Emotional and cognitive overload the dark side of information technology

List of Illustrations vi Acknowledgements vii 1 Information Technology’s Dark Side: IT-related Overload and 2 The Brain and Paradigms of the Mind 17 3 Individual Di fferences in Experienc

EMOTIONAL AND COGNITIVE

OVERLOAD

We live in a world of limitless information With technology advancing at an astonishinglyfast pace, we are challenged to adapt to robotics and automated systems that threaten toreplace us Both at home and at work, an endless range of devices and Information Tech-nology (IT) systems place demands upon our attention that human beings have neverexperienced 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 itsdire consequences on individuals, organizations, and society With theoretical underpinningsfrom thefields of cognitive psychology, management, and information systems, the idea of brainoverload 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 nology on work substitution, technologically induced work-family conflicts, and organizationaldesign as well as the initiatives set up to combat these, the authors go on to propose measure-ment approaches for capturing the entangled aspects of IT-related overload Concluding on anupbeat note, the book’s final chapter explores emerging technologies that can illuminate ourworld when mindfully managed

tech-Designed to better equip humans for dealing with new technologies, supported by casestudies, and exploring the idea of‘IT addiction’, the book concludes by asking how IT pro-cesses may aid rather than hinder our cognitive functioning This is essential reading foranyone interested in how we function in the digital age

Anne-Françoise Rutkowskiis Professor in Management of Information at Tilburg University.Her research interests include information overload, decision-making, emotion, and the materi-ality of algorithms Her background is in psychology Her research has been published in DecisionSupport Systems, IEEE Computer, IEEE Software, Journal of Surgical Endoscopy, and MIS Quarterly.Carol S Saundersis affiliated with the University of South Florida She has received theLEO Award from the Association of Information Systems (AIS) and the Lifetime Achieve-ment Award from the Organizational Communication & Information Systems Division ofthe 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 top-ranked management, information systems, computer science, and communication journals.She currently is the AIS Vice President of Publications

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First published 2019

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© 2019 Anne-Françoise Rutkowski and Carol S Saunders

The right of Anne-Françoise Rutkowski and Carol S Saunders to be identi fied 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.

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List of Illustrations vi Acknowledgements vii

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

2 The Brain and Paradigms of the Mind 17

3 Individual Di fferences in Experiencing IT-related Overload 37

4 Information Technology as a Resource: From the Bright to the Dark Side of Addiction 58

5 Dark Side of Information Technology at the Organizational

6 Measures of IT-related Overload 99

7 Leveraging the Positive Side of IT 118

Figures

1.1 The blender approach to understanding overload 5 3.1 Emotional-Cognitive Model of Overload (ECOM) 45 5.1 Information Technology Dark Side Diamond 77 5.2 Work-life balance continuum (adapted from Sarker, Xiao,

Sarker & Ahuja, 2012).

emotional overload with item loadings

The acknowledgement section is a tangible way of showing my gratitude to all myco-authors referred to in this book Specially, Carol, thank you for being my friendand the strongest link in my chain of publication It was another great adventurewriting this book together Also, Michiel, thank you for being the powerful link inboth my publications and life A special note to Les Wold for reviewing some ofthe physiological jargon A token of my gratitude goes to my colleague and friendPiet Ribbers, who has provided me with continuous support during the last 20years Lauren, Louis: I hope one day you will forget about technologies for a fewdays… only In one of my magic Mary Poppins bags, you will find five oldpaperback copies of Marcel Pagnol’s work Overload yourself, read them… ALL…

to my mother, Marie-Françoise, ton château 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 asimportant validation for my work on the negative consequences of overload Myonly regret is that Frau Schöller, who made this award possible, will not be able tosee this fruit of her generosity I remember fondly our discussion over coffee in heroffice in Nürnberg I also want to thank my wise counselor, lifelong sweetheart,chief cheerleader/supporter and best friend, Rusty He spent many hours discussingthe topics covered in this book with me and editing two chapters Finally, I wouldlike to thank my very supportive family: Kristin, Russell, and Janel

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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 observationsand those of his colleagues For example, Darwin noted that Asian elephants wouldrepel flies by waving a branch in their trunks Interestingly, the elephants wouldfirst fashion the branch into a tool by removing side branches or shortening thestem Earlier, Savage and Wyman (1843–1844) reported that chimpanzees in theirnatural habitat use stones to crack fruits They also devise sticks for hunting prosi-mians Later, Köhler (1917/1925) observed that big apes restructure their envir-onment to reach food Thus, wild animals adapt tools to make them more efficientand use them to enhance their chances of survival It is indeed more efficient forthe elephant to have the right tool for chasingflies away than relying on the length

of his trunk Yet, animals do not exhibit the full scope of intelligence observable inhumans Evolutionary research has related the use of tools with the development ofhominid brains (Wrangham, 1994; Carvalho, Cunha, Sousa, & Matsuzawa, 2008;Sanz & Morgan, 2013) Our early hominid ancestors, such as Ardipithecus, werecapable of making simple tools (Panger, Brooks, Richmond, & Wood, 2002;Roche, Blumenschine, & Shea, 2009) Neanderthals displayed their abilities inhandling complex Paleolithic tools for their survival Through evolution, the betterearly hominids designed and handled complex tools, the smarter and fitter theybecame Early hominid’s use of tools, like ours today, was goal-driven and made itpossible to accumulate exogenous resources and conserve endogenous ones

Misused tools or valuable resources?

Like humans, tools have evolved over time They provide capabilities thatundoubtedly were never imagined by our early ancestors However, in our digital

age, the design and use of ‘digital tools’ such as the smartphone is causing someconcern The popular press is full of revelations of this First World problem Forexample, Tristan Harris, a former product manager and design ethicist at Google,recently declared war on smartphones He stated in an interview with Rachel Metzfor 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’tactually see and admit the erosion of human thought that’s occurring at thesame time

(Cited in Metz, 2017)Research has demonstrated that even the absence of a smartphone in one’s pocketcan be a cause for concern Specifically, phone owners have been reporting

‘phantom vibration syndrome’ In this syndrome, the phone owner is so used toreceiving messages that her body perceives that the phone is vibrating and deli-vering information even when it is not (Drouin, Kaiser, & Miller, 2012) NicholasCarr (2017), in his article “How Smartphones Hijack Our Minds”, reportedresearch denouncing the addictive nature of the smartphone and its weakeningeffect on the brain People are becoming too dependent on their smartphone, andtheir ability to think and make sound judgements is decreasing Carr concludedfrom his readings that when a smartphone’s proximity increases, brainpowerdecreases In a similar vein, Hancock (2014) now muses over whether currenttechnology engenders stupidity instead of whether it can cure stupidity

The smartphone is not the only Information Technology (IT) that has a darkside 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 junk-ies to name just a few Though clearly these advanced technologies have manywonderful uses, their dire consequences on users’ behaviour and stress is generatingsocietal concern However, IT itself is not the problem Rather it is how IT isactually 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 load and IT addiction We define IT-related overload as the state of being challenged

over-in processover-ing over-information used over-in IT-related activities Rather than focus on theamount (i.e., input) or symptoms (i.e., output) of overload, we seek to unlock theblack box of the mind and focus on mental processes That is, we are concernedwith a form of brain overload, or the inability to adequately process input and handlethe associated brain load We define brain load as the emotional and cognitiveefforts required by individuals to appraise and process inputs using the resourcesavailable to them Further, we define IT addiction as the state of being challenged inbalancing IT usage mindfully so as to preserve one’s resources

