Artificial intelligence (AI) is playing an increasingly large role in many industries, and civil engineering is no exception. AI's potential seems limitless, but it isn’t always a seamless fit. As AI's influence grows, so do the ethical concerns surrounding its use in civil engineering, such as safety and reliability, potential job displacement, and accountability and bias.
1. Safety and Reliability
Many civil engineering projects, such as bridges, buildings, and dams, directly impact public safety. AI systems used in structural design or predictive maintenance must be thoroughly tested and validated to prevent catastrophic failures. While AI tools may be helpful time-savers at some parts of the process, such as predictive maintenance or site analysis, a system of checks and balances should be put into place to avoid mistakes that could affect the safety of finished projects. The National Society of Professional Engineers stresses this, as well, advocating for rigorous verification and validation, testing, and continuous monitoring of AI systems to minimize risk and ensure their dependable operation.
2. Potential Job Displacement
AI-driven automation has the potential to revolutionize construction, improving efficiency and reducing costs. However, this also poses ethical concerns related to job displacement. While AI displays efficiency in areas such as analyzing datasets, there are simply some tasks that are best completed by civil engineers who have years of training and experience. In particular, practical tasks, such as serving as a liaison between an owner and the authority having jurisdiction (AHJ), are best completed by a person rather than a computer. Effective communication and negotiation require emotional intelligence and an understanding of human dynamics. It could also be argued that more abstract parts of the design process, such as conceptualization, are best handled by an engineer who has a detailed knowledge of the region in which they are working.
3. Accountability and Bias
As AI systems take on more decision-making roles, questions about accountability and legal liability arise. In civil engineering, where safety standards and regulations are stringent, determining responsibility becomes complex when AI is involved. For example, ensuring compliance with environmental regulations and building codes is vital, and often involves nuanced legal verbiage and ethical considerations that AI is not fully equipped to handle. In contrast, a seasoned engineer would be qualified to make judgments about uncertain conditions, potential consequences, and acceptable levels of risk.
How can we create a balanced approach that fosters innovation while safeguarding public interests? According to Stephanie Slocum, P.E. civil engineers and firms should develop policies surrounding AI to stay ahead of potential concerns. However, Slocum also iterates that those who adopt AI tools early will likely have a competitive advantage. As with any technological development, balance is key. The civil engineering field as a whole is working toward identifying a ratio of human and machine assistance that produces quality work without sacrificing integrity along the way.
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