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Science Outlines Three Types of Work Addicts

When Productivity Becomes a Problem

By Caroline Campbell on Aug 13, 2020

Editor Note: Understanding the importance of this timely topic and to ensure that research is made available to the wider academic community, IGI Global has made a sample of related articles and chapters complimentary to access. View the end of this article to freely access this critical research.

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With many businesses now operating fully online, experiencing continued layoffs, and adapting to the turbulence of the economy, many employees are now faced with longer hours, a higher workload, and untraditional schedules. Through the manifestation of this new workplace normal, employees are becoming hyper-focused on being productive and showcasing their value, which is accelerating the positive association of a busy lifestyle with success. 

However, according to a recent BBC article, this increase in work and focus on productivity can manifest into an addiction. Experts relate the feeling of “accomplishment” to drugs, gambling, eating, or shopping. Whether employees crave recognition or a salary increase, many fall into the three productivity types:

  1. Efficiency Obsessive: These individuals are hyper-organized and focused on the details. They are focused on the smaller things and are “masters of the inbox zero.” However, they do not focus on the larger picture and will not know the difference between efficiency and effectiveness.
  2. Selfish Productive: These individuals are focused on their own goals and will not work well in team environments. They are focused on the “big picture”; however, it will be altered to fit their needs or agenda.
  3. Quantity Obsessed: These individuals focus productivity on how much they output. They equate the number of tasks completed with success and are more focused on crossing off everything from their unrealistic to-do lists.

Although it may seem like working more hours or being focused on being “productive” will make an employee an asset, the long-term effects of over-working can lead to performance issues and a decrease in the individual’s mental and physical health overall. To further investigate this ongoing phenomenon and prevent work addiction, Prof. Shalin Hai-Jew, from Kansas State University, USA, outlines why work is meaningful beyond survival and how it is easy for work to become a catalyst of human identities, self-actualization, self-expression, sociality, and other aspects in her chapter “How and Why Is Work Meaningful (Beyond Survival Needs)?: Setting a Baseline,” from Maintaining Social Well-Being and Meaningful Work in a Highly Automated Job Market (IGI Global). View the chapter below:

Maintaining Social Well-Being and Meaningful Work in a Highly Automated Job Market
Prof. Shalin Hai-Jew (Kansas State University, USA)
Copyright 2020 | Pages: 333 | ISBN: 9781799825098 | EISBN:9781799825111

This publication a pivotal reference source that explores how the world will re-shape as one with less demand for human labor and how to potentially balance how people engage as part-workers and as consumers of others’ creations. Additionally, the book looks at how people will co-create meaningful lives at micro, meso, and macro levels...Learn More.

In a time of fewer jobs, at the lived level, people take on a variety of behaviors. They may make do with less and downsize. Those who are older workers may simply retire earlier than planned. They may monetize their skills by taking on additional jobs. They may work in a gig economy. They may sell some of their possessions. They may rely on family and friends and colleagues for survival. They may tap into government programs, if eligible, or rely on the kindness of others and use social services from food banks and shelters. Or they may engage a number of different strategies and tactics, to ensure that basic survival needs are met—for food, shelter, healthcare, and other foundational needs.

At a lived level, when asked, people may identify various needs that may be met through their work beyond subsistence. They may point to values which are expressed, such as military personnel who enable national security, weather service personnel who enable weather-awareness for various types of preparedness, artists who explore human identity and the universe and aesthetics, teachers who empower learners, and so on. For individuals, they may point to aspects of themselves who can be expressed through their work endeavors; they may point to a sense of their own identity and meaning-making through their professional roles; they may point to aspects of their work lifestyles that inform their sense of personal meaning, and others. If asked what people might do if they had less access to work, there are a variety of responses as well. Some express welcome at having a less demanding work schedule. Others say that they will shift their attention to some of their current non-work interests. Others say that they will pursue part-time employment. Beyond the personal, the academic research literature offers some insights on what of work is personally meaningful. Setting a baseline for what makes work meaningful may support public awareness and policy-making endeavors in this public-private free market space, in light of the advent of the Fourth Industrial Revolution (4IR).