When used well, we view Information Technologies as powerful tools In cular, we view them as exogenous resources – digital tools that may require our

parti-2 Information Technology’s dark side

endogenous brain resources Resources are defined as “objects, personal characteristics,conditions and energies that are valued by individuals or that serve as a means ofattainment of other resources” (Hobfoll, 1989, p.516) They may be endogenousphysical, emotional, or cognitive energy (Hobfoll & Freedy, 1993) Some aretemporal The resources affect each other, exist as a resource pool (Kahneman,1973), and are necessary for cognitive processing (Monetta & Joanette, 2003) Bothendogenous 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 ofthe introduction of new digital tools such as the Internet, email, smartphones, andSocial Networking Systems (SNSs) Indeed, since the commercialization of the Inter-net skyrocketed shortly after the introduction of web browsers, wefind ourselvesincreasingly inundated with information in the form of requests, advertising, pop-ups, new apps, emails, or text messages delivered by various technologies We aredeluged with information that is continuously being pushed at us by others orpulled by us from the Internet and other myriad of technologies because we feelcompelled 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-richenvironment In First World countries, “contemporary society suffers from infor-mation constipation The steps from information to knowledge and from knowl-edge to wisdom, and thence to insight and understanding, are held captive to thenominal insufficiency of processing capacity” (Hancock, 2014, p.450) Managersand employees who suffer cognitively from overload may end up making anincreasing number of errors and poor decisions while trying to process dizzyingamounts of data (Hallowell, 2005) They may also suffer emotionally from theoverload, IT addiction, and workplace stress For example, employees working inhigh-technology industries have been found to demonstrate psychosomatic symp-toms and reduced productivity related to high mental demands (Arnetz & Wiholm,1997; Tarafdar, Tu, Ragu-Nathan, & Ragu-Nathan, 2007) One estimate placesthe cost of information overload due to “lowered productivity and throttledinnovation” at $900 billion a year (Powers, 2010, p.62)

We believe that ‘brain overload’ is a better term to describe the phenomenonmore commonly called ‘information overload’ Processing the information thatInformation Technologies deliver is brain-related and heavily reliant upon availableresources Therefore, brain overload is a function of the brain (e.g., processor) andnot information (e.g., input) While the consequences of brain overload have beenreported frequently in the literature, they systematically have been attributed tosituations characterized by too much data, information, or connectivity The focushas been on the input and the output rather than on the cognitive processes (i.e.,black box)

Information Technology’s dark side 3

More than four decades ago, Simon (1971) pointed out the challenges of sing so much information and the need for attention resources to do so He wrote,What information consumes is rather obvious: it consumes the attention ofits recipients Hence a wealth of information creates a poverty of attentionand a need to allocate that attention efficiently among the overabundance ofinformation sources that may consume it.

proces-(Simon, 1971, pp.40–41)Indeed, there has always been a lot of data in the world Not many of us have readall 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 workingaway from the office I’ll be back, however, on the 4th of May fully charged So if youremail 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, whilehelpful, 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 communicationsdelivered by email and other technologies Some respond as Corey does in theemail signature above In fact, Corey is sharing his coping strategy for curbingemail overload in this automatic reply Consequently, he is using the auto-replyoption in a mindful way, sparing his resources Research from psychology sup-ports the idea that processing all inputs such as incoming email messages involves

a certain level of resources Expending endogenous resources can reduce anindividual’s brain load and increase his processing efficiency In addition to eachindividual’s endogenous pool of resources are exogenous ones Time is acommon exogenous resource that all too often proves inadequate Indeed, Corey

is apparently lacking enough time to read all the emails in his inbox upon hisreturn to the office He warns email senders that their message simply may not beread unless it is re-sent at a later time Also, Corey kindly urges the senders toquestion the relevance of the content of their messages over time He is expertlybuilding healthy boundaries for handling aflood of emails In other words, he isensuring that he has adequate resources for solving his IT-related overloadequation He does provide the option of giving him a phone call or meeting himface-to-face

4 Information Technology’s dark side

Not everyone is afraid of brain overload in today’s digital world In fact, somepeople enjoy it and impatiently wait for the next tweet or text They appreciatethe high-speed connections that allow them to leverage a vast range of information

in accomplishing a phenomenal amount of work Slow connections leave thembored and annoyed These individuals might even suffer from a form of IT addictionthat 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 andpush the button to mix/blend This is State 1 in Figure 1.1 If the ingredients arehard to blend or if we want a smoother consistency of blended materials, we turnthe knob to liquefy rather than blend That is, we call on the blender’s greaterprocessing capabilities For simplicity sake, we assume that processing abilities aresimilar for most blenders State 2 in Figure 1.1 is when the blender cannot handlethe processing Finally, if there are too many ingredients for one batch in theblender, we can blend some of them, pour that into a separate container, and thenprocess 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 2: Inability to process well

State 3: Overflow from too much

to process

FIGURE 1.1 The blender approach to understanding overload

Information Technology’s dark side 5

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

to represent the brain’s memory processes Even though we only have onebrain, it is organized in a way that allows us to process input in batches InState 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 processingthe 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 ahigher 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 increasednumber of errors, reduced information integration, and impaired decision-making (Bettman, Johnson, & Payne, 1990; Shiv & Fedorikhin, 1999) Ofcourse, while blenders may be relatively similar in their processing abilities, theymay vary slightly in terms of power or capacity Individuals, on the other hand,definitely have very different cognitive abilities and stored memories in thebrain that are used to process information More precisely, they may eachhave a very different pool of resources from which to draw We suggest thatsome individuals process information better than others They have better cog-nitive abilities In State 3, the information processing needs to be made moreefficient One way to do this is to chunk the information, which is like proces-sing the information in batches However, at some point, the amount of infor-mation 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 thatthere 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 anindividual would start the blending process if the request is to blend cod liver oilwith jello, or some other ghastly concoction Similarly, before an individual startsprocessing information, there must be some pertinent input to motivate the pro-cessing and it must be perceived positively In our blender example, the individualcan remember how good the smoothie or frozen daiquiri tasted in the past and ismotivated by this positive memory Furthermore, the smoothies this person soenjoys making and drinking may be loaded with sugars or alcohol, consumption ofwhich is addictive to the brain This addiction may also motivate the person to startthe blender

Clearly our blender metaphor is quite simplistic when it comes to explainingoverload and viewing smoothies as a form of addiction We hope to remedy thiswith a more complex model presented in Chapter 3, following a discussion ofmodels in Chapter 2 In the ECOM, Emotional-Cognitive Overload (ECO) is defined

as the negative emotional and cognitive consequences of brain overload In Table1.1 we continue our blender metaphor by highlighting key aspects of informationprocessing that are an important part of the ECOM but which are not usuallyelaborated upon in overload research

6 Information Technology’s dark side

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 tohim or not In contrast, our model reflects the assumption that individuals do notprocess all information that they receive Instead, the information and other inputthat they receive isfiltered, but filtered in a different way from that typically por-trayed in the popular and academic press We argue that the focus should not be

on bottlenecks that are created by brain funnelsfilled with too much information.Likewise, we do not support the widely held assumption that IT addiction iscommonly related to too much connectivity Rather, we suggest that it is time tolook at the processes that individuals use to deal with the deluge of information orsocial connections with which they are presented When individuals receive an

TABLE 1.1 Comparison of brain overload in blenders and people

Aspects of

informa-tion processing

Blender state Person state

Pertinent input We will not turn the

blen-der on unless we want toconcoct something tasty,like a smoothie withbrain-rewarding sugar

The information will not be processedunless it is perceived to be pertinent Ininformation processing, the valence may

be positive or negative When tion is extremely pertinent, the personmay exhaust all resources to process theinformation

informa-Processing No overflow The container

can hold all of the dients and process them

ingre-The blender may be usedseldom or never

No overload The person can process all

of the information perceived as nent If the individual’s resources arenot used fully, the person may beunderloaded, or bored, and may decide

perti-to use resources for other activities.Individual

differences The blender can do ditypes of blending Somefferent

blending is very coarse Ifthe material is to besmoother, a higher level ofprocessing is needed Theknob can be turned to adifferent position indicatingmore intense blending

Relatively little difference isassumed in the power ofblenders

Individuals have markedly differentpools of resources Some people havethe resources to easily process a limitedamount of information Others have alarger pool of resources As theinformation-processing requirementsincrease, they can exert greater effortand invoke higher levels of theirresources They may experience theprocessing to be great fun and quitechallenging Others who do not havethe needed resources experience over-load when they are not able to processall the information

Chunking

abilities

The blender cannot hold all

of the ingredients Theingredients will overflowthe container unless they areprocessed in batches

The resource requirements are great.Overload will occur unless there ischunking

Information Technology’s dark side 7

input, it is moved to the person’s memory, where past emotions and lifelongexperiences are organized and stored Cognitivist theories help explain howincoming events are coded, specific memories are constructed, memories becomeconsolidated so they can be appropriately associated with one another, and per-sonality traits are encapsulated (Personality traits are representative of the wayindividuals think and behave in certain contexts.)

