundamental skill: prompt engineering. The efficacy and safety of the results rely on the user’s ability to form professional prompts.
Case example 1: system deficiency classification
Scenario: An inspection of a dry valve sprinkler system reveals a missing clapper latch assembly.
Poor prompting:
“What is wrong with a dry valve if the clapper’s latch is missing?”
The LLM’s misleading answer:
“A missing clapper latch may result in reduced efficiency, but routine maintenance should resolve it.”
The risk:
This answer is technically incomplete. It doesn’t explain why, and what authoritative references are needed to classify the deficiency. An inexperienced technician could document this as an “observation” without highlighting its implications.
The well-engineered prompt:
“Act as a senior fire inspector examining systems in a warehouse that has 500 sprinklers installed. You note a missing clapper latch in a dry-valve, with a capacity of 1150 gpm. Classify the deficiency according to NFPA 25, 2017 edition, detailing 1) Chapter/Section reference, 2) Deficiency classification, 3) Implication for system operability.”
The LLM’s answer (paraphrased):
“According to NFPA 25 (2017 Edition), a missing clapper latch is a critical deficiency.
- Reference: NFPA 25, Chapter 13, which governs dry pipe valves.
- Classification: This is typically classified as a ‘Critical Deficiency’ as it prevents the valve from functioning as designed and renders the entire system inoperable. When the most remote hydraulically-calculated sprinkler activates, the water flow through the valve assembly is minimal. In the absence of a latch, the clapper may close. In such scenarios, a lot of force, between 3 to 5 times, is acting on the clapper’s upper side. Mostly, the clapper will not reopen until water is drained from the upper-side.
- Required Action: The deficiency must be corrected immediately. The system should be tagged and considered impaired per NFPA 25 Chapter 16.
- Implication: The system may not control a fire.
The value:
This precise prompt forces the LLM to formulate its response against an authoritative standard. It provides actionable information that is professional and code-compliant.
Case example 2: calculating travel distances
Scenario: You are performing a life safety analysis of a business occupancy.
The weak prompt:
“What is the maximum travel distance to an exit in an office building?”
The LLM’s inadequate answer:
“The maximum travel distance in a sprinklered office is typically 300 feet, as per NFPA 101.”
The risk:
This is a risky and oversimplified assessment. An untrained person could just take the 300 ft. and measure a direct line on a drawing without considering the obstacles that an occupant may encounter, leading to unsafe designs.
The professionally engineered prompt:
“Define travel distance per NFPA 101 Life Safety Code, 2018 edition, for a sprinklered business occupancy. Express how it is measured in a real-world environment with obstructions like furniture and partitions.”
The LLM’s accurate answer (paraphrased):
“Per NFPA 101 (2018 Edition), 7.6.1, travel distance is defined as the actual path the occupant would take to the nearest exit from any point within a building.
- Measurement: It must be measured along the natural and unobstructed walking path and include all fixed obstructions, furniture, etc.
- Maximum Limit: For a sprinklered business occupancy, the maximum travel distance is 300 ft (Chapter 38.2.6.3); however, the distance must be measured based on the path taken, not a straight-line distance.”
The value:
This specifically prompts the model to outline the most ambiguous concept regarding egressing and be anchored to the code’s intended application.
Ethical and professional responsibilities
The deployment of LLMs brings ethical and legal issues for which the engineer is legally liable and responsible, such as:
- Accountability –The engineer who seals a design is fully accountable. Liability cannot be transferred for an LLM. Insurance will not cover errors caused by an AI that the engineer didn’t catch.
- Standard of Care –A court in a negligence claim will evaluate the Engineer’s standard of care if exercised or not. Those who blindly rely entirely on an LLM would fail the test unquestionably.
- IP and Privacy –If confidential information or copyrighted documents are shared on a public LLM, it creates a significant privacy and intellectual property risk. No one has complete control over how that data is used, stored or possibly leaked.
The engineers are the conductor
LLMs will undoubtedly be integrated into fire safety workflows. Despite being amplifiers of human judgment, they are not substitutes for it. Think of an LLM in its current state as a junior engineer: bright, fast, and knowledgeable, but in need of continuous oversight. That is, a managed tool. The best approach is to combine engineering with advanced prompt design while training LLMs to boost efficiency and output quality.
Systematic testing and verification must be applied to all generated content through primary driving documents such as codes, standards, and datasheets.
The engineer must be the conductor, able to assess the tool’s capabilities, interpret results in light of professional benchmarks, and process each output in line with the profession’s requirements. Such tools can be used for drafting, summarising and assumption testing. They must never be trusted to conclude, certify, or make code-informed judgments that form the core of the business. Remember, people’s lives and properties are dependent on you!
