Key points
Artificial intelligence already is part of our everyday lives: in our web searches, in our interactions with digital assistants, and even helping us decide what movies and TV shows to watch.
In the world of worker safety, AI is providing “great opportunities.” That’s according to Jay Vietas, chief of the emerging technologies branch of the NIOSH Division of Science Integration.
“Not only will it be in the fabric of the future of work, but it’s going to be in the fabric of solutions to the future of work as well,” Vietas said during a webinar hosted by the agency in June.
Some of the benefits AI is providing to the safety field: deeper insights, continuous observations and real-time alerts to help employees avoid unsafe situations and organizations respond to incidents quicker.
Experts say making use of AI requires collaborative efforts between safety professionals and other departments, namely information technology, to ensure transparency as well as alleviate privacy concerns and other issues workers may have.
“Our recommendation is, basically, try to understand AI and try to see how it can work for you,” said Houshang Darabi, a professor at the University of Illinois Chicago and co-director of the occupational safety program at the school’s Great Lakes Center for Occupational Health and Safety.
Some uses of AI
AI is defined as the use of computers and/or machines to try to replicate human decision-making, problem-solving and other abilities.
“AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data,” according to software company SAS.
Subsets of AI include machine learning, neural networks, computer vision and natural language processing.
One safety-related example is the use of cameras that can detect whether workers are wearing their personal protective equipment. Specifically, the devices can monitor employees who are working at height and need to be wearing harnesses. Not only can the cameras detect whether the workers are wearing their harness, but they also can identify if the PPE is tethered, said Donavan Hornsby, corporate development and strategy officer with Benchmark Digital Partners and the Benchmark ESG digital platform.
During a technical session at the 2021 NSC Safety Congress & Expo, Hornsby and Dave Roberts, vice president of environmental, health and safety at The Heico Cos., offered other examples of tasks that AI-enabled cameras can perform. These include tracking interactions between workers and machinery, monitoring the status of machine guarding, checking if workers are in or outside of designated areas, and performing ergonomic assessments. The devices also can be paired with sensors or wearables that are attached to hard hats, vests or other items.
That continuous eye on workers means that safety pros don’t have to rely solely on observations, walkarounds or inspections to ensure workers are wearing PPE or to identify other safety issues.
“Instead of depending on one person doing their round once a shift or once a day,” Hornsby said, “what if the cameras are always looking and that person can now spend time working on more value-added activities?”
Heat mapping and fatigue monitoring
Cameras and/or sensors and wearables also have the ability to generate heat maps, which can show where high-risk activities are taking place in a facility.
It’s important, Hornsby noted, to layer that data with operational data for greater knowledge and analysis.
“Then you have this kind of multilayer perspective on risk: high-risk operations, people that are working long hours, high concentrations of activity,” he said.
For employees working long hours, Hornsby said certain AI-enabled programs can help measure cognitive impairment. That can come in the form of, say, a 30-second visual puzzle. With an established baseline for each worker, the cognitive screening can test personnel before each shift.
“They can get a sense of whether or not they’re cognitively impaired,” Hornsby said, “which may have been a result of working too long of a shift the day before or not getting enough sleep or personal issues, or whatever the case might be.”