At this point, it also is important to understand that each individual, in a uniqueway, compares each input to what is stored in memory Only the pertinent infor-mation then undergoes cognitive processing By pertinence, or relevance, we meanthat a new input matches the information stored in memory Pertinence is critical

at the starting point of our blender metaphor In other words, pertinent tion makes sense because itfits cognitively with what is stored in the individual’smemory The memory uses pertinence to accept or reject inputs, therefore con-trolling the brain load The concept of pertinence means that not all informationthat is received is processed The idea that not all information is processed is verydifferent from that promulgated in much of the literature on overload Our model

informa-is about improving information processing and not about blaming the dizzyingamount of information that is received or the connectivity that delivers it.This‘amount illusion’ sees information as pouring in and relates brain overloadprimarily to the amount of input Little is said about the capability of individuals toprocess the information If one assumes that the problem people are dealing with istoo much information or too many social connections, the solution is tofind ways

offiltering out what is extraneous and only allowing the needed information intothe mind for processing This has happened to the extent that it is suggested thattechnology be used as afilter or to handle email, time spent on social media, and so

on However, in this scenario, individuals do not look for ways of improving theprocessing 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 experienceoverload (i.e., normal processing takes place) It could be that the person doesnot have much to process and the brain load is relatively slight It could also bethat 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, underloadmay lead to negative consequences just as overload does For example, theexperienced pilots of an Airbus A320 who overshot their plane’s destination andforgot to land appeared to have been suffering from underload In the hopes ofdodging boredom, they started‘playing’ on their laptops to keep their minds andattention busy (Rutkowski, 2016) They claimed that they lost track of time andlocation because they were absorbed in exploring the new monthly crew flightscheduling system on their laptops It may be, though, that their expertise led to an

8 Information Technology’s dark side

underload situation on a long boring flight, with their actions to elude boredomultimately resulting in errors Similarly, anaesthesiologists– whose work is increas-ingly supported by technology – when underloaded, have been found to focustheir attention on things other than their patients When demands for their atten-tion decrease, they have been found reading (Slagel & Weinger, 2009) or surfingonline (Saunders, Rutkowski, Pluyter, & Spanjers, 2016) Hospital administratorsare noticing their bored anaesthesiologists and are substituting many of them withless expensive monitoring technology.

Individual differences

Once inputs have been selected for processing on the basis of their pertinence, theyare processed and stored in the person’s memory The stored memories evolve asindividuals attempt to make sense of their own world Each person’s memories arevery different from those of others

Processing incoming inputs involves a certain level of effort, which calls uponmental and physiological resources Resources can reduce an individual’s brain load

by making the processing more efficient Overall, resources are treated as the fuelthat runs the processing Each person’s pool of resources is different from that ofothers and depends upon how exhausted the person is The level of resourcesneeded to process inputs can be compared to the different power levels in blenders.Emotions distinguish individuals from blenders Emotions can either help orhinder processing of brain load For example, memory of emotional reactions tofinancial information has been found to be better than recall of the actual numbersinvolved (Rose, Roberts, & Rose, 2004) Experience is encoded with a tag called avalence A valence may be a positive or negative emotional tag attached to events andconcepts that were activated in association with prior experience of the relatedemotional tag An input is congruent when its emotional tag, or valence, matchesthat stored with a related item in memory Where there is a mismatch with thevalence of the input and what is stored in memory, processing becomes less efficientand challenges the individual’s pool of resources He will, for example, focus more ofhis 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 inputitems than they can handle Thus, they must learn to focus their attention andhandle input efficiently As noted by Miller (1956b), but often omitted in the lit-erature, the only way to efficiently process the input and to extend the amount ofinformation that can be processed is by chunking Chunking occurs when individualitems are combined into blocks called chunks How the items are organized intochunks determines recall In addition to its role in processing of information,

Information Technology’s dark side 9

chunking also can involve converting a sequence of actions into an automaticroutine Construction of an increasing number of interrelated complex chunksincreases expertise and therefore speeds information processing and decreasesoverload by more efficiently dealing with attentional resource constraints Somechunking is simple, such as automatically putting toothpaste on a toothbrush beforeinserting it into the mouth Others, such as debugging a computer program, aremore complex and emerge as a result of habit over time that provides expertise.Especially good chunkers can combine chunks into superchunks Superchunkscomprisefirst-order chunks which are combined in levels so that they require lesseffort 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 ofactivities so many times that it has been converted into superchunks The set ofactivities 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, arebetter aware of what information they need to complete the activities Thus, theyare better than non-experts at distinguishing which inputs represent pertinentinformation and which can be ignored without any further processing This ability

to prioritize inputs as a function of their pertinence means that experts are betterable to process inputs efficiently and successfully (Sutcliffe & Weick, 2008) Fur-ther, they can more easily store and retrieve memories associated with theirexpertise While they may process the same number of chunks as non-experts,their chunks are bigger and contain more information Experts require less effortand fewer mental resources in processing the brain load created from the incominginputs Thus, even with high brain load, experts may not experience emotional orcognitive overload at all, because their cognitive processes are highly automatized.Further, when they do experience high brain load, they may be able to handle theload successfully and, consequently, tag their stored memories positively The suc-cessful 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 ourknowledge, been discussed by other researchers This type of overload emanatesfrom requests to use new Information Technologies Individuals are not onlyswamped with large quantities of information delivered by IT; they are alsodeluged with promises of capabilities delivered by such devices as smartphones,iPads, and new software applications Further, they are often forced to adopt newversions of software even though they are satisfied with the older versions whosefunctions they have finally mastered Tarafdar, Tu, Ragu-Nathan, and Ragu-Nathan (2011) related the story of a university secretary who found it so difficult touse 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

10 Information Technology’s dark side

multiple features, dismayed by its multiple crashes, and unable to get the IT port that she needed.

sup-We were asked by a large Dutch bank to investigate the possible adoption of aninnovative TV banking system that would eventually replace its current one Mostcustomers were reluctant to adopt the new system We believe that this reluctancecould be explained by IT-related ECO created from both information overloadand too many requests to use IT To test this premise, we conducted a survey ofDutch 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 partici-pants (61%) were concerned about being cognitively overloaded with too muchinformation when they use new Information Technologies Just over two-fifths(42%) felt cognitively and emotionally overloaded with requests to use new Infor-mation Technologies

We concluded that requests to use new technologies can also create brainoverload 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) Forexample, when the smartphone was introduced, one had to forget how to use atraditional camera Indeed, we now look at a screen to adjust a picture instead oflooking 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 individualstry to match the new functionalities of the software or services with the technologythey already know If it differs, they may intentionally forget how they used tointerface with the old technology Intentionally forgetting is cognitively taxing andalso contributes to feelings of burnout and rejection toward new technologies.Overload with IT requests is similar to a component of technostress that is dis-cussed commonly in the popular press

Mary’s strategy is twofold: deleting the email application from her phone andasking us to inform her of the relevance of our emails This meant that we wouldhave to send one email AND a text message in order for her to access importantmessages, multiplying the technologies we use (e.g., computers and smartphones)

Information Technology’s dark side 11

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 ogy We gladly accepted this somehow self-centred request, relieving her of some ofthe“growing pains with information overload” (Rutkowski & Saunders, 2010)

technol-Technostress

Technostress, or the type of stress experienced in organizations by technologyend users as a result of their inability to cope with the demands of organiza-tional computer usage (Tarafdar, Tu, & Ragu-Nathan, 2010), is another darkside 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 pro-blems associated with the organizational use of ICT [Information and Com-munications Technology]” (Tarafdar et al., 2010, pp.304–305) Unlike ourECOM approach, this has not been discussed in relation to emotions, cognitions,

Tarafdar and colleagues have identified five major creators, or components, oftechnostress: techno-overload, techno-innovations, techno-complexity, techno-insecurity, and techno-uncertainty (e.g., Tarafdar et al., 2007; Ragu-Nathan, Tar-afdar, 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 ingreater 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) Inparticular, “SNS addiction incorporates the experience of the ‘classic’ addictionsymptoms, namely mood modification, salience, tolerance, withdrawal symptoms,conflict, and relapse” (Kuss & Griffiths, 2011, p.3530) Brooks, Longstreet, andCaliff (2017) found technostress to be strongly and positively related to Internetaddiction

