Your New Coworker Could Be AI-Powered

April 16, 2020 By Paul Golata, Mouser Electronics

Heigh-Ho, Heigh-Ho, Off to Work We Go 

After a long day in the mines digging for diamonds and rubies and other precious stones, the Seven Dwarfs marched forward singing “Heigh-Ho, Heigh-Ho, its home from work we go.” Disney’s animated film Snow White and the Seven Dwarfs (1937) introduced us to these lovable characters who exemplified many different personalities and worked together day in, and day outThis eclectic troop of coworkers sure enjoyed one another’s company while working the day away. Hopefully, you love your job as much as the Seven Dwarfs love theirs.  

Although it is unlikely that you are working with any coworkers named Bashful, Dopey, Grumpy, Happy, Sleepy, Sneezy, or Doc, one thing is sure; you are going to be getting a new coworker. Artificial Intelligence (AI) is coming to transform the workplace. If the Seven Dwarfs are any indication, coworkers who even have distinctly different characteristics, styles, and traits can still work alongside one another and achieve great things. This article will introduce you to this new coworker of tomorrow and look at some of the coming changes to how work will be performed.  

Transformation of the Workplace 

In all processes, including human work, change is inevitable. With our cutting-edge and ever-expanding developments in artificial intelligence (AI) technology, along with AI’s ability to enable increasing levels of automation, the workplace of tomorrow will transformOur workforce will get augmented with robots and cobots (collaborative robots that work with humans in a shared space). Already deployed in manufacturing, robots will move into the office and workplace environment where humans will be in direct contact with them. Routine clerical tasks and functions will increasingly become automated, yielding improvements in administration, efficiency, safety, and training. This workplace transition will not be the first nor the last in human industry. Over the past several centuries, several significant workplace transformations have taken place. Let’s examine what causes dramatic disruptions to the workplace. 

A Disruption in the Workplace 

Microeconomics believes that individual choices are based upon people behaving rationally for what is in their best and proper interest. The theory assumes that individuals are utility-maximizing and that firms are profit-maximizing. The supply and demand curves of individuals and firms meet at the place known as market price. Markets are understood to be in equilibrium at which point no rational person will change this behavior. This is also the point where supply equals demand. 

Creative destruction is process whereby the mutations and changes within an industry ultimately revolutionize its internal economic structure from the inside out. It is the destruction and shedding of an old skin with a replacement by a new one. It is revolutionary disruption (Figure 1). Let’s take a look at some of the critical workplace transformations that have happened over approximately the past 250 years. 

Figure 1Economic changes lead to creative destruction, which brings disruption of the status quo to industry. (Source: Mouser Electronics) 

Revolution Industry 1.0

Around the time of the founding of the United States (1776), Scottish economist and philosopher Adam Smith (1723-1790), developed the idea of “the division of labor.” Smith wanted to produce a defining work along the lines of Isaac Newton’s (1643-1727) Mathematical Principles of Natural Philosophy (1687) that would boil down economics to a single and ultimate principle. Smith’s ideas were an articulation of the labor theory of value. These ideas led to an industrial revolution in the late 18th and early 19th century. Workplace transformation was characterized by a movement away from primarily biological in the form of humans and animals, toward a workplace where machines powered by water (H2O) and steam provided increased effectiveness and efficiencies. 

Revolution Industry 2.0

Roughly a century and a half ago, thinkers and engineers, including Thomas Alva Edison (1847-1931), sparked a new workplace transformation. The age of steel and electricity had arrived. Lightbulbs, trains, automobiles, skyscrapers, and a host of related developments provided mobility, moving masses of people from the farms toward the cities, introducing into the workplace mass-production techniques increasing worker productivity.  

Revolution Industry 3.0

The invention of the semiconductor and integrated circuits (ICs) around1959 spawned the electronic and computer age as characterized by the rise of the mobile phone and internet. Workplace transformation came rapidly as the digital world allowed physical boundaries to be transcended. The ability to program machines and send information in real-time practically anywhere shifted jobs from mass-production activities toward decentralized centers of core competency.  

Revolution Industry 4.0

Industry 4.0 rides on the back on Industry 3.0, taking it further and farther by providing digitization of value, products, services, and business models. This is done primarily by way of the Internet of Things (IoT). IoT enables the connection of cyber-physical systems through wireless connectivity and smart sensors. Combined with recent advances in low-power microcontrollers, these new "things" are being connected to the internet quickly and inexpensively. 

Ally or Adversary 

AI is part of the move into Industry 4.0. As AI enters the new era workplace, will it be a friend or foe of workers (Figure 2)? 

Figure 2: Is AI an ally or an adversary? It depends on how humans view it. (Source: Mouser Electronics) 

There are no longer as many people employed in Industry 1.0, 2.0, or 3.0 jobs as before. As the employment moves more toward Industry 4.0 jobs and away from Industry 3.0 jobs, this creative disruption will certainly impact jobs, including your own. The horse and buggy gave way to trains and automobiles. You and I are not immune to impending changes.  

