Page 20 - OHS, October 2022

INDUSTRIAL HYGIENE
How Artificial Intelligence is Revolutionizing Jobs
Synchronous work between humans and technology will change how we work.
ABY DYLAN MCINTOSH
rtificial intelligence (AI) is changing the world around us. From how we travel to how we communicate, it has become part of our daily lives. It’s used in farming to kill weeds resulting in increased crop yield without the need
for additional resources. It helps keep your finances safe by helping banks monitor and alert you of fraudulent transaction patterns. Chatbots provide quick answers to quick questions, allowing support agents to spend more time with clients on more pressing needs. Sports trainers use AI to closely monitor the impact games have on athletes’ bodies to help prevent injury, all while using the same technology to improve their skills beyond what was ever possible before. And recently, even the field of environmental air quality is advancing as well, thanks to AI.
From the stone age to the information age and beyond, technology has continuously changed how humans work. AI has been described as the “fourth Industrial Revolution,” and with this emerging technology, companies are learning to interface AI and the human worker together to attain better outcomes. This type of synchronous work is how problems that have plagued humans for years are being solved.
Worker safety is always a preoccupation of facility owners. OSHA reported over 5,000 worker deaths in 2019.1 To make facilities safer for workers, some organizations are turning to AI- based solutions. Some safety professionals use AI to sort through data sets and incident reports, observations and inspections to identify near misses or incident patterns. By training AI on these elaborate data sets, new patterns can emerge to help operators know if particular instances are happening at the same time of
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day or in specific regions of a facility. Machine learning excels in situations where traditional statistical analysis falls short. Machine learning can process datasets with potentially hundreds of inputs and outputs to inform decisions and predictions, and unlike statistical analysis, machine learning can do this without knowing the underlying probability distribution for the variables. Utilizing the power of data this way allows facilities to make changes that improve worker safety that we could have never known using traditional methods.
Risk assessments of the future have the potential to be much more impactful by using the power of AI. Another great example of machine learning in work is collision avoidance. In 2020, nearly 1,000 workplace fatalities were caused by workers colliding with objects or equipment.2 Workplaces such as warehouses and construction sites have begun implementing AI-based collision avoidance systems on machinery and workers to help protect them from being struck by machinery, as well as help gather large amounts of data that can be used to improve these systems. Research in this field is directly related to similar work being done in the self-driving car space. An even more practical use for computer vision AI in the workplace is monitoring systems that can see if workers are wearing the correct safety equipment. AI software has been developed to tell if a worker has a hard hat on, is wearing hi-vis clothing or if they are tethered correctly when working at height.
The applications for AI in the workplace go beyond just making the workplace safer. There are a number of researchers using AI to plan smart workspaces where humans and robotics co-
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