12 Information Technology’s dark side

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 con-nectivity People in all generations are staying connected too long, and this hyper-connectivity often leads to a range of dysfunctional behaviours including ITaddiction, excessive media multitasking, and Pathological Internet Use PathologicalInternet Use (PIU) has four elements: (1) excessive Internet use, often associatedwith a loss of sense of time or a neglect of basic drives; (2) withdrawal, includingfeelings of anger, depression, and tension when Internet is not accessible; (3) tol-erance, including the need for better computer equipment, more software, or morehours of use; and (4) adverse consequences, including arguments, lying, poorschool or vocational achievement, social isolation, and fatigue (Block, 2008, fromSpada, 2014, p.4)

Hyperconnectivity is being reported among all age groups Tweens (children inthe 8–12 age range) and teens (children in the 13–18 age range) are averaging over4.5 hours and 6 hours a day, respectively, on the Internet A quarter of the teens in

a recent survey reported reaching for their phones withinfive minutes of waking

up (Ipsos MediaCT & Wikia, 2013) They are texting and emailing so much thatemployers of young adults accuse them of having difficulty starting and endingconversations and being nervous when making phone calls (Colbert, Yee, &George, 2016) And older adults (commonly called ‘silver surfers’) are also takingadvantage of access to the Internet and smartphones so that they can be in a state ofconstant communication with others (Colbert et al., 2016) One study evenreported that it is parents, not teenagers or tweens, who spend the most time infront of screens (Molina, 2017)

The challenge to ‘unplug’ is spawning new opportunities for the tourismindustry as tour operators are advocating device-free vacations For example,Intrepid Travel, an adventure travel company, now offers “Digital Detox Trips” inwhich the participants pledge not to bring along any digital devices and must resort

to paper notebooks to record their impressions (Glusac, 2016) Renaissance burgh’s family detox package trades digital devices for board games and cardsduring the family’s stay Further, digital detox retreats have sprung up with offers todisconnect, for a price; and resorts offer an ‘iPhone crèche’ where you can leaveyour mobile devices In the private sphere, the negative impacts of IT-relatedoverload have been linked to the exponential use of Information Technologies.State legislatures are now providing motivation to unplug in other ways InHawaii, ‘smartphone zombies’, or pedestrians so distracted by what’s on theirphones that they are oblivious when crossing streets, arefined Further, 47 statesand the District of Columbia have banned texting while driving (Molina, 2017)

Pitts-In the Net Generation, hyperconnectivity is manifesting a number of newbehaviours Net Geners are people born after 1980; this includes the groups calledMillennials and Generation Y Net Geners have now developed the skill of

‘phubbing’ during conversations, which means that they can maintain eye contact

Information Technology’s dark side 13

while also texting However, the eye contact may not be as meaningful as theythink, because just having the phone in sight likely reduces their conversationpartners’ perception of closeness, trust, and relationship quality (Colbert et al.,2016) Another task that Net Geners may not be as good at performing as theythink they are is media multitasking Media multitasking entails checking mobilephone content as often as every 30 seconds, or even less (Rosen, Carrier, & Che-ever, 2013), an activity which commands high switching costs as multitaskers shiftfrequently from one task to another This may explain why younger users ofmobile phones are significantly more likely than older users to experience overloadfrom 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 ofaddiction called mobile email addiction Symptoms of this addiction are that themobile phone user becomes preoccupied with using the smartphone, has difficulty

in controlling or quitting the behaviour, and gets angry or frustrated when rupted (Turel & Serenko, 2010) Attention deficit hyperactivity disorder (ADHD),depression, and social phobia as well as hostility have been identified as symptoms

inter-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 Thedependence is characterized by: (1) an increasing investment of resources in Inter-net-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, Internetaddictsfind it hard to unplug from the Internet, and they suffer from withdrawalupon doing so (Davis, 2001)

Among American psychologists and psychiatrists, there is no recognition of ITaddiction (i.e., Internet, SNS, or mobile email addictions) or stress That is, noform of technology addiction or technostress is listed in the current version of theDiagnostic and Statistical Manual of Mental Disorders (DSM 5), which contains a formallist of mental disorders This is because many believe that the term ‘addiction’should only be used in respect to chemical substances (Turel & Serenko, 2010) orwhen the person has a physiological dependence on some stimulus, which isusually a substance (Davis, 2001) Others believe that a common set of symptomsand diagnosis criteria are missing (Turel & Serenko, 2010) Hence, in this book weuse the term Pathological Internet Use to describe the behaviours described in theliterature as IT addiction As we discuss in Chapter 4, the lack of control con-sciously exerted by the brain during information processing contributes heavily to

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

14 Information Technology’s dark side

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 fromphilosophy, behavioural and cognitive psychology, neurophysiology, and artificialintelligence to enlighten our understanding of the dark side of IT In this book weaddress three main questions: (1) Why do some individuals experience IT-relatedoverload while others do not? (2) Why do some individuals experience IT addictionwhile 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 Iknow several thousand things that won’t work” (Forbes, 1921, p.89) We foundthis 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 ourown 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 workwell, while others indicate approaches that are less convincing We realize that wemay not have understood the IT-related problem fully Still, we believe we aregetting closer every day Our Emotional-Cognitive Overload Model (ECOM) inChapter 3 is based on cognitive theories of memory architecture that are intro-duced in Chapter 2 We also build on the work of other scientists in order tobetter understand the impact of emotion and pools of resources on IT-relatedoverload and IT addiction The ECOM suggests that not every person experiencesoverload 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 positiveand negative Now is the right time to take a serious look at ‘responsible’ ITuse and the consequences of its mindless use In Chapter 7 we suggest someways of acting responsibly in relation to IT We recognize that InformationTechnologies were originally built to serve humanity However, it seems thatway too many people are being held hostage by various forms of IT: Theysuffer from IT-related overload or IT addiction (or both) But blindly bashingtechnology or imposing rules and policy without a deeper understanding of thephenomena would be sterile This would only increase a misunderstanding ofthe role of technology

The brain and availability of resources are key in understanding the enon Evolutionary theorists determined that Neanderthals had brains of similar size

phenom-to modern humans, sometimes even larger (Ponce de León, Golovanova, onichev, Romanova, Akazawa, Kondo et al., 2008) Through evolution, tools haveserved as efficient resources enhancing our efficiency in our natural environment.Our use of tools has been one of the main competitive advantages over otherspecies in hominid brain development However, if not used mindfully, the impact

Dor-of new digital tools may have the inverse effect on our brain (Chapters 3 and 4)

Information Technology’s dark side 15

Hyperconnected managers and employees may suffer from work-family conflict orjeopardize their work-life balance (Chapter 5).

Grinbaum and Groves (2013) emphasized that any innovation creates ultimatelynew social practices and institutions transforming our day-to-day interaction withthe world and each other In relation to IT innovation, those new practices andinstitutions 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

16 Information Technology’s dark side

Revolutions and paradigms

In 1847, Semmelweis was bucking the science of his time By science, we meanthe organized school of thought relating to specific kinds of tradition in scientificpractice, which include the combination of accepted laws, theories, applications, and

instrumentation Traditions of scientific research are therefore scientific languageswith their own sets of concepts, conventions, codes, and rules, that provide a way

to look at the world through different lenses (Popper, 1959) As Kuhn (1962)informed us, “If science is the constellation of facts, theories and methods… thenscientists are the men who, successfully or not, have striven to contribute one oranother element to that particular constellation” (p.1) In some cases, a scientist’scontribution may result in a paradigm shift, or a fundamental change in scientificpractices By requiring physicians to wash their hands, Semmelweis introduced aparadigmatic shift in medical practices The world view of medicine in 1847 didnot include hygiene, germ theory, or handwashing practices Medicine was ripe for

a scientific revolution, or a dramatic change in science

In this chapter, we present the main paradigm shifts that relate to the nitive revolution– “the mind’s new science” (Gardner, 1987)– that stems fromthe philosophical concept of mind-body supervenience We then apply the lensoffered by this scientific revolution to understand brain overload and IT(Information Technology) addiction

cog-Mind-body supervenience in philosophy: a precursor of paradigm shifts

In philosophy, supervenience is the ontological relation that occurs when upper-levelsystem properties are determined by their lower-level properties, making themhierarchical in nature For example, hardware supervenes on software becausesoftware applications cannot be run without some form of hardware The mind-body supervenience dispute has been going on since before the birth of Christ.The dispute centres around what is in charge (the mind or the body) and how itoperates Multiple answers have been provided, depending on the scientificpractice being deployed

