Safety engineering, or system reliability (RAMS — Reliability, Availability, Maintainability, and Safety), is a critical discipline in modern engineering. It involves risk analysis, designing robust and safe systems, and monitoring their performance throughout their lifecycle. Safety engineers play a central role in this process, ensuring that complex systems, whether autonomous vehicles, power plants, or critical infrastructures, function as intended while minimizing risks.
Artificial intelligence (AI), with its growing capabilities, has the potential to profoundly transform this discipline. However, this transformation raises essential questions: will AI make the work of safety engineers obsolete, or will it instead enhance their role by improving processes and increasing efficiency?
1. AI as a Transformational Tool: Automating Analyses and Simulations
One of the first ways AI could transform safety engineering is through the automation of analyses and simulations. Today, engineers spend hours evaluating potential risks using traditional methods like Failure Modes and Effects Analysis (FMEA) or reliability studies. These methods require meticulous data collection and analysis, as well as expertise to interpret the results.
AI, particularly through machine learning and deep learning techniques, could automate much of this work by analyzing massive amounts of operational data, failure histories, and identifying patterns or anomalies that the human eye might miss. For example:
- Predictive Maintenance: AI models can be trained to predict failures based on sensor data, optimizing real-time maintenance and reducing downtime.
- Failure Simulation: AI can simulate complex failure scenarios in real time, anticipating situations that traditional methods might not cover comprehensively.
However, even if AI speeds up these processes, it doesn’t necessarily mean that engineers will become obsolete. In fact, these automation tools could augment their capabilities, allowing them to focus on higher-value tasks such as interpreting results, making strategic decisions, and developing innovative solutions.
2. AI and Safety Engineers: An Essential Collaboration
The very nature of safety engineering requires human interpretation. Indeed, even if AI can analyze data and simulate scenarios, it has its limitations:
- Contextual Understanding: AI doesn’t understand the operational context, regulatory implications, or ethical and social constraints as comprehensively as human engineers. A failure can have vastly different consequences depending on the environment, and this requires human judgment.
- Decision-Making in Critical Situations: In critical situations, the decision to balance safety, costs, and performance remains primarily a human responsibility. AI can assist by providing analyses and options, but it cannot make ethical or strategic decisions.
Therefore, engineers will continue to play a central role, but their work will increasingly focus on collaborating with intelligent systems. They will need to understand how to use AI tools, how to interpret their results, and how to integrate this information into a comprehensive risk management framework.
3. A Transformation of Skills: The Engineers of Tomorrow
AI will also transform the skills required for safety engineers. Traditionally, these engineers focus on risk analysis based on databases, failure diagrams, or past experiences. With the introduction of AI, new skills will be needed:
- Data Analysis: Engineers will need to know how to manipulate and interpret machine learning models, understand potential biases in the data, and adjust algorithms to obtain reliable predictions.
- Cybersecurity and AI System Safety: As safety systems themselves become AI-based, engineers will need to ensure that these systems are secure against attacks and data manipulation, guaranteeing their reliability.
- AI Ethics and Regulation: Understanding the ethical and regulatory issues surrounding AI will be crucial to ensuring that proposed solutions meet safety and security standards while being socially responsible.
4. Toward an Automated or Augmented Future?
The question of whether AI could eliminate the safety engineer remains open. In the short and medium term, it seems unlikely that AI will entirely replace humans. On the contrary, AI presents itself as a tool for augmenting human capabilities, allowing engineers to process larger volumes of data, automate repetitive tasks, and focus on the strategic and critical aspects of safety engineering.
However, in the long term, it is possible that next-generation intelligent systems, combined with autonomous robots capable of intervening on-site, will make some human tasks less necessary. The human role will then evolve, shifting from that of an executor to that of a supervisor, strategist, and guarantor of the ethics and compliance of autonomous systems.
AI will not eliminate the role of the safety engineer, but it will profoundly transform their activities and the skills required. Engineers will need to adapt, learn to collaborate with these new tools, and focus on higher-value tasks. Rather than seeing AI as a threat, it is better to view it as an opportunity to reinvent the discipline and improve system performance in terms of reliability and safety.