Technology has a reputation for being impersonal. It’s easy to think of machine-driven artificial intelligence, 3D and biomechanics software as we would an episode of Netflix’s Black Mirror. But when pointed at the right problem, advanced data analytics solutions have the power to change human lives for the better.

Take the workplace. Laborers across practically every sector — from shipping to pipefitting — are at risk of being physically compromised on the job every day. More than half of manual worker compensation insurance claims are filed due to slips, trips and falls, as well as lifting-related injuries — including overextension and other poor body mechanics. Many of these problems could be avoided or corrected through proper lifting technique, good posture and core strengthening.

How data analytics can assess biomechanics

How, exactly? By tracking, analyzing and providing timely feedback to workers about their biomechanical form, communicated in simple terms and in an easy-to-apply format. Repetitive movements are known to cause musculoskeletal strain or injuries, and when left unaddressed, their risk grows and the more likely severe consequences are to follow. But companies could make exponential performance gains in movement health while reducing injuries and maintaining a healthier workforce with just a few basic implementations.

For example, monitoring the displacement of the wrist and elbow in comparison to the hip joints would determine whether a worker is overextending their arms. Suggestions could be delivered to employees for correcting their form and engaging larger muscle groups over smaller ones. Identifying the weight of the boxes being moved would help refine the AI algorithms, and workers could be sent real-time alerts or haptic feedback to their smartphones — everything from in-the-moment direction (“Make sure to put one foot in front of the other to share the load bearing from the lower back to the hamstrings”) to personalized strength and conditioning techniques.

In fact, when it comes to maintaining the feedback loop, worker smartphones would do a lot of the heavy lifting, so to speak. Almost all manual laborers have access to one – and they may even be provided a phone by the company. Workers could be asked (and incentivized) to stretch and participate in a few drills as their smartphone tracks their movements to ensure completion and proper form. In factory and distribution center environments, cameras could be positioned throughout the work area to monitor and detect specific imbalances or instabilities. Feedback from that analysis – including strengthening exercises and connections to company-expensed trainers or physical therapists – would be sent to each individual employee’s smartphone.

Making lives easier

Workers may be uneasy about these implementations. Some startups have taken to outfitting their workers with wearable trackers and sensor-equipped vests that, however well-intentioned, may be restrictive and take a psychological toll. (“Am I being watched?” an employee might ask themselves. “Does the company not trust me?”) And from an operational perspective, introducing new complexities — daily sensor charging, monitoring employee compliance, troubleshooting — creates more work for management. Isn’t technology supposed to make workers’ jobs easier?

AI can help. In fairness to labor, companies should maintain full transparency about their intentions and the means of data collection. Chances are, that candidness and investment in less intrusive technology will be welcomed by employees, who won’t be required to attach sensors and feel overly scrutinized every workday. Computer vision tech is already incorporated into the security measures of most large system environments. By using those cameras not to monitor people’s worst behaviors (theft, burglary, false claims), companies could use these powers for good — tracking employee biomechanics, reducing workplace injuries and optimizing workflows to improve worker wellness. Employees stay healthier. Management reduces its insurance claims. Win-win.

Is Big Brother watching?

Now, manual workers may have reason to be leery of artificial intelligence beyond Big Brother-like monitoring concerns. For decades, laborers from factory line workers to packagers have been on the lookout for the rise of the machines – and some have, indeed, lost work to automation. But some of that change is undeniably positive, including where heavy-assembly and high-risk environments once exposed workers to life-and-limb-threatening machinery or hazardous chemicals and pollutants. Robotics are also reducing injuries, as well as improving efficiency, for certain repetitive-motion tasks previously performed by human workers.

In a perfect world, employees in labor-intensive roles will be re-trained to tackle more creative and complex problem-solving tasks. Less-experienced workers will be able to quickly skill up with AI-augmented on-the-job training. In some cases, AI-equipped cameras are already enhancing, rather than replacing, human labor. By monitoring assembly-line production, tracking worker steps and processing findings into actionable feedback, this data technology can deliver valuable movement-efficiency training to employees on the line – including how to safely and efficiently move and operate in spaces shared by humans and robots.

Yet who’s footing the bill here? How do business owners benefit from the adoption (and, of course, investment in) data technology? First and foremost is the obvious and immediate benefit of reducing lost labor hours due to injuries and worker-compensation-related costs. But there is also the knock-on effect of promoting a healthier and (hopefully) happier workforce. The question then becomes how to gain the buy-in of labor. Most of us know that we should be sitting or standing taller to improve our posture, but often we aren’t compliant until an injury occurs. But perhaps gamifying biomechanics and creating a reward system for program completion and form improvements could be the answer. At scale, imagine every UPS or FedEx driver, assembly worker and distribution center employee not only having access to but actively engaging with movement-health-in-your-pocket tech. Industry as we know it would be changed overnight.

Making AI a success

The key to making it a reality: a healthy mix of quantified and qualitative data. Video, for instance, is a great source of qualitative data. It resonates on platforms like Instagram and TikTok. On the other hand, data doesn’t lie. Marrying the two — qualitative and quantitative information — is the most likely approach to yielding the results companies are looking for. The seamless integration of these data streams is persuasively powerful, helping a worker visualize, comprehend and translate their movements and the changes required to address deficiencies and risk.

It’s too important to be left to chance — for workers and employers. Even among white-collar workers, improving posture reduces injuries, saves time away from work and allows for a more active and enhanced off-hours and weekend lifestyle. As healthier employees and retirees grow older, they are more likely to age in place — in the home and amid familiar and comfortable surroundings. This leads to a better late-stage quality of life, free from movement impairment and the limitations imposed by a senior care facility.

Even if AI doesn’t save the world, it can spare this assembly-line worker a rotator cuff tear and that picker a slipped disc. Data analytics have the power to help 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 cofounder and CEO of Uplift Labs.