The mind-body supervenience problem is central to philosophy Mind-bodysupervenience holds that mental phenomena must be anchored in some type ofphysical system In the Scholastic-Aristotelian tradition, the mind is conceptualized

as a tabula rasa (viz blank slate) at birth From an epistemological perspective,human mental content is therefore built from bodily perceptions and experiences.Descartes (1644), the father of modern Western philosophy, rejected this splitting

of corporeal substance into matter and stated“Cogito, ergo sum” (I think, therefore Iam) He conceptualized the mind as a thinking substance distinct from the body.Later, the philosopher Kant (1781–1787/2003) criticized Descartes’ rationalisttheories of the mind Kant stated:

The“I think” must be able to accompany all my representations: for otherwisesomething would be represented in me that could not be thought at all, which

is as much as to say that the representation would either be impossible or else

at least would be nothing to me

(B131–B132)

18 The brain and paradigms of the mind

Kant introduced the notion of mental representation and schemata in the firstchapter of his Critique of Pure Reason (1781–1787/2003) Kant described schemata as

a form of analysis in interposition between the sensory data and the abstract a prioricategories in the mind Schemata are dual: one part is rules (i.e., logic) and theother is empirical perception (i.e., image) Kant wrote, “This representation of auniversal procedure of the imagination in providing an image for a concept, Ientitle the schema of this concept” (A140)

Later, Diderot (1818–1819) conceptualized the mind as a metaphor– the soul’svessel He argued that when the material dispositions of the brain are inadequate,the mind is not able to navigate the body vessel In fact, he considered the mind

to be a material entity (i.e., the brain) that, when it functions adequately, controlsthe body

A history of paradigm shifts

The extensive debates regarding mind-body supervenience in philosophy havespawned discussions regarding the supervenience of cognition and emotions, or

of mind-gut feelings, in psychology The primary paradigm shift from phy to psychology occurred when Wundt challenged one of Kant’s postulatesthat mental processes could not be empirically investigated In 1879, Wundtfounded the first laboratory of psychology, at the University of Leipzig, there-fore distinguishing psychology as a separate scientific practice from philosophyand biology Wundt defined psychology as “the study of conscious experience

philoso-as experience” (Gardner, 1987, p.102) Generally referred to philoso-as the father ofexperimental psychology, Wundt applied the method of introspection, whichinvolves attending to one’s physiological sensations and reporting thoughts orimages as objectively as possible The introspection method focuses on thesensation rather than on the stimulus

A second major paradigm shift in psychology occurred when Ebbinghaus (1885/1913) applied the natural science methods to capture internal mental processes.Ebbinghaus was thefirst scientist to establish the memory as a proxy to study thehuman mind In particular, he measured learning and forgetting performancecurves to study the effects of internal processes He measured performance as theretention of bits– that is, one single element of information (e.g., the letter ‘A’ orthe number‘5’)– during learning

While progress in psychology was being made in Europe, James (1890) took an

“American pragmatic approach.… He suggested that psychological mechanismsexist because they are useful and help individuals to survive and carry out impor-tant activities of living” (Gardner, 1987, p.108) This third paradigm shift, whichfocuses on survival, is referred to as functionalism According to functionalists,internal mental processes provide people with the means (i.e., intent) and ends (i.e.,goal) to adapt in order to survive in the environment Through this shift, func-tionalism highlighted the importance of mental dispositions and purpose, a wordderived from the old French porpos meaning aim or intention

The brain and paradigms of the mind 19

The work of functionalists surely fed one of the most famous disputes in chology: the James–Canon controversy on emotion (1884–1929) Cannon (1914,

psy-1927, 1929) stated that brain activity causes both an emotional experience (e.g.,fear) and peripheral responses (e.g., sweating), which is the central view on emo-tion even today James (1884, 1890, 1894) favoured a peripheral view in whichbodily responses must occur before the feeling of fear The debate still animatesresearch in psychology and neuroscience (Ekman, 1984; Cobos, Sanchez, Garcia,Vera, & Vila, 2002) Both the central and peripheral views are still present inresearch on emotions and cognition, and a plethora of definitions for the concept

of emotion are actively circulating in the scientific community In this book, weuse Sherer’s (1994) definition of emotion: the “intelligent interface that mediatesbetween input and output” (p.127) This means adopting, or daring to adopt, acentral view We distinguish emotions from primary drives such as hunger (Tom-kins, 1984) and from feelings, or the subjective experience of emotion We consideremotion as having a specific intentional object (Frijda, 1986), such as a ‘loved one’

or a‘feared one’

Interestingly, this line of reasoning smoothly shifts the mind-body supervenienceproblem toward a new problem, that of cognition-emotion supervenience In psychology,cognition-emotion supervenience is also referred to as the ‘interplay of affect andcognition’ or, more commonly, ‘feeling and thinking’ Obviously, the solutionsproposed in solving the controversy (i.e., central versus peripheral) have shifted as afunction of the dominant paradigm

Behaviourists, cognitivists, and their revolutions

The numerous and extended debates on mind-body supervenience in philosophyhave varied according to the two dominant paradigms: behaviourism and cogniti-vism Behaviourists mostly focus on modelling human behaviour, starting from ananimal’s point of view Typically, they are concerned with stimulus and ante-cedents In contrast, cognitivists try to open the black box of the mind They try tostudy conscious mental processes and operations In this section, we point tothe key contributions of these two paradigms and the revolutions they prompted

We explore their distinctive scientific practices, tentatively reconciling them in thechapters that follow as we seek to understand IT-related overload

Stimulus and antecedents

Watson (1913) launched the behaviourist revolution with a strong focus on theconsequences of the activation of the physiological system on animal behaviour.Indeed, behaviourism is defined as the study of the effects of the environment on theobservable behaviour of individuals without consulting hypothetical events oraspects of cognition that occur within the mind (Carlson & Buskist, 1997) Theunderlying focus of behaviourism is on patterns of observable behaviours provokedexclusively by stimuli Behaviourist research identifies the determinants or

20 The brain and paradigms of the mind

antecedents of individuals’ behaviour while ignoring their mental processes cedents – from the Latin antece-de-ns (viz that go before) – precede the observedbehaviour and are hypothetically governed by a set of natural or social laws Thebehaviourist school is responsible for tremendous progress in experimental psy-chology through the operationalization of the Stimulus-Response (S-R) scheme.Behaviourists developed mechanistic models, where environmental conditions arechanged to alter the probability of certain behaviours occurring and researchers usestatistical approaches in their laboratories (see the work of Pavlov, 1927; Skinner,1935; Hull, 1943) Behaviourists accept the biological nature of organisms anddiscovered laws of behaviour.

