Latest white paper describes how employers can apply data and AI technology to reduce the risk of serious injuries and fatalities for workers
Despite concerted efforts to reduce serious injury and death on the job, workplace fatality rates unfortunately increased in 2021, with more than 5,000 workers dying on the job, according to the latest report from the Bureau of Labor Statistics. Recognizing this devastating trend and ongoing challenges organizations face, the National Safety Council released a new white paper through its Work to Zero initiative, Using Data and AI to Gain Insights into Your Safety Program, to help keep workers safe.
“EHS professionals already manage large volumes of data on a daily basis, and advancements in analytics and artificial intelligence have made it easier to synthesize this information to improve existing risk mitigation activities,” said Emily Whitcomb, NSC director of innovation. “In addition to helping employers understand the benefits of investing in safety technology, this white paper outlines new ways organizations of all sizes can leverage AI-powered analytics to advance their workplace’s unique safety culture and ultimately prevent injuries and save lives.”
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The new report evaluated findings from several academic and industrial journals to identify best practices for preventing instances of workplace illness, injury and death with AI technology. Specifically, the white paper highlighted three forms of machine learning organizations can leverage to save time and money, while enhancing performance and improving upon traditional EHS processes, including:
- Computer vision technology. Commonly deployed within CCTV video management systems to monitor images and video footage and detect objects and workers’ proximity to hazards, computer vision capabilities can be combined with additional data such as location, time and safety guidelines to deliver automated alerts for equipment malfunctions, vehicle collisions and more.
- Natural language processing, which can rapidly summarize written reports and extract quantitative insights and sentiments, may be used to enhance productivity and streamline safety reporting and compliance.
- Predictive and prescriptive analytics engines. Designed to enable AI to learn cause-and-effects from historical data, these rule-based systems can be configured to predict incidents before they occur and produce recommendations, such as the most suitable PPE for a specific task, across a range of operating environments.
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While the latest research highlights modern data analytics and AI as powerful tools to reduce employee incidents and streamline manual tasks – creating more time for leaders and EHS professionals to focus on value-added initiatives – Work to Zero uncovered several barriers to widespread AI adoption, including potentially high implementation costs and privacy considerations. The white paper also identified distinct challenges small organizations and large enterprises may face when selecting AI technology, and notes large businesses are more likely to benefit from customized platforms that assist with widespread data collection, training and deployment, while small firms should consider flexible, modular AI packages.
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