Emotional and cognitive overload the dark side of information technology

EMOTIONAL AND COGNITIVE
OVERLOAD

We live in a world of limitless information. With technology advancing at an astonishingly
fast pace, we are challenged to adapt to robotics and automated systems that threaten to
replace us. Both at home and at work, an endless range of devices and Information Technology (IT) systems place demands upon our attention that human beings have never
experienced before, but are our brains capable of processing it all?
In this important new book, an in-depth view is taken of IT’s under-studied dark side and its
dire consequences on individuals, organizations, and society. With theoretical underpinnings
from the fields of cognitive psychology, management, and information systems, the idea of brain
overload is defined and explored, from its impact on our decision-making and memory to how
we may cope with the resultant ‘technostress’. Discussing the negative consequences of technology on work substitution, technologically induced work-family conflicts, and organizational
design as well as the initiatives set up to combat these, the authors go on to propose measurement approaches for capturing the entangled aspects of IT-related overload. Concluding on an
upbeat note, the book’s final chapter explores emerging technologies that can illuminate our
world when mindfully managed.
Designed to better equip humans for dealing with new technologies, supported by case
studies, and exploring the idea of ‘IT addiction’, the book concludes by asking how IT processes may aid rather than hinder our cognitive functioning. This is essential reading for
anyone interested in how we function in the digital age.
Anne-Franỗoise Rutkowski is Professor in Management of Information at Tilburg University.
Her research interests include information overload, decision-making, emotion, and the materiality of algorithms. Her background is in psychology. Her research has been published in Decision
Support Systems, IEEE Computer, IEEE Software, Journal of Surgical Endoscopy, and MIS Quarterly.
Carol S. Saunders is affiliated with the University of South Florida. She has received the
LEO Award from the Association of Information Systems (AIS) and the Lifetime Achievement Award from the Organizational Communication & Information Systems Division of
the Academy of Management. She served or is serving on numerous editorial boards,
including a three-year term as Editor-in-Chief of MIS Quarterly. Her articles appear in topranked management, information systems, computer science, and communication journals.
She currently is the AIS Vice President of Publications.


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EMOTIONAL AND
COGNITIVE OVERLOAD
The Dark Side of Information
Technology

Anne-Franỗoise Rutkowski and Carol S. Saunders


First published 2019
by Routledge
2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN
and by Routledge
711 Third Avenue, New York, NY 10017
Routledge is an imprint of the Taylor & Francis Group, an informa business
â 2019 Anne-Franỗoise Rutkowski and Carol S. Saunders
The right of Anne-Franỗoise Rutkowski and Carol S. Saunders to be identied as
authors of this work has been asserted by them in accordance with sections 77
and 78 of the Copyright, Designs and Patents Act 1988.
All rights reserved. No part of this book may be reprinted or reproduced or
utilised in any form or by any electronic, mechanical, or other means, now
known or hereafter invented, including photocopying and recording, or in any
information storage or retrieval system, without permission in writing from the
publishers.
Trademark notice: Product or corporate names may be trademarks or registered
trademarks, and are used only for identification and explanation without intent to
infringe.
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Cataloging in Publication Data

A catalog record has been requested for this book
ISBN: 978-1-138-05333-5 (hbk)
ISBN: 978-1-138-05335-9 (pbk)
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Typeset in Bembo
by Taylor & Francis Books


CONTENTS

List of Illustrations
Acknowledgements
1

Information Technology’s Dark Side: IT-related Overload and
IT-Addiction

vi
vii

1

2

The Brain and Paradigms of the Mind

17

3

Individual Differences in Experiencing IT-related Overload

37

4

Information Technology as a Resource: From the Bright to the
Dark Side of Addiction

58

Dark Side of Information Technology at the Organizational
Level

76

6

Measures of IT-related Overload

99

7

Leveraging the Positive Side of IT

5

Glossary
References

Index

118
134
142
166


ILLUSTRATIONS

Figures
1.1 The blender approach to understanding overload
3.1 Emotional-Cognitive Model of Overload (ECOM)
5.1 Information Technology Dark Side Diamond
5.2 Work-life balance continuum (adapted from Sarker, Xiao,
Sarker & Ahuja, 2012).
Tables
1.1 Comparison of brain overload in blenders and people
3.1 Summary of issues in processing and output for expert versus
non-expert
5.1 Summary of the Information Technology dark side diamond
6.1 Operationalization of IT-related overload with item loadings
6.2 Operationalization of memories of past cognitive and
emotional overload with item loadings
Boxes
3.1 Chris and Alix
3.2 Example application of the Emotional-Cognitive Overload
Model
5.1 Anna and David

5
45
77
84

7
50
97
108
109

37
51
76


ACKNOWLEDGEMENTS

The acknowledgement section is a tangible way of showing my gratitude to all my
co-authors referred to in this book. Specially, Carol, thank you for being my friend
and the strongest link in my chain of publication. It was another great adventure
writing this book together. Also, Michiel, thank you for being the powerful link in
both my publications and life. A special note to Les Wold for reviewing some of
the physiological jargon. A token of my gratitude goes to my colleague and friend
Piet Ribbers, who has provided me with continuous support during the last 20
years. Lauren, Louis: I hope one day you will forget about technologies for a few
days… only. In one of my magic Mary Poppins bags, you will find five old
paperback copies of Marcel Pagnol’s work. Overload yourself, read them… ALL…
to my mother, Marie-Franỗoise, ton chõteau en papier, and to my father, Wlodzimierz,
who taught me all that matters.