AI will increase our productivity of deploying capital and labor in the workplace while simultaneously shifting how collective and individual industrial tasks get allocated. Some jobs will no longer be needed as AI makes them expendable. Others will require partial or total transformation. The individuals and organizations that are proficient at adjusting to the advent of AI’s impact will find themselves at a competitive advantage in a workplace landscape that has cyber-physical systems working together more effectively than pre-Industrial 4.0 models. 

Getting a Competitive Advantage 

AI is enabling a new range of competitive advances in the workplace. One of these is robots. Robots are machines that can perform jobs and tasks that in some manner mimic, emulate, or transcend human capabilities. Robotics technology depends heavily on motors, motor controls, sensors, and processors.  

AI also enables various new automation processes to be incorporated. Automation removes or eliminates humans from repetitive manual tasks. Automation helps ensure that operationget performed the same. It also increases efficiency, reduces waste, increases output and quality, improves safety, and allows for multitasking (Figure 3).  

Figure 3Successfully harnessing AI will allow companies to achieve competitive advantages. (Source: Mouser Electronics) 

I work at Mouser Electronics, who is a leader in state-of-the-art distribution advancements. Mouser is a leader at bringing automation into the workplace. The company implemented state-of-the-art Vertical Lift Modules (VLMs) at its global distribution center. VLMs—essentially giant vertical filing cabinets, complete with shelves and an automated elevator—store tens of thousands of electronic components. When activated by the employee, the VLMs deliver the parts directly to the workstation, vastly increasing efficiency and floor space. The automated machines can reduce an employee’s walking time by 45 percent or higher. Mouser now has 55 Vertical Lift Modules—including 11 brand new modules 

Many other leading companies, including Amazon, take advantage of automation equipment. Amazon is a company that is actively looking into how robots can assist their warehouse and distribution activities. Automation is made easier when machines can learn. 

Machine Learning  

Learning is the gaining of knowledge by studying, experience, or being taught. Machines can learn. This is known as machine learning (ML). ML is a subset of AI that relies upon statistical methods to improve itself over time. ML trains itself by first studying structural descriptions from known data examples. The machine is then allowed to proceed on its own and examine new structural descriptions that are not part of known data examples. By way of comparison, evaluation, and feedback, it “learns.”  

ML Will Change Human Tasks  

Human work is vast and various. Humans are capable of thousands of tasks. Those most suitable for being impacted by ML are of a specific type. These tasks are those that ML will have definitive advantages over humans. 

Here is an example evaluation of jobs and tasks with the introduction of AI: 

Humans > Machines: What jobs and tasks do humans do better than ML? 

Machines > Humans: What jobs and tasks does ML do better than humans? 

Most jobs will have one or more of the human tasks that are fitting for ML to take over specific tasks. Some jobs might have a very high percentage of tasks that can be taken over by ML. Wherever ML gets introduced will require both the organization and the individual worker to make adjustments in how they execute their workplace roles. Additionally, as ML steps in to assume human tasks, a new set of reflective questions may be asked. What jobs and tasks would it be best for humans to perform to create economic value? How can existing and new people be trained/retrained to create the most value? 

Here is an example evaluation of jobs and tasks with the introduction of AI: 

Creating value: What jobs and tasks would it be best for humans to create value? 

Human learning to unleash this value: How can existing and new people get trained/retrained? 

Presently the number of changes to humans’ jobs and tasks because of the implementation of ML is relatively small. In general, humans excel at creating value relative to ML in jobs and tasks that require personal attributes that enable someone to interact effectively and harmoniously with other people. 

Conclusion 

Absent the company of the Seven Dwarfs; I sit alone in my office wondering:  what’s next? I can’t help but consider some of the coming changes to the workplace as AI transforms and reshapes its landscape. Disruptions enter and ultimately become the new normal. Workplace changes can be taken as good or bad based upon the context and the subjective viewpoint of those impacted. Moving forward, society should adopt a strategy where human work migrates toward where it excels relative to AI, ML, and automation. When you finally meet your new coworkerAIyou can teach it how to whistle while you work, making it a happier and more productive workplace for us all. 

Author 

 

Paul Golata joined Mouser Electronics in 2011. As a Senior Technology Specialist, Paul contributes to Mouser’s success through driving strategic leadership, tactical execution, and the overall product-line and marketing directions for advanced technology-related products. He provides design engineers with the latest information and trends in electrical engineering by delivering unique and valuable technical content that facilitates and enhances Mouser Electronics as the preferred distributor of choice. 

Before joining Mouser Electronics, Paul served in various manufacturing, marketing, and sales-related roles for Hughes Aircraft Company, Melles Griot, Piper Jaffray, Balzers Optics, JDSU, and Arrow Electronics. He holds a BSEET from the DeVry Institute of Technology (Chicago, Ill.); an MBA from Pepperdine University (Malibu, Calif.); an MDiv w/BL from Southwestern Baptist Theological Seminary (Fort Worth, Texas); and a PhD from Southwestern Baptist Theological Seminary (Fort Worth). 

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