Ante-Interestingly, emotion was often at the core of most behaviourist experimentsduring the early 20th century, though only implicitly For example, Pavlov (1927)conditioned defensive responses in animals He presented subjects with a neutralstimulus (e.g., a tone) in parallel with another stimulus (e.g., an electric shock) In

so doing, he demonstrated that the neutral stimulus when used on its own wouldacquire the affective properties of the other stimulus He noted it was possible topair the neutral stimulus to another stimulus such that the neutral stimulus would

be valenced positively (i.e., as reward) or negatively (i.e., as punishment)

In the classical behaviourist paradigm of associative learning, antecedents are muli that cue behaviour They are also perceptive and depend on the environment.Consider Pavlov’s example The bodily perception of the tone became associated

sti-in the animal’s msti-ind with the electric shock, cuesti-ing defensive behaviours Later,the tone presented alone directly cued the defensive behaviour without the deliv-ery of the electric shock Thus, in order to treat maladaptive behaviour, such as thesubject running away or acting aggressively when it hears a bell, behaviouristspropose replacing one behaviour with a healthier one until the original behaviour

is extinguished That could be done, for example, by presenting the animal with apositive reward each time the bell rings Over time, the defensive behaviour isextinguished The behaviourist approach is therefore heavily concerned withrewards (negative and positive) related to the biological centre of reward, which istoday referred to as the Brain Reward System (BRS)

Behaviourist approaches based on associative learning have been extensively used

to explain addictive behaviour– repeated and compulsive in nature, affecting duals and their surroundings This mostly originated with Skinner’s early efforts tounderstand the rewarding effects of certain stimuli on laboratory rats placed in anempty box The rats could ‘decide’ to either push on a pedal to get food (i.e., areinforcer) or push on another one to receive electric simulation in the BRS.Skinner (1935) observed the frequency with which the animals performed abehaviour to get a reward The behaviour (i.e., pushing on one or the other pedal)became a behavioural antecedent through association Some rats went as far asdying from exhaustion, preferring the stimulation to the food This study providedthefirst evidence of brain addiction, which is a form of self-injurious behaviour It

indivi-is a fascinating phenomenon as it does not contribute to the survival of theorganism On the contrary, it may even lead to its extinction, as in the case of

The brain and paradigms of the mind 21

exhausted rats Interestingly, there is no evidence of rats suffering from brainaddiction outside of the laboratory, where the environment is not constructed tofacilitate the addiction That is, in the real world, the rats need to actively searchfor potent reinforcers such as food.

With the evolution of behavioural paradigms, antecedents have been usedextensively as predictors of behaviour Congruently, in the organizational beha-viour and management information systems literature, antecedents are mostlydeemed causal, behavioural (e.g., maladaptive usage), environmental (e.g., workingpressure and technological features), and psychological (e.g., personality) whenresearchers consider brain overload or IT addiction That is, an antecedent is anystimulus that in association with another, impacts behaviour Let us take lying as anexample Applying the behaviourist paradigm, in the child’s mind, lying may beassociated with an efficient means to manipulate his environment The child’s goal

is to either avoid punishment or obtain rewards Thus, applying the behaviouristparadigm to extinguish the lying, the child should be positively reinforced when hetells the truth and his lies should be completely ignored (i.e., not reinforced).Pathological lying in adults occurs when the behaviour has been strongly rein-forced in childhood as a functional behavioural antecedent For example, under asituation of time pressure at work, absenteeism could be a form of deceptivebehaviour used to avoid a high workload

Mental processes were definitely not a concern when behaviourism was at itspeak Behaviourists refused to deal with the black box of the mind; they simplyexcluded mental operations and processing from their studies

Cognitive revolution

Other researchers have observed shortcomings with the behaviourist approach.Simon (1980) claimed that behaviourists did not solve important questions regard-ing the complexity of the human mind Lashley (1929) criticized the S-R scheme

as too simplistic He stressed the importance of understanding the brain by focusing

on complex mental problems, especially problem-solving While, according to theliterature, the cognitivist school is deemed to have emerged as a paradigmaticrevolution in the 1950s, Knapp and Robertson (1986) stated that “the conditions

so often regarded as necessary before cognitive psychology could develop werepresent in years earlier” (p.14) For example, Moore (1938) conducted research to

“throw light on the problem of how knowledge gets into the mind” (p.v) Thuscognitive sciences were forming even earlier than the 1950s For example, the idea

of the cognitive map and spatial representation was introduced when researchersbegan studying the paths of rats searching for food in labyrinths (Tolman, 1948).The functionalist notion of intention is embedded in the very core of the mentalprocesses of problem-solving and decision-making

Cognitivists challenge the S-R scheme and focus their research on how the minddeals with information Cognition refers to the metamorphosis that a stimulus (e.g.,information) goes through while being processed by the human mind Neisser

22 The brain and paradigms of the mind

(1967) wrote, “Such terms as sensation, perception, imagery, retention, recall,problem-solving and thinking, among others refer to hypothetical stages oraspects of cognition” (p.4) Cognitivist theoreticians are the precursors of thedevelopers of artificial intelligence, computer science, and neuroscience (Gardner,1987) They deal with the inner processing of information, working on infor-mation theories,flow, and processing A non-exhaustive list of core topics in thecognitive sciences includes perceptual interpretation, information categorization,evaluation, judgment, problem-solving, decision-making, and learning Cogni-tive scientists have programmed digital computers to perform problem-solvingtasks that were challenging to the everyday human (Newell, Shaw, & Simon,1957) Miller (1956a, 1956b), Broadbent (1958), and Newell and Simon (1972)were instrumental in providing key insights for understanding memory, attentionselection, information processing, and therefore brain overload Newell et al.(1957) designed and implemented a class of information- or list-processing lan-guages that incorporate basic information processes They wrote programs such asLogic Theorist to run on a computer designed to solve difficult problems (Newell

et al., 1957) They accounted for the ‘behaviourist magic’ that occurs inside thehuman mind preceding behaviour Their key contribution was to establish com-plex problem-solving processes and empirically test heuristics, or the operationalpath taken to solve a problem expeditiously They stated that“the programmability

of the theories is the guarantor of their operationality” (Simon & Newell, 1971, p.148) Cognitivists reverse-engineered the mind and developed new models ofmemory architecture following two main approaches: computationist and associative.Computationist models focus on formal operations using symbols to be computedduring information processing Scientists such as Miller (1956a, 1956b) andBroadbent (1958) demonstrated that memory capacity is limited to 7+/−2 bits ofinformation Furthermore, they contributed to the theorization of the process ofattention by viewing it as a limited cognitive resource Bits of information areorganized in chunks; that is, the assemblage of units of a larger number of elements(i.e., information) Based on their relevance (i.e., congruity) with other elements inmemory, they are structured in the form of schemata All schemata are combined

to form a set of mental representations

Associative models (Anderson & Bower, 1973) focus on the activation ofmental representations through node activations These mental representationsare stored and later activated when the brain needs to process new elements ofinformation (bits or chunks) To solve problems, the individual consciously actsupon theses mental representations, which are fused with their stored personalhistory and mental thesaurus Interestingly, Kant (1781–1787/2003) used hisunderstanding of mind-body supervenience to convey the idea that “a schema

is directly activated in terms of sensory experience and yet can be plausiblythought to provide an interpretation of the experience itself” (Gardner, 1987,p.58) Schemata are enriched through personal experiences that build nets ofrepresentations explicitly in the memory Schemata are required for current andfuture problem-solving

The brain and paradigms of the mind 23

As we explained previously, debates on mind-body supervenience have beenwaged throughout the history of psychology The associated theories, concepts, andmethods used to understand the thoughts and actions of human beings have variedaccording to the dominant paradigms: behaviourism and cognitivism In the nextsection, we detail the rich tenets of cognitive theories and associated terminology.

Brain, memory architecture, and emotion

The structure of the human brain has evolved over millions of years in response toour need to survive in hostile environments (Heider, 1946) The human brain hasshown the potential to adapt based on its experiences, processing information andmaking decisions while primarily focusing on survival This evolved nervous systempromotesfitness both directly and indirectly For example, it directly helps us avoidharm by signalling when to remove a hand from a hot surface to prevent a burn.Such reflexes are deemed to be peripheral, rigid, and non-reflective when theyconnect one type of stimulus to one type of response, as observed in the S-R tra-dition They promotefitness indirectly by modifying biological parameters, such asthe peptide hormones and neuropeptides involved in reproductive behaviours andthe attachment to offspring (e.g., oxytocin) Panksepp, Knutson, and Burgdorf(2002) argued on the other hand that the human emotional system is proactivebecause it anticipates fitness-relevant stimulus based on experience Therefore, welearn to avoid putting our hands into afire after having been burned a few times

Human nervous system

The human nervous system is divided into the Peripheral Nervous System (PNS) andthe Central Nervous System (CNS) The PNS and CNS act in concert to processinformation The PNS consists of spinal and cranial nerves, the Autonomic Ner-vous System, and ganglia, which are sensory receptor organs scattered throughoutthe body Information about perceived bodily changes are conveyed as electricalsignals carried via the nervous network to the CNS The CNS is divided into thebrain (containing about 1 trillion cells) and the spinal cord The CNS consists ofthree main functional components: the sensory system, the motor system, andhigher brain functions (e.g., the hypothalamus, subcortical, and cortical areas) Thehypothalamus is a portion of the brain that is particularly concerned with home-ostasis Homeostats, such as regulating body temperature, thirst, and sleep, areenergy-consuming physiological mechanisms (Cannon, 1932) The hypothalamus, apart of the limbic system, is located below the thalamus While the cortical areasare involved in personality, creativity, thinking, judgment, and mental processingamong others, the subcortical areas are involved in consciousness and attentionprocesses All three elements are involved in motivation, emotion, learning, andmemory The limbic system is where the subcortical structure meets the cerebralcortex, the highest level of neuronal organization and function and the uppermostregion of the CNS Neurons are connected to one another through complex

24 The brain and paradigms of the mind

synaptic biochemical and electrical mechanisms that support the body’s activities.Neurons’ neurosecretory cells synthetize and release neurohormones (e.g., dopa-mine and oxytocin) that circulate through the blood and serve as biochemicalmessengers.