I would like to thank the Schöller Foundation for recognizing me as a Fellow in
2012. The award came at a low point in my academic career and served as
important validation for my work on the negative consequences of overload. My
only regret is that Frau Schöller, who made this award possible, will not be able to
see this fruit of her generosity. I remember fondly our discussion over coffee in her
office in Nürnberg. I also want to thank my wise counselor, lifelong sweetheart,
chief cheerleader/supporter and best friend, Rusty. He spent many hours discussing
the topics covered in this book with me and editing two chapters. Finally, I would
like to thank my very supportive family: Kristin, Russell, and Janel.


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1
INFORMATION TECHNOLOGY’S DARK
SIDE
IT-related Overload and IT Addiction

Charles Darwin (1871)– a naturalist best known for his contributions to the science
of evolution– wrote, “It has often been said that no animal uses any tool” (p. 51).
Darwin challenged this 19th-century statement through his own observations
and those of his colleagues. For example, Darwin noted that Asian elephants would
repel flies by waving a branch in their trunks. Interestingly, the elephants would
first fashion the branch into a tool by removing side branches or shortening the
stem. Earlier, Savage and Wyman (1843–1844) reported that chimpanzees in their
natural habitat use stones to crack fruits. They also devise sticks for hunting prosimians. Later, Köhler (1917/1925) observed that big apes restructure their environment to reach food. Thus, wild animals adapt tools to make them more efficient
and use them to enhance their chances of survival. It is indeed more efficient for
the elephant to have the right tool for chasing flies away than relying on the length
of his trunk. Yet, animals do not exhibit the full scope of intelligence observable in

humans. Evolutionary research has related the use of tools with the development of
hominid brains (Wrangham, 1994; Carvalho, Cunha, Sousa, & Matsuzawa, 2008;
Sanz & Morgan, 2013). Our early hominid ancestors, such as Ardipithecus, were
capable of making simple tools (Panger, Brooks, Richmond, & Wood, 2002;
Roche, Blumenschine, & Shea, 2009). Neanderthals displayed their abilities in
handling complex Paleolithic tools for their survival. Through evolution, the better
early hominids designed and handled complex tools, the smarter and fitter they
became. Early hominid’s use of tools, like ours today, was goal-driven and made it
possible to accumulate exogenous resources and conserve endogenous ones.

Misused tools or valuable resources?
Like humans, tools have evolved over time. They provide capabilities that
undoubtedly were never imagined by our early ancestors. However, in our digital


2 Information Technology’s dark side

age, the design and use of ‘digital tools’ such as the smartphone is causing some
concern. The popular press is full of revelations of this First World problem. For
example, Tristan Harris, a former product manager and design ethicist at Google,
recently declared war on smartphones. He stated in an interview with Rachel Metz
for the MIT Technology Review:
It’s so invisible what we’re doing to ourselves.… It’s like a public health crisis.
It’s like cigarettes, except because we’re given so many benefits, people can’t
actually see and admit the erosion of human thought that’s occurring at the
same time.
(Cited in Metz, 2017)
Research has demonstrated that even the absence of a smartphone in one’s pocket
can be a cause for concern. Specifically, phone owners have been reporting
‘phantom vibration syndrome’. In this syndrome, the phone owner is so used to

receiving messages that her body perceives that the phone is vibrating and delivering information even when it is not (Drouin, Kaiser, & Miller, 2012). Nicholas
Carr (2017), in his article “How Smartphones Hijack Our Minds”, reported
research denouncing the addictive nature of the smartphone and its weakening
effect on the brain. People are becoming too dependent on their smartphone, and
their ability to think and make sound judgements is decreasing. Carr concluded
from his readings that when a smartphone’s proximity increases, brainpower
decreases. In a similar vein, Hancock (2014) now muses over whether current
technology engenders stupidity instead of whether it can cure stupidity.
The smartphone is not the only Information Technology (IT) that has a dark
side. The popular press is full of accounts about the dark side of other types of IT:
information overload, email fatigue, iDisorders, technostress, or social media junkies to name just a few. Though clearly these advanced technologies have many
wonderful uses, their dire consequences on users’ behaviour and stress is generating
societal concern. However, IT itself is not the problem. Rather it is how IT is
actually used that can lead to good or dire consequences. When it is not used well,
the dark side of IT is unveiled.
We are particularly concerned with two ‘dark side’ challenges: IT-related overload and IT addiction. We define IT-related overload as the state of being challenged
in processing information used in IT-related activities. Rather than focus on the
amount (i.e., input) or symptoms (i.e., output) of overload, we seek to unlock the
black box of the mind and focus on mental processes. That is, we are concerned
with a form of brain overload, or the inability to adequately process input and handle
the associated brain load. We define brain load as the emotional and cognitive
efforts required by individuals to appraise and process inputs using the resources
available to them. Further, we define IT addiction as the state of being challenged in
balancing IT usage mindfully so as to preserve one’s resources.
When used well, we view Information Technologies as powerful tools. In particular, we view them as exogenous resources – digital tools that may require our


Information Technology’s dark side 3

endogenous brain resources. Resources are defined as “objects, personal characteristics,

conditions and energies that are valued by individuals or that serve as a means of
attainment of other resources” (Hobfoll, 1989, p.516). They may be endogenous
physical, emotional, or cognitive energy (Hobfoll & Freedy, 1993). Some are
temporal. The resources affect each other, exist as a resource pool (Kahneman,
1973), and are necessary for cognitive processing (Monetta & Joanette, 2003). Both
endogenous and exogenous resources are necessary to battle the dark side of IT.

