Artificial Intelligence and Machine Learning for Job Automation: A Review and Integration

Artificial Intelligence and Machine Learning for Job Automation: A Review and Integration

Gang Peng, Rahul Bhaskar
Copyright: © 2023 |Pages: 12
DOI: 10.4018/JDM.318455
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Abstract

Job automation is a critical decision that has brought about profound changes in the workplace. However, the question of what drives job automation remains unclear. This study conducts an interdisciplinary review of five theoretical frameworks on job automation, paying particular attention to the role played by artificial intelligence and machine learning. It highlights the concepts and mechanisms underlying each of the frameworks, compares and contrasts their similarities and differences, and highlights challenges and suggests opportunities of job automation. It also proposes an integrated framework on job automation by addressing the research gaps in extant frameworks and thereby contributes to the research and practice on this important topic.
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Automation

The term automation comes from automatos, a Greek word meaning acting by itself, or by its own will, or spontaneously. Automation has been defined as the performance of tasks by machines (usually computers) rather than human operators (Parasuraman et al., 2000), or a technology that actively selects data, transforms information, makes decisions, or controls processes, as well as exhibits potential to extend human performance and improve safety (Lee & See, 2004). Although automation has been defined in many different ways, the common theme is that automation is about the autonomy of a system or process from human involvement and intervention, and, quite often, it frees humans from time-consuming and repetitive tasks, whether the tasks involve physical activities or simple cognitive activities.

Automation dates back to ancient times when tools were first invented by humans. Early examples of automation include windmills, water clocks, sundials, and self-moving artifacts. During the first Industrial Revolution, automated systems were designed for temperature control, operation of mills, and regulation of steam engines (Bissell, 2009). Many tasks performed by artisans were also automated, such as spinning and weaving in manufacturing (Acemoglu & Restrepo, 2019). Modern automation started during the early 20th century when Henry Ford introduced the assembly lines for mass production. Ever since then, automation has been widely used for various control systems for operating equipment, factory processes, boilers and heat treating ovens, telephone network switches, steering and stabilization of ships, aircraft and vehicles with the purpose to reduce human cost and intervention and improve efficiency and quality (Rifkin, 1995). Automation has been achieved by various technologies including mechanical, hydraulic, pneumatic, electric, and electronics, or in combination (Parasuraman & Wickens, 2008; Williams, 2009). Although automation may not involve computers, it is the computers that have revolutionized automation and made it so widely adopted in every industry today (Janssen et al., 2019).

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