Limbic system

The limbic system is a complex collection of structures that is commonly referred to

as the emotional brain or archaic brain In a nutshell, it includes the amygdala, pocampus, thalamus, hypothalamus, basal ganglia, and cingulate gyrus Thesestructures have been studied extensively in order to understand emotion as well asmemory As LeDoux (1998) reported, the“limbic system itself has been a movingtarget… [with] [m]ountains of data on the role of limbic area in emotion… butthere is still little understanding of how our emotions might be the product of thelimbic system” (p.158) LeDoux (1992) demonstrated that the amygdala is a locus

hip-of synaptic plasticity underlying learned fear Research has focused on the pathwaysbetween sensory input to the amygdala, and on intercellular signalling mechanisms.Authors have speculated that this part of the limbic system modulates explicit (i.e.,declarative) memories formed in other systems (Packard, Cahill, & McGaugh,1994) Scoville and Milner (1957) demonstrated that damage to the hippocampusleads to a deficit in Long-Term Memory (LTM) The hypothalamus links the ner-vous and endocrinal systems via the hypophysis The limbic system communicatesthrough secretion of neurohormones and transmitters that control basic bodilyhomeostatic states such as hunger, thirst, mood, and fatigue The limbic system,particularly the hypothalamus, is involved in social attachment behaviour through theaction of the neurohormone oxytocin Oxytocin is also commonly called the‘love’ or

‘cuddle’ hormone It is a key biological parameter in understanding reproductivebehaviours, attachment to offspring, and thus survival of the species

The limbic system also plays a role in substance addiction through dopaminergicprojection to the nervous system Neurohormones such as dopamine are heavilyinvolved in the BRS mechanism, which is a complex cerebral circuit engagingspecific neuronal pathways that are modulated by cortical oversight systems affili-ated with emotion, memory, judgment, and decision-making (Makris, Oscar-Berman, Jaffin, Hodge, Kennedy, Caviness et al., 2008) The major component ofBRS is the mesocorticolimbic reward circuit (Heimer & Van Hoesen, 2006) Inanimals and humans, the BRS is responsive to positive and negative reinforcement.Behaviourists have demonstrated that reinforcement increases the probability of asubsequent response When abused, drugs activate the BRS and are as addictive asnatural reinforcers such as food (Volkow & Wise, 2005)

Interestingly, researchers have found that the limbic system is tightly connected

to the prefrontal cortex (PFC) and therefore involved in many brain functions,such as emotion, LTM, and motivation Damasio (1994) demonstrated that ana-tomic damage to part of the limbic system leads to inability to use affective feed-back in judgment and decision-making A traumatic brain injury in part of the

The brain and paradigms of the mind 25

limbic system leads to impaired emotional reactions to punishment or reward inmonkeys (Kluver & Bucy, 1937) and causes emotional and behavioural dis-turbances (Damasio & Van Hoesen, 1983).

Advances in cognitive neurosciences and understanding of neurocognition(brain/mind) systems (Tulving, 2002) have relied heavily on identifying biologicalprocesses that support cognition and behaviour This scientific practice focuses onthe neural connections in the brain that are involved in mental processes Parts ofthe brain, such as the limbic system and the PFC, play an important role inunderstanding emotion and cognition Cognitivists modelling memories haverelied heavily on advances in the field of neurophysiology For example, thedevelopment of functional neuroimaging techniques (e.g., positron emission tomo-graphy and functional magnetic resonance imaging) has helped researchers under-stand how these parts of the brain function as well as their impact on cognition andbehaviours Despite such technical progress, there is still no comprehensive biologicalmap addressing the broader mind-body supervenience problem

Information processing, models of memory, and cognitive

schemata: an overview

Attention andfilters

The concepts of attention and filters are critical to the study of information cessing and brain overload Attention is defined as “the process of allocatingresources to a stimulus or attributes of a stimulus” (Basil, 1994, p.180) Broadbent(1958) is best known for developing a popular model of information processing.This Filter Model of Attention describes a sieve, orfilter, that selectively accepts orrejects information signals The filter reduces the information processing load on

pro-26 The brain and paradigms of the mind

the cognitive system It deals with one sensory channel at a time as it determineswhat information is recognized Broadbent’s all-or-nothing model explains thebottleneck effect that occurs before pattern recognition However, the modeldoes not account for what is known as the ‘cocktail party situation’ – that is,when a person can be immersed in a discussion at a party and still hear her namebeing mentioned in another conversation If the stimulus is not analysed, asBroadbent proposed, how can its relevance be demonstrated? Nevertheless,the Filter Model of Attention was of extreme relevance in the evolution of theconceptualization of memory and attentional processes in the history of cognitivepsychology It inspired researchers such as Treisman (1964) to investigate atten-tion selection as a function of information content, and its threshold in activatinghierarchical awareness.

Deutsch and Deutsch (1963) suggested a model in which pertinence is thekey to the selection of attention Based on this Pertinence Model, Norman(1969) stipulated that all signals are initially analysed and then passed on to anattenuator before further processing However, the Pertinence Model is noteconomical in terms of the cognitive system’s total load Furthermore, ithas failed under certain experimental laboratory conditions (Treisman &Riley, 1969)

The conceptualizations of human memory and attentional resources as limitedand embedded have their roots in the pivotal article by Miller (1956a), “TheMagical Number Seven, Plus or Minus Two: Some Limits on Our Capacity forProcessing Information” Miller (1956a) quantified the mind’s limited capacity andstated in the unitization hypothesis that the only way to increase the amount ofinformation being processed is “by organizing the stimulus input simultaneouslyinto several dimensions and successfully into a sequence of chunks [so that] wemanage to break … [the] information bottleneck” (p.95) How the items areorganized into chunks determines recall For example, memorizing and recallingthe letters ‘UAKESUU’ is harder than memorizing and recalling the same lettersintroduced as ‘USA UK EU’, because they are grouped together into acronymsthat have associations with terms stored in our memory Thus, memory limits can

be overcome by encoding items into chunks before transferring them to schemata,forming mental representations Mandler (1967) extended the unitization hypoth-esis by proposing the existence of“superchunks” The cognitive system’s ability toovercome its structural limitations opened the way for the two major con-ceptualizations of memory architecture: the Modal Model and the Full WorkingMemory Model

Models of memory architecture

Our discussion of memory architecture models includes a description of the ModalModel (three-store model) for short-term, long-term, and sensory memory Wealso explore the roles of the central executive control system and schemata as theyrelate to WM

The brain and paradigms of the mind 27

Modal Model

The most common representation of the structure of the human memory tecture is the Modal Model (Atkinson & Shiffrin, 1968) The model combines theshort-term storage and attentional system into a single limited-capacity memory:the Short-Term Memory (STM) The model was developed to represent the capacity

archi-of each basic memory store in terms archi-of time and load and is based on theassumption of the existence of two distinct structural components, as proposed byBroadbent: LTM and STM Incoming sensory information that initially enters thesensory memory (SM) store soon decays and then is lost in a short period of time.The STM receives the selected inputs both from the SM and the LTM stores Themodel suggests that the way an input is processed depends on the particularexecutive control processes that the individual activates in the STM (e.g., rehear-sing, searching, deciding, or coding) and on matching with the information held inthe LTM