Brain overload
The dark side of IT has exponentially increased in the last half-century as a result of
the introduction of new digital tools such as the Internet, email, smartphones, and
Social Networking Systems (SNSs). Indeed, since the commercialization of the Internet skyrocketed shortly after the introduction of web browsers, we find ourselves
increasingly inundated with information in the form of requests, advertising, popups, new apps, emails, or text messages delivered by various technologies. We are
deluged with information that is continuously being pushed at us by others or
pulled by us from the Internet and other myriad of technologies because we feel
compelled to seek additional information or social contact. We face the challenge
of dealing with the huge amount of information that is omnipresent in our world.
“Never in history has the human brain been asked to track so many data points”
(Hallowell, 2005, p.58). The consequences are serious in today’s information-rich
environment. In First World countries, “contemporary society suffers from information constipation. The steps from information to knowledge and from knowledge to wisdom, and thence to insight and understanding, are held captive to the
nominal insufficiency of processing capacity” (Hancock, 2014, p.450). Managers
and employees who suffer cognitively from overload may end up making an
increasing number of errors and poor decisions while trying to process dizzying
amounts of data (Hallowell, 2005). They may also suffer emotionally from the
overload, IT addiction, and workplace stress. For example, employees working in
high-technology industries have been found to demonstrate psychosomatic symptoms and reduced productivity related to high mental demands (Arnetz & Wiholm,
1997; Tarafdar, Tu, Ragu-Nathan, & Ragu-Nathan, 2007). One estimate places
the cost of information overload due to “lowered productivity and throttled
innovation” at $900 billion a year (Powers, 2010, p.62).
We believe that ‘brain overload’ is a better term to describe the phenomenon
more commonly called ‘information overload’. Processing the information that

Information Technologies deliver is brain-related and heavily reliant upon available
resources. Therefore, brain overload is a function of the brain (e.g., processor) and
not information (e.g., input). While the consequences of brain overload have been
reported frequently in the literature, they systematically have been attributed to
situations characterized by too much data, information, or connectivity. The focus
has been on the input and the output rather than on the cognitive processes (i.e.,
black box).


4 Information Technology’s dark side

More than four decades ago, Simon (1971) pointed out the challenges of processing so much information and the need for attention resources to do so. He wrote,
What information consumes is rather obvious: it consumes the attention of
its recipients. Hence a wealth of information creates a poverty of attention
and a need to allocate that attention efficiently among the overabundance of
information sources that may consume it.
(Simon, 1971, pp.40–41)
Indeed, there has always been a lot of data in the world. Not many of us have read
all the books in a library. Libraries are not blamed for causing information overload
– technologies, especially email, are.

Using resources mindfully
Recently, this automatic email reply arrived in one of our inboxes:
Hi there, Thanks for your mail, which I regrettably will not read since I’m working
away from the office. I’ll be back, however, on the 4th of May fully charged. So if your
email is still relevant after then, please send it again or otherwise it’ll end up in the heap
of mails that I’ll unlikely respond to. Even better, if the matter is urgent, give me a call
at +XXXXXXX. Have a good one – Corey
PS – join the fight against email fatigue and let others know that email, while
helpful, shouldn’t be a substitute for face-to-face or telephone communication. Together,

we can make the world a less stressful place.
In the digital workplace, managers show signs of overload from communications
delivered by email and other technologies. Some respond as Corey does in the
email signature above. In fact, Corey is sharing his coping strategy for curbing
email overload in this automatic reply. Consequently, he is using the auto-reply
option in a mindful way, sparing his resources. Research from psychology supports the idea that processing all inputs such as incoming email messages involves
a certain level of resources. Expending endogenous resources can reduce an
individual’s brain load and increase his processing efficiency. In addition to each
individual’s endogenous pool of resources are exogenous ones. Time is a
common exogenous resource that all too often proves inadequate. Indeed, Corey
is apparently lacking enough time to read all the emails in his inbox upon his
return to the office. He warns email senders that their message simply may not be
read unless it is re-sent at a later time. Also, Corey kindly urges the senders to
question the relevance of the content of their messages over time. He is expertly
building healthy boundaries for handling a flood of emails. In other words, he is
ensuring that he has adequate resources for solving his IT-related overload
equation. He does provide the option of giving him a phone call or meeting him
face-to-face.


Information Technology’s dark side 5

Not everyone is afraid of brain overload in today’s digital world. In fact, some
people enjoy it and impatiently wait for the next tweet or text. They appreciate
the high-speed connections that allow them to leverage a vast range of information
in accomplishing a phenomenal amount of work. Slow connections leave them
bored and annoyed. These individuals might even suffer from a form of IT addiction
that compels them to stay connected for fear of losing out.
To better understand the role of the brain in processing information, we propose
a model based on cognitive theories of memory (Atkinson & Shiffrin, 1968;

Bower, 1981). In particular, we draw on both the emotional and cognitive aspects
of the brain and consider the resources necessary to fuel its processing of inputs.
We introduce our model, the Emotional-Cognitive Overload Model (ECOM),
using the metaphor of a blender.