Technological Change and Transitions to New Job Realities

Advances in computational capabilities, artificial intelligence (AI), cloud-based computing, mobile computing, sensor networks, robotics, computer vision, machine learning, data analytics, and other capabilities have meant that new functions are coming to the forefront of the human workplace. These include applications “not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine” (Rotman, Aug. 2, 2013). AI enables machine creativity, machine learning, machine artwork, machine-generated music, and other endeavors.

What is the current state-of-the-art? Machines are used to automatically harvest fruits and vegetables and grains, in many cases, lessening the need for human labor. News stories are written by algorithms in many cases [and research in one country found both journalists and the general public preferring the work of the algorithms to human journalists because of “the public’s negative attitude toward journalists’ credibility and craving for new information and communication technology (ICT) products/services” (Jung, Song, Kim, Im, & Oh, 2017, p. 291).] Robotics are seen as inevitable for service-based organizations, based on an exploratory research study (Qureshi & Syed, 2014). Social robots engage on social media, with humans often unable to tell the difference between machine or person or cyborg (mixed machine and human embodiment in the social account). Smart tutors and other automated agents have been deployed in education. With the automation of education, many fear that teaching jobs will disappear (Wasfy, Wasfy, Peters, & Mahfouz, Nov. 2013).

The definition of robots differs “substantially from the term just a decade ago” (Thrun, 2004, p. 2); in one work, robots have to be able to think and be somewhat autonomous (Lin, Abney, & Bekey, 2011, p. 943). Other works expand the definition of robotics from the traditional “hard” robotics to “soft” ones involving a variety of different materials and capabilities. If robots in the past were brought in to perform works that were the “three Ds” or “dull, dirty, or dangerous” (Lin, Abney, & Bekey, 2011, p. 944), they have newer roles in which they replace humans almost across the board. One researcher writes:

The uniqueness of the AI technologies is their potential to supplement, substitute and amplify practically alltasks currently performed by humans with critical consequences for firms that must achieve significant productivity improvements to stay competitive, but at the same time raising the possibility of increased unemployment. (Makridakis, 2017, p. 55)

Given their rising capabilities and design complexity, there is widespread concern that machines will take over people’s jobs and leave them without work or only low-paid work. This sense of fear has been around such the time of the Luddites, in the early 1800s. One author observes: “There have been periodic warnings in the last two centuries that automation and new technology were going to wipe out large numbers of middle class jobs” (Autor, Summer 2015, p. 3). Another author cites English economist David Ricardo, who in 1821, expressed concern about machinery and their effects on “the labouring (sic) class” (Chelliah, 2017, p. 1). Another researcher suggests that in the modern era, the fear of technology resulting in fewer human jobs has been around since the 1930s but has not truly materialized (Lohr, Oct. 23, 2011).

Some predict that the advent of high tech will mean more jobs at the higher and lower ends of the wage scale but less in the middle, and there are ideas that people will need more education and skills for non-routine cognitive work (Goos & Manning, Feb. 2007). Industrial workers, for example, experience declining wages with the introduction of robotics in manufacturing (DeCanio, 2016). Workforce polarization may lead to greater wage disparities and the phenomenon of haves and have-nots. Some researchers suggest that the popularization of AI will create unique jobs that “that look nothing like those that exist today” (Wilson, Daugherty, & Morini-Bianzino, Summer 2017, p. 14); they point to Accenture’s global study of over a thousand companies that identified three new categories of “uniquely human jobs” (trainers, explainers, and sustainers), including “smart-machine interaction modeler” and “transparency analyst” and “automation ethicist” and “automation economist,” among others (Wilson, Daugherty, & Morini-Bianzino, Summer 2017, p. 16). Others suggest that humans have an important role in technologies, which require a human in the loop (to use an information technology phrase). “Heteromation” or the centrality of human labor in technological systems suggests that human labor will continue to be relevant (Ekbia, Nardi, & Šabanović, 2015, p. 1). Another researcher pointed to how automation substitutes for human labor but also complements it and helps to “increase productivity, raise earnings, and augment demand for labor” (Autor, Summer 2015, p. 5). Robotics in a firm can increase the survivability of the organization and its employees (Fernandez, Gutierrez, Ruiz, Perez, & Gil, Summer 2012). Suggesting that technological advancements result in a simple lessening of available jobs may be inaccurate and too simplistic. Computational technologies in work places have always required higher skill levels and the need to upgrade skills (Autor, Katz, & Krueger, Nov. 1998).

