by Maxime Vermeir, Senior Director of AI Strategy
One of the most significant humanitarian contributions of AI is that it’s helping create a safer world, whether that takes the form of improving driver safety, detecting safety hazards at construction sites, or helping the FDA identify adverse reactions to drugs more quickly.
We all know that artificial intelligence (AI)–driven technology can deliver impressive business results: higher productivity, faster processes, reduced overall costs, etc. According to some predictions, AI will contribute up to $16 trillion to the global economy by 2030, primarily in the form of productivity gains.
Alongside these business-focused, bottom-line-boosting benefits of adopting AI, another category of benefits has emerged: those that benefit society on a human level. To cite just a few examples, AI is enabling more accurate weather forecasting, faster responses to disaster situations, and improved patient experiences.
These innovations are emerging at a time when many are expressing concerns about artificial intelligence, viewing it as a threat to personal freedoms rather than a force for good. At its core, however, AI is a tool like any other, and its impact depends on how it is used. One of the most significant humanitarian contributions of AI is that it’s helping create a safer world, whether that takes the form of improving driver safety, detecting safety hazards at construction sites, or helping the United States Food and Drug Administration (FDA) identify adverse reactions to drugs more quickly.
According to the National Highway Traffic Safety Administration, traffic crashes in 2020 were responsible for more than 38,000 fatalities—the highest number since 2007. The office further reports that in 45 percent of those fatal crashes, drivers of passenger vehicles were engaged in risky behaviors such as speeding.
In an effort to prevent future fatalities and promote safer conditions for all drivers, auto insurance companies are turning to intelligent automation. Previously, insurers relied on past driving records—frequency and severity of tickets and accidents—to assess the safety of an individual’s driving habits. Today they can use telematics to collect real-time data while the person is driving, either through a physical device plugged into the vehicle or via a smartphone app. Both methods use AI to detect behaviors such as sudden acceleration and hard braking, and smartphone apps can also flag phone use while driving, a proven risk factor in traffic fatalities. Auto insurance companies then use this data to reward safe drivers with discounts and to encourage those with less-than-stellar habits to be more careful.
On the commercial side, truck fleets are using AI-driven coaching apps to leverage positive reinforcement in helping drivers improve their safety practices. Netradyne’s Driver-i application, for example, analyzes 100 percent of a driver’s practices (not just “triggered events” such as speeding, in contrast with consumer insurance tracking apps) via computer vision using data from the rig’s dashcam. Through in-cab alerts and automated virtual coaching, drivers receive real-time feedback on what they’re doing as well as what they could be doing better.
Netradyne’s senior vice president of marketing, Barrett Young, recently shared his views on positive reinforcement as vital to improving the safety practices of commercial drivers. “If you think about the psychology of truck drivers,” he told Commercial Carrier Journal, “they're proud people. They're proud of their jobs. They work hard at their jobs—arguably some of the hardest workers in our entire economy. And so the last thing they want is to constantly be told that they're doing the job bad, especially when the majority of the time they're not.”
In 2020, more than one in five workplace deaths occurred within the construction industry, and more than one-third of those fatalities resulted from falls, slips, and trips. In addition to saving lives, enhancing construction site safety also helps businesses avoid financial hardships. Each Occupational Safety and Health Administration (OSHA) violation incurs a penalty of up to $15,625, and OSHA estimates that U.S. employers pay nearly $1 billion per week for direct workers' compensation costs.
Construction companies are getting ahead of safety risks by increasing visibility with smart technology, particularly AI-supported cameras. Through photo recognition and 3-dimensional scanning, these cameras can recognize objects and people then use this data to identify hazards such as workers without hardhats, exposure to hazardous materials, and activities being performed unsafely or without the required safety gear.
AI-powered “smart” construction equipment systems help construction operators increase transparency and accountability through consistent monitoring and reporting. Caterpillar’s VisionLink system, for example, delivers a dashboard that conveys the exact location of every piece of heavy equipment and tracks machine health, enabling proactive maintenance to prevent potential safety hazards due to malfunctioning machinery.
AI adds another dimension of safety by enabling some building elements to be produced away from the construction site. Robotic factories can produce certain structural components in a highly controlled setting, removing potential hazards from the site and thus lowering the risks of worker injury.
Tracking adverse drug events (ADEs)—harms resulting from medication that include allergic reactions, side effects, and human error—is a key component in making drugs safer. Every year, adverse drug events (ADEs) cause about 1.3 million visits to the emergency room and 350,000 hospitalizations, costing about $3.5 billion a year.
The U.S. Food and Drug Administration (FDA) tracks ADEs through two systems: the MedWatch Voluntary Reporting System for medical products and the Vaccine Adverse Event Reporting System (VAERS) for clinical vaccines. Manufacturers and healthcare providers are required by law to report every adverse drug event (patients may also submit reports but are not obligated). In a recent interview, Justin Scott, senior business informatics officer at the FDA Office of Business Informatics, revealed that the administration receives an average of 40,000 safety reports a year before a drug goes on the market and 2 million a year after it is released.
Historically, the FDA has relied on human analysts to process adverse event forms. Each reviewer would spend an average of 10 minutes reading each form. For about 10 percent of the forms, another 15–20 minutes would be required to write a report about the possible relationship between the drug and the event. This process alone added up to about 1,000 hours, causing high levels of worker fatigue as well as a high risk of human error.
The FDA turned to intelligent automation to tackle an immense challenge: digitize a 30-year archive of adverse event reports, which encompassed over two dozen versions of forms with over 120 complex fields. The platform uses artificial intelligence to capture and extract vital data and information from each form at an accuracy rate of 99 percent and is expected to save 7,500 labor hours per year.
In that same interview, Scott explained that today, “[analysts] can basically go to a series of reports, take a glance at it, and understand, ‘All right, this is how many people took this product and were hospitalized, this is how many of them were hospitalized and subsequently died’ … Before, where they might get fatigued from reading all these PDFs and notes, now they have the data just presented right in front of them.”
By speeding up adverse event report processing and dramatically reducing the risk of human error, the FDA is helping ensure that problems with medications can be addressed quickly and effectively. Healthcare providers can prescribe drugs with greater confidence in their safety and effectiveness, and patients ultimately benefit from the prevention of future adverse reactions.
These are a few examples of areas where intelligent automation is contributing to a safer future, and there are many more where these came from.
Whether they are delivering feedback that helps drivers operate more safely, tracking machine health to prevent construction-site accidents, or enabling faster, more accurate processing of drug safety reports, AI-guided platforms are enabling unprecedented levels of safety awareness and powering more effective prevention strategies. By processing massive amounts of inputs faster and more accurately than humans, intelligent automation is turning data into actionable insights. The result is an effective collaboration between humans and machines, leveraging the best that each has to offer in building a safer world.