The benefits of artificial intelligence in the workplace cannot be ignored. AI excels at repetitive tasks that require extreme attention to detail for long periods of time. These types of tasks often expose human error caused by distractions or fatigue, two downfalls AI will never succumb to. At the same time, human workers—scientists, engineers, doctors, and more—have skills that artificial intelligence cannot yet even begin to replicate. These experts in their fields, as well as most humans, have the practical judgment we often refer to as common sense. This makes us better suited for making decisions, a task AI often struggles with.
There are simply some tasks that are better suited to machines, while others benefit from humans’ learned experience. Combining the power of these two systems offers a symbiotic solution known as augmented intelligence or intelligence amplification. How is this different from the utilization of AI alone in the workplace? “The key difference between AI and augmented intelligence is one of autonomy.”
Rather than AI making decisions autonomously based on available information, augmented intelligence provides decision support for human decision makers. Using AI to gather all available information to create more complete datasets allows for better, faster pattern recognition and insights. The data becomes actionable and results in more informed decisions. If this sounds familiar, it’s because it’s exactly how InnovationQ Plus® enables critical decision making throughout the innovation lifecycle.
Other industries are putting intelligence amplification to work as well. Healthcare organizations are using augmented intelligence to comb research and identify possible treatment options for individual patients. Retailers use both human and AI “workers” to provide more personalized shopping experiences and customer service. Manufacturing processes and maintenance can be streamlined using augmented intelligence.
You’ll even notice intelligence amplification in your everyday life. For example, personal assistants like Siri, Alexa, and Google Assistant review huge datasets, whether it be your personal calendar or the internet at large, to answer your questions, such as what’s on your schedule for the day and how warm it will be this afternoon. You then use this information to make data-based decisions, such as what to wear for the day.