Cognitive Automation and Organizational Psychology

Priming Goals as a New Source of Competitive Advantage

Alexander D. Stajkovic, Kayla Sergent

• Publisher: Routledge
• Year: 2019
• ISBN:
  9781000022957
• Edition: 1
• Topic: Personal Development
• Subtopic: Personal Success

Jobs that were once well-defined are now multifaceted. New realities have placed a premium on employee cognitive processing to fulfill complex occupational roles. But human conscious cognitive capacity is limited, making it nearly impossible for employees to keep up without being overloaded. Stajkovi? and Sergent refute the common assumption that technological automation is the only way forward. Instead, they directly tackle the issue of employee cognitive overload by proposing cognitive automation as an alternative solution. The authors present a sampling of cutting-edge research showing that conscious guidance is not required for all goal pursuits; goal-directed behavior at work can be automated via priming of subconscious goals.

Building on research in social psychology and organizational behavior, Stajkovi? and Sergent introduce four models to explain how subconscious goals are primed in organizations:

•Auto-motive model: Repeated practice with a goal makes cognitive automation possible.

•Goal contagion: Observing and inferring goals of others creates cognitive automation.

•Means-goal priming: Confidence in your goal pursuit enhances cognitive automation.

•A history of reinforcement: Money, feedback, and social recognition used to reinforce goal achievement become associated with the goal, resulting in cognitive automation.

The authors canvas a broad range of knowledge concerning the problem of employee cognitive overload in contemporary organizations and rely on multidisciplinary research to propose cognitive automation as a solution that can address it directly. This book is a deep well of valuable information for those interested in solving real work problems with application of science of organizational behavior (SOB).

Part I
The Problem and Proposed Solution

1 Skyrocketing Cognitive Load Versus the Snail’s Pace of Attentional Adaptation

We open this chapter by illustrating the contrast in job demands in the last five decades. Consider the clarity of description in this job advertisement, posted 50 years ago. In 1968, Radio Manufacturing Company placed a job ad in the London press stating the following:

South city requires intelligent young man, 21–25, as Trainee Supervisor. Applicant should have Leaving Certificate standard of education and some mechanical experience.

Compare the above simplicity to a posting for a similar position at Rite Aid in 2019:

Learn to lead store associates though the execution of company business plans and objectives to drive sales, be profitable, and provide a superior customer and associate experience … Learn to manage an individual store while meeting store retail budgeted sales, margin, labor, expenses, and overall P&L monthly results to ensure operating EBITDA and income are achieved.

The characteristics of yesterday’s jobs are quite different from the job demands of today. In this chapter, we examine how the multifaceted and amorphous nature of modern-day jobs contributes to employee cognitive overload.

Why should you care about cognitive overload? We will provide empirical evidence from multiple sources indicating that employee cognitive overload is causing alarming levels of psychological distress and related health problems.

Could leaders tackle this issue with the existing tools in their wheelhouse? We will describe the competitive landscape of organizations and contend that traditional ways in which companies compete are inadequately equipped to tackle employee cognitive overload. Though these traditional practices have economic benefits, they are too remote to be convincing when it comes to remedying psychological problems.

Overall, data suggest we need new approaches to mitigate employee cognitive overload directly. One approach, as-of-yet unexplored in organizations, is cognitive automation.

The Old-New Jobs Gap

Work of the Past Was Clear and Predictable

By and large, jobs in the first part of the 20th century were clear; people knew what had to be done. Products were manufactured, packed, sold, and shipped. Fields were plowed, and crops were planted and harvested. Those with little formal education had a recourse in industrial jobs that were mostly unvarying and required little in the way of elevated cognitive processing. Once requisite job skills were acquired, performance was largely a matter of execution. Because work behaviors were pre-identified, more often than not, effort led to success; hence, “work hard and play by the rules” was the foundation of the American dream.

Work of Today Is Multifaceted and Amorphous

Those types of employment options are rapidly shrinking. Jobs that were once well-defined are now multifaceted. In terms of macro-economic forces, businesses are progressively shaped by transnational interdependencies. New realities are placing a premium on cognitive processing to fulfill increasingly complex occupational roles. Indeed, because of virtually all-embracing global interconnectedness, what happens in one part of the globe affects the welfare of organizations on the other side of the world. These global economic and cultural forces pressure organizations to adopt shifting missions and customized responses that can be hard for employees to fully understand, let alone to functionally control.