Researchers have harnessed data and machine learning to predict future employment susceptible to computerization (and obsolescence for human workers) down to the actual professional roles in the U.S. labor market (Frey & Osborne, 2017). The idea that “up to half of all jobs in western industrialized countries are at risk of automation in the next 10 to 20 years” but may be an over-estimation and closer to 9 – 38% US job drops (Arntz, Gregory, & Zierahn, 2017, p. 157). Regardless of outcomes, in the mainstream literature, articles suggest that the dynamic is “AI” and “automation” and “robotics” vs. human jobs. Some academic research works explore different policy approaches to address anticipated challenges.

Some researchers explore ways to encourage human acceptance of robots in service industries, medicine, and other fields. They’ve identified a human preference for social robot personas that align with social stereotypes (Tay, Jung, & Park, 2014), given a human tendency to anthropomorphize robots (and even desktop computers, for that matter). People tend to respond more socially to computer representations that are depicted as human; their increased sociality has been observed in terms of “users’ social judgment and homophily perception of the agents, conformity in a choice dilemma task, and competency and trustworthiness ratings of the agents” (Gong, 2008, p. 1494). The personality of a self-driving vehicle may increase riders’ trust in the technology (Waytz, Heafner, & Epley, 2014). Some see the sense of anthropomorphism senses of computers as more mindless than mindful (Kim & Sundar, 2012).

Before the computer, the animals, mortal though not sentient, seemed our nearest neighbors in the known universe. Computers, with their interactivity, their psychology, with whatever fragments of intelligence they have, now bid for this place. (Turkle, 2005, p. 285)

If people are looking to bond with computers and smart machines, they also tend to pursue a sense of meaning in their lives, and for many, their work provides a major sense of value and self-worth. People’s sense of their own “free will” or ability to take independent action free from internal and external controls (Moynihan, Igou, & van Tilburg, 2017, p. 54) and their social sense of belongingness both contribute to “a sense of meaningfulness” (Moynihan, Igou, & van Tilburg, 2017, p. 61), which is considered a core human need. (People without a sense of life meaning may tend towards absurdism, a sense of a purposeless universe, but they are striving against an internal sense that the world should make sense or be somewhat ordered.)

No matter how the advent of technology adoption manifests, many people are likely to be affected by the transitions. There may be some who are educated but jobless and making do with limited housing or staying with family or friends and adjusting in other ways.

Meaningful Work

An amateur or folk assumption lies at the core of this work, that people expect more from their work than mere pay and that work may be meaningful beyond meeting basic needs for survival. Anecdotally, human work is not just work. For example, people put work into their social media profiles as core parts of identity and personal values.

Interested in Reading the Rest of the Article? Access the Full Article Through IGI Global’s InfoSci-Demo Account, here.


Understanding the need for research around this topic and how employees and businesses can adapt and be successful in the “new normal,” this research is featured in the publication Maintaining Social Well-Being and Meaningful Work in a Highly Automated Job Market (IGI Global), edited by Prof. Shalin Hai-Jew, from Kansas State University, USA. This title is a pivotal reference source that explores how the world will re-shape as one with less demand for human labor and how to potentially balance how people engage as part-workers and as consumers of others’ creations. Additionally, the book looks at how people will co-create meaningful lives at micro, meso, and macro levels. While highlighting topics such as mobile technology, positive psychological capital, and human capital, this book is ideally designed for technologists, AI designers, robotics designers, policymakers, social engineers, CIOs, politicians, executives, economists, researchers, and students.

It is currently available in print and electronic format (ISBN: 9781799825098; EISBN: 9781799825111) through IGI Global’s Online Bookstore at a 20% discount, and is featured in IGI Global’s InfoSci®-Books database (5,900+ e-books). Recommend this publication and the InfoSci-Books database to your library to have access to this critical research, as well as thousands of other research resources, including the chapters below, in the IGI Global InfoSci-Books database.

Complimentary Research Articles and Chapters on Business Culture, Employee Burnout, and Productivity:

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