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Technology has a reputation for being impersonal. It’s easy to think of machine-driven artificial intelligence, 3D and biomechanics software as an episode of Netflix’s Black Mirror. But when pointed to the right problem, advanced data analytics solutions have the power to change people’s lives for the better.
Take the workplace. Workers in virtually every industry — from shipping to pipe fitting — are at risk of being physically compromised on the job every day. More than half of workers’ compensation claims are made for slips, trips and falls, as well as lifting-related injuries, including overextension and other poor body mechanisms. Many of these problems can be avoided or corrected with proper lifting technique, good posture, and core strengthening.
How data analytics can assess biomechanics
How exactly? By tracking, analyzing and providing employees with timely feedback on their biomechanical shape, communicated in simple terms and in an easy-to-apply format. Repetitive movements are known to cause musculoskeletal strain or injuries, and if left unchecked, the risk increases and the more serious consequences are more likely. But companies can achieve exponential performance gains in exercise health with just a few basic implementations, while reducing injuries and maintaining a healthier workforce.
For example, checking the displacement of the wrist and elbow compared to the hip joints would determine whether an employee is overloading their arms. Suggestions could be given to workers to correct their shape and target larger muscle groups instead of smaller ones. Identifying the weight of the boxes being moved would help refine AI algorithms, and workers could get real-time alerts or haptic feedback to their smartphones — all from the actual direction (“Make sure to lift one foot for the other to share the load from the lower back to the hamstrings”) to personalized strength and conditioning techniques.
When it comes to maintaining the feedback loop, worker smartphones would do a lot of the heavy lifting, so to speak. Almost all manual workers have access to it – and they may even get a phone from the company. Workers may be asked (and encouraged) to stretch and engage in a few exercises while their smartphones track their movements to ensure completion and proper form. In factory and distribution center environments, cameras can be placed throughout the work area to monitor and detect specific imbalances or instabilities. Feedback from that analysis — including strengthening exercises and connections with company-paid trainers or physical therapists — would be sent to each individual employee’s smartphone.
Making life easier
Employees may feel uncomfortable with these implementations. Some startups have equipped their employees with wearable trackers and sensor-equipped vests that, well-intentioned, can be limiting and take a psychological toll. (“Am I being watched?” an employee might ask. “Doesn’t the company trust me?”) And from an operational perspective, introducing new complexities – daily sensor charging, compliance monitoring by employees, problem solving – more work for management. Shouldn’t technology make workers’ jobs easier?
AI can help. To be fair to labor, companies must maintain complete transparency about their intentions and the means of collecting data. Chances are, candor and investment in less intrusive technology will be welcomed by workers, who don’t need to plug in sensors and feel overly controlled every workday. Computer vision technology is already embedded in the security measures of most major system environments. By using those cameras to fail to monitor people’s worst behaviors (theft, burglary, false claims), companies can put these powers to use for good: tracking employee biomechanics, reducing workplace injuries, and optimizing workflows to improve employee wellbeing. Employees stay healthier. Management reduces its insurance claims. Win win.
Is Big Brother watching?
Now, manual workers may have reason to be suspicious of artificial intelligence beyond Big Brother-esque control problems. For decades, workers, from factory workers to packers, have been chasing the rise of the machines—and some have indeed lost work to automation. But some of that change is undeniably positive, including where heavy-duty assembly and high-risk environments have once exposed workers to life-threatening machinery or hazardous chemicals and pollutants. Robotics also reduces injuries and improves efficiency for certain tasks involving repetitive movements previously performed by human workers.
In a perfect world, workers in labor-intensive roles will be retrained to tackle more creative and complex problem-solving tasks. Less experienced workers will quickly gain skills with AI-augmented on-the-job training. In some cases, AI-equipped cameras are already improving rather than replacing human labor. By monitoring production on the assembly line, tracking worker steps and turning findings into actionable feedback, this data technology can provide valuable training in motion efficiency to workers on the line, including how to move and work safely and efficiently in spaces shared by humans and robots.
But who pays the bill here? How do business owners benefit from the adoption (and of course the investment in) data technology? First and foremost is the obvious and immediate benefit of reducing lost labor hours due to injuries and employee-related costs. But there’s also the knock-on effect of fostering a healthier and (hopefully) happier workforce. The question then becomes how to obtain the buy-in of labor. Most of us know that we need to sit or stand longer to improve our posture, but often we are not compliant until an injury occurs. But perhaps gamifying biomechanics and creating a reward system for program completion and shape improvements is the answer. Imagine that every UPS or FedEx driver, assembly worker and distribution center employee not only has access to, but is also actively engaged with exercise and health technology in your pocket. The industry as we know it would change overnight.
Making AI a success
The key to making it happen: a healthy mix of quantified and qualitative data. For example, video is a great source of qualitative data. It resonates on platforms like Instagram and TikTok. On the other hand, data doesn’t lie. Combining the two – qualitative and quantitative information – is the most likely approach to achieving the results companies are looking for. The seamless integration of these data flows is convincingly powerful and helps an employee visualize, understand and translate their movements and the changes needed to address shortcomings and risks.
It’s too important to leave to chance — for employees and employers. Even among white-collar workers, improving posture reduces injuries, saves time away from work, and allows for a more active and improved lifestyle outside office hours and on weekends. As healthier workers and retirees age, they are more likely to age in their place — at home and in familiar and comfortable surroundings. This leads to a better quality of life at a late stage, free of movement restrictions and the restrictions imposed by an aged care facility.
Even if AI doesn’t save the world, it could save this assembly line worker a rotator cuff tear and that picker a hernia. Data analytics has the power to keep us healthy and moving. And the better we move, and the longer we move well, the happier we’ll all be.
Sukemasa Kabayama is the co-founder and CEO of Uplift Labs.
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This post How to use data analytics to improve quality of life
was original published at “https://venturebeat.com/2022/04/23/how-to-use-data-analytics-to-improve-quality-of-life/”