The Groundless Use of Linearity in Daily Thinking and Decision-making

László Duma

doi:10.3311/ppso.14900

Abstract

The overuse or groundless use of linearity, that is the fallacy of omnipotent linearity, intertwines our everyday lives and decisions. The misconception of linearity is not an isolated phenomenon, yet we do not handle this question in the proper way. The examples of MPG (Miles per Gallon) and MPH (Miles per Hour) or driving speed have something else in common: there is a widely used indicator conveying a false impression about the nature and physical, economical effects of the described phenomena by creating the illusion of linearity, leading to faulty decisions. In this paper, I show the common cases where we often make linear mistakes, and for which I can give illustrations drawn from scientific publications or everyday examples. Fresh survey research has been done in order to reveal the presence of linearity in the daily decision-making in terms of its groundless use. The article also identifies some common roots to the problem; it also outlines the psychological mechanisms and possible policies to help avoid them.

Highlights

The overuse or groundless use of linearity, that is the fallacy of omnipotent linearity, intertwines our everyday lives and decisions
The examples of MPG (Miles per Gallon) and MPH (Miles per Hour) or driving speed have something else in common: there is a widely used indicator conveying a false impression about the nature and physical, economical effects of the described phenomena by creating the illusion of linearity, leading to faulty decisions
Fresh survey research has been done in order to reveal the presence of linearity in the daily decision-making in terms of its groundless use

Summary

Introduction

The overuse or groundless use of linearity, that is the fallacy of omnipotent linearity, intertwines our everyday lives and decisions. Our individual decisions as network users impair the value of the entire network and all other users factorially Another practical example of negative network effects at work is the so-called Brooks' law, which says "adding manpower to a late software project makes it later". The key elements here are the nodes with extraordinarily high number of connections, making these networks scale independent In these small-worlds, networks with shortcut connections the distance between two nodes increases in non-linear proportion to the size of the graph but only logarithmically, that is degressively (Albert and Barabási, 2002). I will discuss this issue further in the second part of the article Another nice example of non-linear growth is the popular puzzle which goes as follows: "If a lily pad doubles in size everyday and on the 20th day it covers a lake, on what day would it cover just half of the lake?". The possible causes are examined briefly below the chart

Possible causes of misinterpretation

Lack of conceptual knowledge Simplified visualization

Findings

Conclusions