Blender metaphor
We use the commonplace blender to explain the brain overload phenomenon.
With a blender, we normally pour in the ingredients that need to be processed and
push the button to mix/blend. This is State 1 in Figure 1.1. If the ingredients are
hard to blend or if we want a smoother consistency of blended materials, we turn
the knob to liquefy rather than blend. That is, we call on the blender’s greater
processing capabilities. For simplicity sake, we assume that processing abilities are
similar for most blenders. State 2 in Figure 1.1 is when the blender cannot handle
the processing. Finally, if there are too many ingredients for one batch in the
blender, we can blend some of them, pour that into a separate container, and then
process the remainder in another batch. If we do not process in batches, there will
be an overflow condition, which is what is happening in State 3 in Figure 1.1.

State 1: Normal processing
State 3: Overflow from too much
to process
State 2: Inability to process well
FIGURE 1.1

The blender approach to understanding overload


6 Information Technology’s dark side

The material to be processed represents information, and the blender is used

to represent the brain’s memory processes. Even though we only have one
brain, it is organized in a way that allows us to process input in batches. In
State 1 the information to be processed is limited enough or easy enough that
it can be processed without difficulty. Consequently, no overload occurs.
However, in State 2 the person’s pool of resources is inadequate for processing
the information. The person may lack expertise in processing the information,
lack interest in or time for solving the problem, or be too exhausted because of
a lack of physiological resources. As a result, the person must either call upon a
higher level of cognitive ability than usual to be able to process the information
or adapt to lower levels of performance by learning to live with an increased
number of errors, reduced information integration, and impaired decisionmaking (Bettman, Johnson, & Payne, 1990; Shiv & Fedorikhin, 1999). Of
course, while blenders may be relatively similar in their processing abilities, they
may vary slightly in terms of power or capacity. Individuals, on the other hand,
definitely have very different cognitive abilities and stored memories in the
brain that are used to process information. More precisely, they may each
have a very different pool of resources from which to draw. We suggest that
some individuals process information better than others. They have better cognitive abilities. In State 3, the information processing needs to be made more
efficient. One way to do this is to chunk the information, which is like processing the information in batches. However, at some point, the amount of information or the ability to process it exceeds an individual’s resources. This leads to
a state of emotional and cognitive overload.
What we have not addressed so far is when to start the blender. We argue that
there must be some relevant (pertinent) input that starts the blending process –
such as the desire to have a fruit smoothie or a frozen daiquiri. It is unlikely that an
individual would start the blending process if the request is to blend cod liver oil
with jello, or some other ghastly concoction. Similarly, before an individual starts
processing information, there must be some pertinent input to motivate the processing and it must be perceived positively. In our blender example, the individual
can remember how good the smoothie or frozen daiquiri tasted in the past and is
motivated by this positive memory. Furthermore, the smoothies this person so
enjoys making and drinking may be loaded with sugars or alcohol, consumption of
which is addictive to the brain. This addiction may also motivate the person to start
the blender.

Clearly our blender metaphor is quite simplistic when it comes to explaining
overload and viewing smoothies as a form of addiction. We hope to remedy this
with a more complex model presented in Chapter 3, following a discussion of
models in Chapter 2. In the ECOM, Emotional-Cognitive Overload (ECO) is defined
as the negative emotional and cognitive consequences of brain overload. In Table
1.1 we continue our blender metaphor by highlighting key aspects of information
processing that are an important part of the ECOM but which are not usually
elaborated upon in overload research.


Information Technology’s dark side 7

TABLE 1.1 Comparison of brain overload in blenders and people

Aspects of information processing

Blender state

Person state

Pertinent input

We will not turn the blender on unless we want to
concoct something tasty,
like a smoothie with
brain-rewarding sugar.

Processing

No overflow. The container

can hold all of the ingredients and process them.
The blender may be used
seldom or never.

Individual
differences

The blender can do different
types of blending. Some
blending is very coarse. If
the material is to be
smoother, a higher level of
processing is needed. The
knob can be turned to a
different position indicating
more intense blending.
Relatively little difference is
assumed in the power of
blenders.

Chunking
abilities

The blender cannot hold all
of the ingredients. The
ingredients will overflow
the container unless they are
processed in batches.

The information will not be processed

unless it is perceived to be pertinent. In
information processing, the valence may
be positive or negative. When information is extremely pertinent, the person
may exhaust all resources to process the
information.
No overload. The person can process all
of the information perceived as pertinent. If the individual’s resources are
not used fully, the person may be
underloaded, or bored, and may decide
to use resources for other activities.
Individuals have markedly different
pools of resources. Some people have
the resources to easily process a limited
amount of information. Others have a
larger pool of resources. As the
information-processing requirements
increase, they can exert greater effort
and invoke higher levels of their
resources. They may experience the
processing to be great fun and quite
challenging. Others who do not have
the needed resources experience overload when they are not able to process
all the information.
The resource requirements are great.
Overload will occur unless there is
chunking.

