Technology and people are central to the success of modern organizations. This chapter explains the creation of the people as technology (PT) concept by providing a synopsis of the case from which the concept originated. Enhancements for the PT concept are discussed along with ways that education and training of employees increases organizational opportunities for success. The chapter also provides details of ways that the COVID-19 pandemic impact forced changes in organizational policies and procedures and emphasized the need for better people and technology interactions.
TopBackground
In capitalist societies money is central to practically all interactions when goods and services are involved. Without a monetary value, goods and services are deemed to be less valuable. Despite the end of slavery in civilized societies, people and their capabilities are still monetized. Although slaves were never paid, they were sold and exchanged for their knowledge, skills, and abilities (KSAs) to perform work needed by their owners. While not equating workers to slaves, the construct still exists in workplaces today. Employees’ and technology’s value are measured by their KSAs. Hoskisson et al. (2008) stated that value was being “measure[d] by a product’s performance characteristics and by its attributes for which customers are willing to pay” (p. 101). Can we then say that people performance is based upon their personal characteristics and their attributes that the organization is willing to pay for (Hughes, 2012)?
Value is often equated with money in organizations, but what truly is money? The monetary value of things has been continuously debated (Friedman, 1994; Marx, 1906). The exchange value or purchasing power of money is foundational within a capitalist society. How is value of people and technology relative to the competitive advantage of an organization? People value is more difficult to define and describe than some technology value in the workplace; yet the workplace is inefficient without both values. AI and other emerging technologies became prominent during Industry 4.0 (Klingenberg et al., 2022). AI and machine learning have become difficult technologies to define and describe so explainable AI (Arrieta et al., 2020) has become an area of study for researchers. It seems that the more computer programmers seek to make technology that relates to people functionality, the more complex and indescribable its application becomes. They are also seeking to understand how to make AI more ethical (Formosa & Ryan, 2021).