How will artificial intelligence impact professional engineers?
Will it improve their lives or put them out of work?
Any major AI chatbot can provide answers to those questions, spitting out a list of bland bullet points. But the answers reflect a lack of detail and an ignorance of how engineering currently operates in the real world.
Others in the field have a more nuanced view, with engineers still figuring out where and how machine learning will be applied.
“We view it as just another tool,” said Dorothy Davison, executive director of the
American Council of Engineering Companies of Rhode Island.
She’s confident the technology will not put engineers out of work.
“We used to have drafters do all the drawing, then CAD [computer-aided design] came about. People freaked out,” Davison said. “But it wasn’t the end. Those who learned CAD used it to draft more efficiently.”
If anything, demand may be greater in the future, she says.
“Right now, we have a real workforce issue. A huge number of engineers are aging, and we don’t have nearly enough people going into civil, structural and mechanical engineering. AI may make some jobs obsolescent. But if you have an engineering degree, there will always be a place for you.”
AI technology has been used for numerous engineering tasks, including assisting with computer coding, generating data sets and designing electronic circuits. With many AI platforms at their early stages of development, there is some anxiety about where things might be headed.
ChatGPT, an AI chatbot developed by OpenAI, has answers for everything, including questions about the future of AI in engineering.
“AI can automate routine and time-consuming tasks, enabling engineers to focus on more-complex and strategic activities,” ChatGPT responded when queried. “This enhances productivity, allowing professionals to tackle more-challenging problems and deliver higher-quality results.”
Asked where AI will have the most impact, ChatGPT honed in on a few particulars: design optimization, predictive maintenance, process automation, data analysis and decision support, and managing and optimizing smart infrastructure support.
ChatGPT professed that trained professionals are still necessary.
“It’s worth noting that while AI can automate certain tasks and assist engineers, human expertise, creativity and critical thinking will continue to be essential in engineering fields,” ChatGPT said. “Engineers will be responsible for designing AI systems.”
Miguel Bessa, an associate professor of engineering at
Brown University, is launching a course this fall focusing on data-driven design and analysis of structures and materials. The class will examine how AI applications can solve engineering problems.
“Engineers who know machine-learning methods will be at a significant advantage in the job market,” Bessa said. “[It will be] akin to what happened in the recent past to engineers who knew how to code.”
He expects engineers to start shifting toward a more data-driven approach to decision-making, analysis and design. Some disciplines already have embraced machine learning and AI, such as automotive engineering due to the growth of autonomous driving, he says.
“An even greater impact might happen in robotics due to our quest to engineer intelligent artificial agents, but this may occur over a longer time span,” Bessa said.
Yan Sun leads the Department of Electrical, Computer, and Biomedical Engineering at the
University of Rhode Island. Initially, she was reluctant to fully adopt AI in her classes.
As the spring semester began, Sun banned students in her information security class from using ChatGPT to write papers, considering it cheating. She recalibrated after only three weeks.
“I decided we better all learn how to use it,” Sun said.
Machine learning can be used to battle hackers attacking the American power grid from Russia, she says. “The opposition already uses AI to be powerful and stronger. My research focuses on how to detect those attacks, how machine learning can detect anomalies, failures of power substations, and assaults on transmission lines.”
Sun says there aren’t enough engineers to meet demand. “If we use machine learning and AI correctly, we can improve productivity,” she said.
Indeed, Davison says the creative process still must be done by a person. Building projects, for instance, often must take into account parochial conditions and community desires. There always are existing structures to consider along with aesthetics, infrastructure, water and zoning commissions.
“You always have to take the computer-simulated design and bring it down to earth,” Davison said. “It’s a trained engineer who makes the decisions. So we don’t look at AI as a terrifying thing. Engineers are problem solvers, they love technology, and they will likely find ways to embrace it and to use it.”
