Modern software companies, computer science research facilities and even the entertainment media have long touted the importance of artificial intelligence (AI) and its inevitable impact on the future of all our technological fields. Current endeavours have proved that assertion to be true, as talk of AI has already infiltrated a multitude of industries and has already been used to varying degrees.
From companies like Twitter or Facebook using their machine learning algorithms to suggest content to their user’s based on their likes and interests, to schools like the University of Wisconsin creating an AI algorithm to detect COVID-19 pneumonia in otherwise asymptomatic patients within seconds, or hit TV shows like Westworld grappling with the psychological and philosophical notions of artificial thought and feeling, AI has been a hallmark of technological advancement in software engineering.
Driving Artificial Intelligence
Yet, while the focus on AI is high, it runs the risk of becoming either too lofty, or otherwise too ambiguous to effect any practical impact on day-to-day activities within the current workforce. In order to ensure a workforce that can evolve with the growing needs of a large scale economy, the operations directing that workforce need to be as streamlined and transparent as possible. Therein lies the crux of the matter. Assisting human workforce operations are what can, and arguably should, drive the efficacy of AI today and into the future.
The idea is simple. By assisting in operational management you can boost the efficiency of a workforce. The interesting thing about this is that AI-assisted operations needn’t be tackling some overly complicated workload distribution scheme to be significantly impactful. Rather, an AI mechanism that boosts productivity in operations needs to only do two things: (1) remove otherwise mundane decision points from managers and workers, and (2) craft and display correlations based on information aggregated across the entire system as a whole. By removing the smaller decision points, managers are freed to use their lifelong expertise to make decisions where it really matters, aided by the AI’s correlation of various data points that make the system physically visible to the human eye. Likewise, for workers it allows them to focus on getting the job done, rather than having to wrestle with the best way to perform an operation or knowing what operation to perform and when.
Implementing Artificial Intelligence
Following this line of thought, software companies like Chekhub have begun to set the stage for implementing an AI framework that focuses on boosting the quality of operations management on national or local levels. As their software expands, the use of key AI algorithms can allow software systems to learn what correlations to make and display, and allow the system to make the minute decisions on an otherwise large-scale operation. With that in place, it ultimately leaves managers and workers to be focused on implementing their key skill sets, all while allowing for any organization to easily handle reliable, and repeatable processes across a wide scale.