Pertinence and ‘Amount Illusion’
In our anecdote, Corey would process all the emails that he receives after returning
to the office – even if only giving them a quick glance to see if they are relevant to

him or not. In contrast, our model reflects the assumption that individuals do not
process all information that they receive. Instead, the information and other input
that they receive is filtered, but filtered in a different way from that typically portrayed in the popular and academic press. We argue that the focus should not be
on bottlenecks that are created by brain funnels filled with too much information.
Likewise, we do not support the widely held assumption that IT addiction is
commonly related to too much connectivity. Rather, we suggest that it is time to
look at the processes that individuals use to deal with the deluge of information or
social connections with which they are presented. When individuals receive an


8 Information Technology’s dark side

input, it is moved to the person’s memory, where past emotions and lifelong
experiences are organized and stored. Cognitivist theories help explain how
incoming events are coded, specific memories are constructed, memories become
consolidated so they can be appropriately associated with one another, and personality traits are encapsulated. (Personality traits are representative of the way
individuals think and behave in certain contexts.)
At this point, it also is important to understand that each individual, in a unique
way, compares each input to what is stored in memory. Only the pertinent information then undergoes cognitive processing. By pertinence, or relevance, we mean
that a new input matches the information stored in memory. Pertinence is critical
at the starting point of our blender metaphor. In other words, pertinent information makes sense because it fits cognitively with what is stored in the individual’s
memory. The memory uses pertinence to accept or reject inputs, therefore controlling the brain load. The concept of pertinence means that not all information
that is received is processed. The idea that not all information is processed is very
different from that promulgated in much of the literature on overload. Our model
is about improving information processing and not about blaming the dizzying
amount of information that is received or the connectivity that delivers it.
This ‘amount illusion’ sees information as pouring in and relates brain overload
primarily to the amount of input. Little is said about the capability of individuals to
process the information. If one assumes that the problem people are dealing with is
too much information or too many social connections, the solution is to find ways

of filtering out what is extraneous and only allowing the needed information into
the mind for processing. This has happened to the extent that it is suggested that
technology be used as a filter or to handle email, time spent on social media, and so
on. However, in this scenario, individuals do not look for ways of improving the
processing and sparing their resources.

Processing – the conditions of no overload and underload
Up to this point we have spent a lot of time talking about brain overload.
There are, however, many occasions when a person does not experience
overload (i.e., normal processing takes place). It could be that the person does
not have much to process and the brain load is relatively slight. It could also be
that the brain load is great, but the person is able to handle it successfully. This
is often the case with experts.
When the brain load is too slight, underload may occur. Surprisingly, underload
may lead to negative consequences just as overload does. For example, the
experienced pilots of an Airbus A320 who overshot their plane’s destination and
forgot to land appeared to have been suffering from underload. In the hopes of
dodging boredom, they started ‘playing’ on their laptops to keep their minds and
attention busy (Rutkowski, 2016). They claimed that they lost track of time and
location because they were absorbed in exploring the new monthly crew flight
scheduling system on their laptops. It may be, though, that their expertise led to an


Information Technology’s dark side 9

underload situation on a long boring flight, with their actions to elude boredom
ultimately resulting in errors. Similarly, anaesthesiologists – whose work is increasingly supported by technology – when underloaded, have been found to focus
their attention on things other than their patients. When demands for their attention decrease, they have been found reading (Slagel & Weinger, 2009) or surfing
online (Saunders, Rutkowski, Pluyter, & Spanjers, 2016). Hospital administrators
are noticing their bored anaesthesiologists and are substituting many of them with

less expensive monitoring technology.

Individual differences
Once inputs have been selected for processing on the basis of their pertinence, they
are processed and stored in the person’s memory. The stored memories evolve as
individuals attempt to make sense of their own world. Each person’s memories are
very different from those of others.
Processing incoming inputs involves a certain level of effort, which calls upon
mental and physiological resources. Resources can reduce an individual’s brain load
by making the processing more efficient. Overall, resources are treated as the fuel
that runs the processing. Each person’s pool of resources is different from that of
others and depends upon how exhausted the person is. The level of resources
needed to process inputs can be compared to the different power levels in blenders.
Emotions distinguish individuals from blenders. Emotions can either help or
hinder processing of brain load. For example, memory of emotional reactions to
financial information has been found to be better than recall of the actual numbers
involved (Rose, Roberts, & Rose, 2004). Experience is encoded with a tag called a
valence. A valence may be a positive or negative emotional tag attached to events and
concepts that were activated in association with prior experience of the related
emotional tag. An input is congruent when its emotional tag, or valence, matches
that stored with a related item in memory. Where there is a mismatch with the
valence of the input and what is stored in memory, processing becomes less efficient
and challenges the individual’s pool of resources. He will, for example, focus more of
his scarce attentional resources in order to understand and solve the problem.