In terms of micro-foundations of daily work, a premium is placed on rapid acquisition of technology. The gap between technological innovation and work adaptation is shrinking. For example, elevator mechanics at Otis are now required to use iPhones to document malfunctions and order spare parts online in real time, even though smart phones may not be their forte. Likewise, employees are faced with expanding communication and cooperation across units. Let us not forget about emails, as there is a general expectation to answer them. Figuring out how the goals of yesterday morphed into new targets today because of new market entries and customer acquisitions, and how this shakes up a unit or an organization, takes another intellectual toll. Shifting work priorities call for added deliberations about new choices and data needed to support completion of a project; this is all wrapped into shrinking margins of error. Moreover, the best laid plans can be undone with one unexpected email from the boss which is why many employees feel that success today requires sleeping with an iPhone. Taken together, the cognitive processing burden placed on today’s employees is accelerating.

To claim that society has not made strides to automate various job demands would be uninformed. By the same token, to ignore the psychological cost of cognitive overload in the modern workplace would be equally foolish. Apropos, we next review evidence from multiple sources, indicating that employee cognitive overload across professions appears to be causing alarming levels of psychological distress and related health problems.

Cognitive Dissonance and Psychological Distress

Compared with tasks employees used to perform, characteristics of the modern-day workplace demand higher levels of information processing. Because adaptation to, and management of, mounting cognitive load requires a corresponding psychological makeover, many employees fear whether they can handle it all (Stajković, Lee, Greenwald, & Raffiee, 2015). A survey conducted by the Institute of Leadership and Management in the United Kingdom found that about 40% of employees reported self-doubt about their performance and career (Flynn, Heath, & Holt, 2011). This discrepancy between job demands and employees’ perceived inability to handle them results in a psychological phenomenon known as cognitive dissonance (Festinger, 1957), in which reality does not match one’s perception of it. When dissonance is reduced, predictability fosters adaptive preparedness, making it more likely a person will surmount predicaments. However, “inability to exert influence that adversely affect one’s life breeds apprehension, apathy, or despair” (Bandura, 1995, p. 1).

The U.S. Department of Health and Human Services (DHHS) uses the term psychological distress to refer to a range of psycho-somatic symptoms, where “psychological distress includes mental health problems severe enough to cause moderate-to-serious impairment in occupational functioning, and they may require treatment” (Weissman, Pratt, Miller, & Parker, 2015, p. 1). Based on the wide-ranging data DHHS collects (Weissman et al., 2015; Pratt, Dey, & Cohen, 2007), this agency concluded that psychological distress in the U.S. is not only rising, but it is at an all-time high. Yet, the education level of the U.S. workforce and living conditions today are far better than ever before (Pinker, 2018).

Employee cognitive overload is not limited to a few high-stress industries. Moderate-to-serious impairments in work functioning caused by psychological distress have been reported across occupations including arts, construction, entertainment, entrepreneurship, management, military, maintenance services, sports, and trucking (Allen et al., 2012; Bruder, 2013; Fan et al., 2012; Gu et al., 2013; Jacobsen et al., 2013; Ng, Eby, Sorensen, & Feldman, 2005; Shockey, Zack, & Sussell, 2017). Neither is cognitive overload limited to just the U.S.; work-related psychological distress affects employees around the globe (Hassard et al., 2014), imposing an economic cost of $200 billion in the U.S. (SAMHSA, 2016), €617 billion in Europe (Hassard et al., 2014), and CA$11 billion in Canada (Chiu, Lebenbaum, Cheng, de Oliveira, & Kurdyak, 2017). Markedly, despite a 65% increase in antidepressant prescriptions for psychological distress in the last 15 years (Pratt, Brody, & Gu, 2017), suicide rates have risen by 25% (Curtin, Warner, & Hedegaard, 2016).

Traditional Ways in Which Companies Compete Are Inadequate to Address the Problem

Although the practices we review next unquestionably reap economic benefits, they do little to nothing to recognize and mitigate employee cognitive overload. We neither venerate nor dismiss these traditional approaches to gaining a sustainable competitive advantage. We simply underscore that these strategies have been leapfrogged by time when it comes to cognitive overload and consequences for employees’ mental health.

Historically, because one purpose of forming an organization was to organize, efficiency was paramount. Efficiency involves making a product or offering a service with the least amount of time, material, and labor. Frederick Taylor’s Scientific Management was the high point of the efficiency focus at the turn of the 20th century. The first cousin of efficiency is scale. Economies of scale have consolidated many industries through mergers and acquisitions since the mid-20th century. As sources of a competitive advantage, efficiency and scale are about competing on lower unit cost. In the 1980s, Edward Deming pushed quality as a new focus in competitive business battles, which manifested itself in two ways. One is that products and services of high quality, e.g., certified by six sigma quality control processes, are more likely to be sold, ceteris paribus. The other is that higher quality products allow for a pricing premium. For every Southwest Airlines that earns margins via cost austerity, there is an Emirates Air that competes on luxury.

