A Classical Uncertainty Principle for Organizations

A Classical Uncertainty Principle for Organizations

Joseph Wood (U.S. Army, USA), Hui-Lien Tung (Paine College, USA), James Grayson (Augusta State University, USA), Christian Poppeliers (Augusta State University, USA) and W.F. Lawless (Paine College, USA)
DOI: 10.4018/978-1-60566-026-4.ch087
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Abstract

After this article introduction, we review the prevailing theory of organizations, and what it means to organizational science and the new discipline of Quantum Interaction to have an uncertainty principle (ir.dcs.gla.ac.uk/qi2008; the corresponding author is one of the organizers). Further into the background, we review control theory for organizations and its importance to machine and human agents; we review the hypothesis for the uncertainty principle; and we review the status of the field and laboratory evidence so far collected to establish the uncertainty principle for organizations. Then we review future trends and provide the conclusion.
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Background

At the first Quantum Interaction conference, held at Stanford University in the spring of 2007, a panel addressed whether QI was relegated to being a metaphor or whether it could function as a working model that could be applied in an agent-based model to solve social problems like organizational decision making. Of the 24 papers presented at this inaugural conference, few put forth a working model with sufficient details to be falsified. We accept the challenge by proposing in this review a path forward to a working model.

Rieffel (2007) suggested that few advantages accrue from claiming that the quantum model is applicable to the social interaction when it is not, and few disadvantages from applying an uncertainty principle to demonstrate classical tradeoffs, as in the case of signal detection theory, or to demonstrate nonseparability when the tensor calculus fails to hold. In response, the model should lay the groundwork to demonstrate classical effects of the uncertainty principle for organizations.

As an example from common experience, movie entrepreneurs manipulate individuals en masse with entertainment exchanged for payment, as in the joint viewing of a Clint Eastwood movie where individual brains have been found to “tick collectively” (Hasson, Nir, Levy, Fuhrmann, & Malach, 2004). For organizational tradeoffs, the uncertainty principle means that under interdependence, the probability of applying sufficient attention to a plan or to execute it shifts uncertainty in an opposing direction, and vice versa, iff the state of interdependence continues (Note: the symbol iff means “if and only if”).

The interdependent tradeoffs to control a system requires channels that enhance the ability of management to diminish the destructive interference from inside or outside of an organization. It means that tradeoffs form cross-sections that reflect defensive and offensive maneuvers to expand or limit the size of an organization. Tradeoffs mean that as perspectives shift, what is observed to change in an organization also shifts (Weick & Quinn, 1999); that illusions are fundamental to organizational hierarchies (Pfeffer & Fong, 2005) by driving or dampening feedback oscillations (Lawless, Whitton, & Poppeliers, 2008); and that tradeoffs explain why criteria for organizational performance has been intractable (Kohli & Hoadley, 2006).

We define illusions not as false realities, but as bistable interpretations of the same reality that can only be held simultaneously by neutrals while “true believers” drive neutrals to weigh one and then its opposing reality, for example, an ideology of nuclear waste cleanup or the concrete steps needed for cleanup. Single ideological views are usually driven by strong-minded agents who we represent as forcing functions, f(t), where the valence of each marginal element of fact they present to neutrals is represented by one bit of additional information. Illusions entangle only neutral agents not wedded to either competing view, where the valence of both views is represented by two bits of entangled information. Courting neutrals to decide outcomes moderates the heated debates between opposing drivers; when neutrals abandon the decision process, it becomes volatile and unstable (Kirk, 2003). Tradeoffs can reduce the effect of illusions by decreasing the volatility in organizational performance that produces “gridlock” (Lawless et al., 2008).

Key Terms in this Chapter

Tradeoffs: Occurs when one aspect of a phenomenon, such as its resolution, is improved while another aspect is lost or degraded.

Fourier Pairs: The Fourier transform and its inverse form Fourier pairs; e.g., f(t) <--> F(w)

Fourier Transforms: A representation of a signal received over time can be transformed into harmonic frequencies in the frequency domain. A uniform sine wave is transformed into a single frequency. The Fourier transform and its inverse are also known as harmonic analysis.

Uncertainty Principle: Applies when a system with a pair of observables, such as the factors of action and observation, that are not independent, but rather interdependent, precluding a precise knowledge of both observables simultaneously.

Social Influence: Occurs when an action on one or more individual(s) affects the other individuals in a group of two or more agents.

Interdependence: Occurs when two or more objects influence each other. Also, mutual sensitivity, mutual connectedness, or where an action on one object affects the other(s).

Entanglement (quantum): Occurs when one quantum object enters into a (quantum) superposition with another, characterized by having a mutual influence on each other that requires a description of both with reference to the other whether or not spatially separated.

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