Chunking abilities
The attentional resources of the brain are rather limited (Kahneman, 1973; Neisser,
1976). The brain can only hold seven, plus or minus two, items at a time (Miller,
1956a). Individuals become overloaded when they have to deal with more input
items than they can handle. Thus, they must learn to focus their attention and

handle input efficiently. As noted by Miller (1956b), but often omitted in the literature, the only way to efficiently process the input and to extend the amount of
information that can be processed is by chunking. Chunking occurs when individual
items are combined into blocks called chunks. How the items are organized into
chunks determines recall. In addition to its role in processing of information,


10 Information Technology’s dark side

chunking also can involve converting a sequence of actions into an automatic
routine. Construction of an increasing number of interrelated complex chunks
increases expertise and therefore speeds information processing and decreases
overload by more efficiently dealing with attentional resource constraints. Some
chunking is simple, such as automatically putting toothpaste on a toothbrush before
inserting it into the mouth. Others, such as debugging a computer program, are
more complex and emerge as a result of habit over time that provides expertise.
Especially good chunkers can combine chunks into superchunks. Superchunks
comprise first-order chunks which are combined in levels so that they require less
effort to store in memory and also make the information easier to remember
(Mandler, 1967). Experts are particularly good superchunkers.
Experts are distinguished from non-experts in that they have performed a set of
activities so many times that it has been converted into superchunks. The set of
activities thus becomes automatic and can be completed by the expert with ease.
As a result of repetition of similar activities, experts, compared to non-experts, are
better aware of what information they need to complete the activities. Thus, they
are better than non-experts at distinguishing which inputs represent pertinent
information and which can be ignored without any further processing. This ability
to prioritize inputs as a function of their pertinence means that experts are better
able to process inputs efficiently and successfully (Sutcliffe & Weick, 2008). Further, they can more easily store and retrieve memories associated with their
expertise. While they may process the same number of chunks as non-experts,
their chunks are bigger and contain more information. Experts require less effort

and fewer mental resources in processing the brain load created from the incoming
inputs. Thus, even with high brain load, experts may not experience emotional or
cognitive overload at all, because their cognitive processes are highly automatized.
Further, when they do experience high brain load, they may be able to handle the
load successfully and, consequently, tag their stored memories positively. The successful resolution of conditions of high brain load can lead to and enhance self-image,
which allows them to see themselves as ‘super-experts’.

Overload from requests to use new IT
There is another type of input that can create overload but that has not, to our
knowledge, been discussed by other researchers. This type of overload emanates
from requests to use new Information Technologies. Individuals are not only
swamped with large quantities of information delivered by IT; they are also
deluged with promises of capabilities delivered by such devices as smartphones,
iPads, and new software applications. Further, they are often forced to adopt new
versions of software even though they are satisfied with the older versions whose
functions they have finally mastered. Tarafdar, Tu, Ragu-Nathan, and RaguNathan (2011) related the story of a university secretary who found it so difficult to
use a new student-management application that it drove her to early retirement.
The use of the software was mandated, but she was never able to master its


Information Technology’s dark side 11

multiple features, dismayed by its multiple crashes, and unable to get the IT support that she needed.
We were asked by a large Dutch bank to investigate the possible adoption of an
innovative TV banking system that would eventually replace its current one. Most
customers were reluctant to adopt the new system. We believe that this reluctance
could be explained by IT-related ECO created from both information overload
and too many requests to use IT. To test this premise, we conducted a survey of
Dutch participants aged 16 or older; 1,857 responded from a total sample of 2,538
(Rutkowski & Saunders, 2010). We found that almost two-thirds of the participants (61%) were concerned about being cognitively overloaded with too much

information when they use new Information Technologies. Just over two-fifths
(42%) felt cognitively and emotionally overloaded with requests to use new Information Technologies.
We concluded that requests to use new technologies can also create brain
overload conditions. Further, brain overload can be caused not only by being asked
to use too many technologies, but also by failing to intentionally forget some part
of what we have already learned (Rutkowski, Saunders, & Hatton, 2013). For
example, when the smartphone was introduced, one had to forget how to use a
traditional camera. Indeed, we now look at a screen to adjust a picture instead of
looking directly through the camera viewfinder.
Old technologies with which we are familiar may be very similar to new ones,
but different enough to be confusing. Brain overload is created when individuals
try to match the new functionalities of the software or services with the technology
they already know. If it differs, they may intentionally forget how they used to
interface with the old technology. Intentionally forgetting is cognitively taxing and
also contributes to feelings of burnout and rejection toward new technologies.
Overload with IT requests is similar to a component of technostress that is discussed commonly in the popular press.

Technostressed Mary
Recently, one of our young doctoral students, Mary, came up with an interesting
new strategy. Mary stated:
I decided to remove the email application on my smartphone. I cannot cope with the
constant pop-ups. They were driving me crazy. I will never be able to finish my dissertation that way. Would you please send me a phone text message when I need to
check important updates for my dissertation during the weekend? I have to focus if I am
ever going to finish my PhD.
Mary’s strategy is twofold: deleting the email application from her phone and
asking us to inform her of the relevance of our emails. This meant that we would
have to send one email AND a text message in order for her to access important
messages, multiplying the technologies we use (e.g., computers and smartphones).

12 Information Technology’s dark side

In order to spare some of her resources, Mary was asking to dig into our pool. Doing
so was her way of dealing with brain overload from messages delivered by technology. We gladly accepted this somehow self-centred request, relieving her of some of
the “growing pains with information overload” (Rutkowski & Saunders, 2010).