Many organizations still concentrate on these traditional sources of competitive advantage. The economic benefits of these strategies are undeniable. At the same time, they are tangential to substantively addressing mounting employee cognitive overload.

At a more micro level of analysis, organizations offer, almost in unison, more education as an answer to calls for continual growth, doing more with less, and above and beyond performance. Upgrading existing skills, mastering more academic subjects, and regulating learning by finding new ways of thinking are sensible alternatives; except, each one elevates the demand on attentional processing. Minimizing the frequencies of task switching, providing clearer and more instrumental feedback, being more careful in delivering negative evaluations, and reducing work interruptions can help reduce cognitive load (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001), when feasible. The extent to which these procedures are enacted regularly is uncertain in light of escalating competitiveness and decreased time spent by companies on employee development (Cappelli, 2012). That is, research continues to show that employee cognitive load still impacts risk aversion (Benjamin, Brown, & Shapiro, 2013), impulsive behavior (Getz, 2013), unethical choices (Gino, Schweitzer, Mead, & Ariely, 2011), and stereotyping (van Boven & Robinson, 2012), and it also impairs judgement (Duffy & Smith, 2014).

New Approaches Are Needed

Given the pervasive negative effects of cognitive overload on a host of outcomes, a skeptic might conclude the extant approaches to mitigate load are not being used, not being used properly, or are not working. Because employee attentional processing capacity appears to be maxed out and because human “broadband” capacity is neither easily nor rapidly upgradable, conscious remedies can Experate the already undulating employee cognitive load. It may be a bitter pill to swallow, but business professionals must recognize the biological fact that the attentional processing band employees have today is not all that broad, and it will not change during our lifetime. Instead, we call for consideration of a new employee “broad” band—subconscious processing via cognitive automation.

This proposal sets up the spontaneous question, “Why not use artificial intelligence instead of exploring the workings of the subconscious mind?” The future may bring brain-boosting power, for example, via CRISPR designer-minds. Someday, brains might be upgraded with new genes or with 3-D printed younger brain components. So, why go into the “unknown” depths of the subconscious when technical solutions appear auspicious?

First, we retort by asking, “Why is “artificial” intelligence better than real human intelligence?” Was it the oversight of God or evolution that human processing be inferior to an artificial commingle? If so, is it the responsibility of businesses to fix human cognitive shortcomings with mechanical solutions, for profit, of course? As it stands, the effectiveness of blending the mind with artificial “intelligence” (AI) in organizations is untested, to say nothing of it being legally unregulated and morally unclear. These concerns do not nurture implementation anytime soon.

Second, development of AI requires investment, is expensive to purchase and use, and requires electricity or batteries at all times. Using AI instead of human constituents could even be awkward. For example, a person can carry an iPhone on a date, but imagine if he asked Siri for advice midstream because the situation changed. Even if our parody of today becomes the reality of tomorrow, what if the gadget runs out of juice?

Third, the perpetual need to sell something coupled with the need to recuperate the sunk cost of investments has made businesses occasionally impervious to social considerations. Although many professionals are mesmerized by AI, few discuss if the fusion of human brains and AI would deepen social divisions. Given the rapid pace of AI advancement, it is not far-fetched to foresee a moral quandary where natural giftedness of a poor child is relegated by an artificially enhanced mind of a wealthier child. How would this scenario play out in standardized testing? If the scores should be adjusted, then what is the point of using AI in the first place? Many forget that when IQ testing was first used in Great Britain, it was meant to identify kids with high IQ who were from the lower social strata to afford them greater opportunities in society than what their social status would otherwise predict.

Fourth, maybe insistence on AI is drawn from a perception that artificial processing that costs millions is decidedly more powerful than the natural, God- or evolution-given human brain. The reasonableness of this assertion depends on what is compared. If AI is equated to conscious processing, AI wins. But, we have long known that consciousness is limited. Subconscious processing, though, outperforms AI. For instance, in 2013, the technology company Fujitsu used one of the most powerful super-computers at the time to simulate human brain processing. Even though this “super” computer connected 83,000 of the fastest processors, it took it 40 minutes to simulate 1 second of 1% of human brain activity.

Until a society agrees on how to handle the possibility of purchasing genetic upgrades, perhaps real human processing ought to be considered before going “all in” on artificial. To be sure, we are not dismissing the benefits of technology. Instead, we are asserting that a premature...

Table of contents

• Cover
• Half Title
• Series
• Title
• Copyright
• Dedication
• Contents
• Introduction
• Part I The Problem and Proposed Solution
• Part II Theory Foundations
• Part III The Latest Empirical Research
• Authors’ Biographies
• Index