Technostress
Technostress, or the type of stress experienced in organizations by technology
end users as a result of their inability to cope with the demands of organizational computer usage (Tarafdar, Tu, & Ragu-Nathan, 2010), is another dark
side of IT. This stress may be induced by a surfeit of information delivered by
IT. It may also be the result of “application multitasking, constant connectivity,
information overload, frequent system upgrades and consequent uncertainty,
continual relearning and consequent job-related insecurities, and technical problems associated with the organizational use of ICT [Information and Communications Technology]” (Tarafdar et al., 2010, pp.304–305). Unlike our
ECOM approach, this has not been discussed in relation to emotions, cognitions,
or resources.
The term ‘technostress’ is interesting but confusing as it seems to suggest that
technologies bring on the stress. According to our model, the technology is not
to blame. Rather, we argue that the stress is created by a lack of available
resources or impulse control. Some individuals may never have experienced
technostress even when juggling many technologies. Mary ended up upset just
hearing the constant ‘beep’ of her phone when an email lands. We believe her
stress is more symptomatic of a lack of resources than it is a function of the
information received. It arrives at a moment in time when she needs to leverage
her pool of resources to the maximum in order to finish a very relevant task –
completing her PhD.
Tarafdar and colleagues have identified five major creators, or components, of
technostress: techno-overload, techno-innovations, techno-complexity, technoinsecurity, and techno-uncertainty (e.g., Tarafdar et al., 2007; Ragu-Nathan, Tarafdar, Ragu-Nathan, & Tu, 2008; Tarafdar et al., 2010). At the organizational level,
technostress has been found to lead to increased role stress and reduced productivity,
end-user performance, and end-user satisfaction. These findings are discussed in
greater detail in Chapter 5.

Interestingly, technostress has been strongly related to compulsive behaviours
(Lee, Chang, Lin, & Cheng, 2014), which are often associated with addiction.
Further, drug addiction has been found to display the same underlying symptoms
as SNS or Internet addiction (both types of IT addiction) (Goeders, 2003). In
particular, “SNS addiction incorporates the experience of the ‘classic’ addiction
symptoms, namely mood modification, salience, tolerance, withdrawal symptoms,
conflict, and relapse” (Kuss & Griffiths, 2011, p.3530). Brooks, Longstreet, and
Califf (2017) found technostress to be strongly and positively related to Internet
addiction.


Information Technology’s dark side 13

Addictive IT behaviours
There is indeed another IT-related challenge associated with having ‘too much’
that is reaching epic proportions: too much Internet and mobile phone connectivity. People in all generations are staying connected too long, and this hyperconnectivity often leads to a range of dysfunctional behaviours including IT
addiction, excessive media multitasking, and Pathological Internet Use. Pathological
Internet Use (PIU) has four elements: (1) excessive Internet use, often associated
with a loss of sense of time or a neglect of basic drives; (2) withdrawal, including
feelings of anger, depression, and tension when Internet is not accessible; (3) tolerance, including the need for better computer equipment, more software, or more
hours of use; and (4) adverse consequences, including arguments, lying, poor
school or vocational achievement, social isolation, and fatigue (Block, 2008, from
Spada, 2014, p.4).
Hyperconnectivity is being reported among all age groups. Tweens (children in
the 8–12 age range) and teens (children in the 13–18 age range) are averaging over
4.5 hours and 6 hours a day, respectively, on the Internet. A quarter of the teens in
a recent survey reported reaching for their phones within five minutes of waking
up (Ipsos MediaCT & Wikia, 2013). They are texting and emailing so much that
employers of young adults accuse them of having difficulty starting and ending
conversations and being nervous when making phone calls (Colbert, Yee, &

George, 2016). And older adults (commonly called ‘silver surfers’) are also taking
advantage of access to the Internet and smartphones so that they can be in a state of
constant communication with others (Colbert et al., 2016). One study even
reported that it is parents, not teenagers or tweens, who spend the most time in
front of screens (Molina, 2017).
The challenge to ‘unplug’ is spawning new opportunities for the tourism
industry as tour operators are advocating device-free vacations. For example,
Intrepid Travel, an adventure travel company, now offers “Digital Detox Trips” in
which the participants pledge not to bring along any digital devices and must resort
to paper notebooks to record their impressions (Glusac, 2016). Renaissance Pittsburgh’s family detox package trades digital devices for board games and cards
during the family’s stay. Further, digital detox retreats have sprung up with offers to
disconnect, for a price; and resorts offer an ‘iPhone crèche’ where you can leave
your mobile devices. In the private sphere, the negative impacts of IT-related
overload have been linked to the exponential use of Information Technologies.
State legislatures are now providing motivation to unplug in other ways. In
Hawaii, ‘smartphone zombies’, or pedestrians so distracted by what’s on their
phones that they are oblivious when crossing streets, are fined. Further, 47 states
and the District of Columbia have banned texting while driving (Molina, 2017).
In the Net Generation, hyperconnectivity is manifesting a number of new
behaviours. Net Geners are people born after 1980; this includes the groups called
Millennials and Generation Y. Net Geners have now developed the skill of
‘phubbing’ during conversations, which means that they can maintain eye contact


14 Information Technology’s dark side

while also texting. However, the eye contact may not be as meaningful as they
think, because just having the phone in sight likely reduces their conversation
partners’ perception of closeness, trust, and relationship quality (Colbert et al.,
2016). Another task that Net Geners may not be as good at performing as they

think they are is media multitasking. Media multitasking entails checking mobile
phone content as often as every 30 seconds, or even less (Rosen, Carrier, & Cheever, 2013), an activity which commands high switching costs as multitaskers shift
frequently from one task to another. This may explain why younger users of
mobile phones are significantly more likely than older users to experience overload
from information and communication messages delivered by their phones (Saunders,
Wiener, Klett, & Sprenger, 2017).
Some claim that such heavy use of smartphones can lead to a particular type of
addiction called mobile email addiction. Symptoms of this addiction are that the
mobile phone user becomes preoccupied with using the smartphone, has difficulty
in controlling or quitting the behaviour, and gets angry or frustrated when interrupted (Turel & Serenko, 2010). Attention deficit hyperactivity disorder (ADHD),
depression, and social phobia as well as hostility have been identified as symptoms
of Internet addiction in adolescents (Yen, Ko, Yen, Wu, & Yang, 2007).
Mobile email addiction is viewed as one form of Internet addiction. Kandell
(1998) defined Internet addiction as psychological dependence on the Internet. The
dependence is characterized by: (1) an increasing investment of resources in Internet-related activities; (2) unpleasant feelings (e.g., anxiety, depression, emptiness)
when offline; (3) an increasing tolerance to the effects of being online; and (4)
denial of the problematic behaviours (Kandell, 1998, p.11). In short, Internet
addicts find it hard to unplug from the Internet, and they suffer from withdrawal
upon doing so (Davis, 2001).
Among American psychologists and psychiatrists, there is no recognition of IT
addiction (i.e., Internet, SNS, or mobile email addictions) or stress. That is, no
form of technology addiction or technostress is listed in the current version of the
Diagnostic and Statistical Manual of Mental Disorders (DSM 5), which contains a formal
list of mental disorders. This is because many believe that the term ‘addiction’
should only be used in respect to chemical substances (Turel & Serenko, 2010) or
when the person has a physiological dependence on some stimulus, which is
usually a substance (Davis, 2001). Others believe that a common set of symptoms
and diagnosis criteria are missing (Turel & Serenko, 2010). Hence, in this book we
use the term Pathological Internet Use to describe the behaviours described in the
literature as IT addiction. As we discuss in Chapter 4, the lack of control consciously exerted by the brain during information processing contributes heavily to

IT addiction. These behaviours can be specific or general. They are considered
specific when a person is dependent on a particular function of the Internet such as
online auction services, sexual material/services, or gambling. They are considered
general when the Internet is overused in such cases where people waste time
online without a clear objective. But whether it is called IT addiction, Internet
addiction, specific PIU, or general PIU, it is a force to be dealt with in our society.


Information Technology’s dark side 15

In the rest of this book, we will tell you why. In addressing this force as a society,
we can reap the benefits of technology while staving off its harmful effects.

What’s coming next? A sneak preview
The following six chapters dive into details of scientific practices borrowed from
philosophy, behavioural and cognitive psychology, neurophysiology, and artificial
intelligence to enlighten our understanding of the dark side of IT. In this book we
address three main questions: (1) Why do some individuals experience IT-related
overload while others do not? (2) Why do some individuals experience IT addiction
while others do not? and (3) What are the consequences of the dark side of IT?
Thomas Edison once said, “Results! Why, man, I have gotten a lot of results. I
know several thousand things that won’t work” (Forbes, 1921, p.89). We found
this to be the case in our painful attempts to measure IT-related overload, which
we describe in Chapter 6. In this book we present results we have collected in our
own research and draw on data collected by others to support our arguments.
Some studies suggest ways to tackle IT-related overload that are likely to work
well, while others indicate approaches that are less convincing. We realize that we
may not have understood the IT-related problem fully. Still, we believe we are
getting closer every day. Our Emotional-Cognitive Overload Model (ECOM) in
Chapter 3 is based on cognitive theories of memory architecture that are introduced in Chapter 2. We also build on the work of other scientists in order to

better understand the impact of emotion and pools of resources on IT-related
overload and IT addiction. The ECOM suggests that not every person experiences
overload or addiction in the same way– if at all.
Our book is not about bashing IT. Our interest in the dark side is triggered
by our wishing to better understand the possible effects of IT, both positive
and negative. Now is the right time to take a serious look at ‘responsible’ IT
use and the consequences of its mindless use. In Chapter 7 we suggest some
ways of acting responsibly in relation to IT. We recognize that Information
Technologies were originally built to serve humanity. However, it seems that
way too many people are being held hostage by various forms of IT: They
suffer from IT-related overload or IT addiction (or both). But blindly bashing
technology or imposing rules and policy without a deeper understanding of the
phenomena would be sterile. This would only increase a misunderstanding of
the role of technology.
The brain and availability of resources are key in understanding the phenomenon. Evolutionary theorists determined that Neanderthals had brains of similar size
to modern humans, sometimes even larger (Ponce de León, Golovanova, Doronichev, Romanova, Akazawa, Kondo et al., 2008). Through evolution, tools have
served as efficient resources enhancing our efficiency in our natural environment.
Our use of tools has been one of the main competitive advantages over other
species in hominid brain development. However, if not used mindfully, the impact
of new digital tools may have the inverse effect on our brain (Chapters 3 and 4).


16 Information Technology’s dark side

Hyperconnected managers and employees may suffer from work-family conflict or
jeopardize their work-life balance (Chapter 5).
Grinbaum and Groves (2013) emphasized that any innovation creates ultimately
new social practices and institutions transforming our day-to-day interaction with
the world and each other. In relation to IT innovation, those new practices and
institutions are key in handling its dark side. The future is bright because it is ours

in which to build the needed institutions and social practices.