The Long-Term Memory is permanent memory that is partitioned into two types

of memory: Explicit (i.e., declarative, conscious) Memory and Implicit (i.e., declarative, non-conscious) Memory Explicit Memory is a brain construct that refers

non-to the conscious recollection of factual information, previous experiences, and cepts It is subdivided into the Semantic Memory that acts as a mental thesaurus and theEpisodic Memory that stores personal experiences (PFC and limbic system) (Tulving,

con-1972, 1983) Implicit memory is not a brain system construct since it is non-conscious Itrefers to a heterogeneous collection of abilities (Squire & Alvarez, 1995)

Working memory

Norman (1968) argued that the two stores in the Modal Model actually stitute a single storage mechanism: the working memory The WM’s role is toactivate traces leading to temporal versus permanent change in the cognitivesystem itself Later on, Baddeley and Hitch (1974) focused on the STM store anddeveloped the multicomponent model of the WM In their model, the centralexecutive control system directs, selects, and orchestrates theflow of information

con-so as to overcome limited structural capacity, thus accounting for the cocktailparty situation

The distinction between these models focuses on the STM: it is clearly limited

in the Modal Model and moreflexible in the Full WM model A strength of theFull WM model is that it helps explain information processing in task-switchingcontexts Also, the central executive control system is directly responsible forcoordinating the information used to perform planning activities and make decisions(Baddeley & Logie, 1999)

Later, Baddeley (2000) added the idea of an episodic buffer, which is similar infunction to Tulving’s (1972) episodic memory Schemata guide the way information

is encoded and retrieved from the LTM based on the activation of the associatedcognitive network (Bower, 1981)

28 The brain and paradigms of the mind

Emotions and cognition as interdependent in information processing

To understand the interdependence of emotions and cognition, we introduceBower’s Associative Model of Emotional Memory (1981) and the InteractingCognitive Subsystem (Barnard, 1985) Each approach to emotions and cognitionwas principally built using either the Modal Model or WM

Bower’s Associative Model of Emotional Memory

Bower’s Associative Model of Emotional Memory focuses on both emotionsand cognition Bower (1981) argued that cognitive processes are necessary foreliciting and experiencing emotions His model is based on the informationprocessing view of cognition as an associated network that activates nodesrepresenting specific concepts, events, and clusters in the LTM Each emotionnode is connected to another node representing valenced events (i.e., episodicmemory) and/or valenced concepts (i.e., semantic memory) that have beenactivated previously in association with past experiences of the related emo-tions Memory activation spreads from emotions and from concepts held in thememory Thus, the cognitive schemata are reinforced through a feedback loop

as a function of past experiences Bower (1991) wrote that “about six (plus orminus a few) basic emotion nodes are biologically wired into the brain, and…

a number of innate as well as learned environmental situations can turn on aparticular emotion node” (p.32)

Information processing in memory has proven to be affect-congruent, and itsretrieval is affect-dependent For example, Bower (1981) demonstrated thatanxious people recall threatening material better than non-threatening material Inother words, individuals are more likely to process information that is affectively, aswell as cognitively, congruent (i.e., pertinent) By congruent we mean that thecognitive schemata (i.e., mental representations) in LTM match emotionally andcognitively with the information being processed The match includes auto-biographical events, concepts, and affects When the information is congruent, itselectively and automatically primes associated cognitive schemata in memory.Also, information that is encoded in a similar affective state is easier to retrievethrough reactivation of the associated cognitive schemata Bower’s model predictsthe affect-congruity phenomena, the perceptual threshold for affect-congruent atten-tional biases being higher than it is for affect-incongruent material Again, anxiousindividuals recall threatening material better than non-threatening material (Bower,1981) Like pertinent material, congruent material is deemed to match based onthe actual schemata stored in the mind Bower (2001) clearly established that affect

is a resource used by human memory to process information It presents a selectionbias for self-relevant information At the same time, emotional information is pro-cessed in parallel by brain systems (i.e., the amygdala and hippocampus) responsiblefor identifying emotional aspects as well as the non-emotional, conceptual, orsemantic aspects of information (LeDoux, 1992)

The brain and paradigms of the mind 29

Bower’s model suggests that links between affect and thinking are neithermotivationally based… nor are they the result of merely incidental, blindassociations, as conditioning theories imply Instead, Bower (1981) proposedthat affect, cognition and attitudes are integrally linked within an associatednetwork of mental representations.

(Cited in Forgas, 2003, p.599)Bower’s model is supported by findings from neuroscience For example, LeDoux(1998) emphasized that“conscious memories can make us tense and anxious and weneed to account for this as well” (p.203) That is, the mind can biologically activate abodily reaction when recalling memories Also, neuroscientists have demonstratedthat emotionally tagged signals assist with decision-making processes (LeDoux, 1992;Damasio, 1994)

Interacting Cognitive Subsystem

Barnard looked at affect-based judgement differently than Bower Barnard (1985)proposed a computational approach to model Bower’s associated network Hismodel, the Interacting Cognitive Subsystem (ICS), presents eight subsystems of themental architecture, similar to Baddeley’s (1986) full WM model ICS offers aschematic perspective on the activation of emotion in information processing underprototypical features of emotion-eliciting situations The related schematic modelsare based on experiences in a given culture or family The ICS model proposes thatdifferent histories develop as a result of different cognitive-affective routines Themodel operates at the abstract level of meanings, which“enables the concept of anemotion to be invoked without the experience of it” (Barnard, Duke, Byrne, &Davidson, 2007, p.1173) This explains why highly personal emotional signalsbetter match arousal and valenced memory recognition tasks than low personalsignals ICS proposes that affect-biased judgement occurs at the schematic level(i.e., abstract model of experience), whereas Bower focuses on specific conceptuallevels (See Teasdale, 1993, for a comparison of these models.) Both models provide

an interesting explanation of subjective organization of memory (Tulving, 1972).Emotion and affect have been studied extensively to determine how they influencecognition and behaviour Interestingly, Schwarz (1990) indicated that when won-dering about how we feel regarding a certain target, we may mistake feelingsexperienced due to a pre-existing state for a reaction to a target This may explainthe common saying that‘you only have one chance to make a first impression’

Behaviourist and cognitivist: enemy brothers

The scientific practices used to understand the thoughts and actions of humanbeings have varied according to the dominant paradigms of behaviourism andcognitivism Both have contributed to a better understanding of the mind andbehaviours However, fundamental similarities between cognitivists and behaviourists

30 The brain and paradigms of the mind

are often overlooked (Bargh & Ferguson, 2000) Above all, both schools considerthat“mental and behavioural processes… can proceed without the intervention ofconscious deliberation and choice” (Bargh & Ferguson, 2000, p.925) In addition,the study of emotion and feelings initially was perceived as a curse by both para-digms The science of‘computer-like operation’ is not about emotion according tocognitivist Neisser (1967) and his colleagues Only later did behaviourists considerpersonality traits to be antecedents of behaviour (Zajonc, 1980) Finally, bothparadigms initially addressed emotion and differences in personal disposition asnuisance variables that needed to be controlled or even ignored.

Eventually, both paradigms evolved toward a greater consideration of emotionthrough the common concept of association Behaviourists pair stimuli togetherthrough conditioning, whereas cognitivists match stimuli to mental representationsthrough information processing (Skinner, 1985) Both also address emotions andaffect through concepts such as positive and negative nodes or the BRS Further-more, the consideration of personality disposition evolved for both Interestingly,both approaches even aimed to expel all vocabulary relating to mentalism– the ter-minology of the mind, used particularly in psychoanalysis (Gardner, 1987)– fromtheir scientific practices

Nurture versus nature debate of individual differences

As we discussed earlier, behaviourists, in the Scholastic-Aristotelian tradition, sider the mind to be a tabula rasa Thus, their paradigm surely favours a nurtureperspective on the mind, where environmental characteristics shape and predictbehaviours Consequently, personality is built from environmental and perceptualexperiences and consists of observable behaviours Here, we define a personality trait

con-as the tendency to manifest particular patterns of cognition, emotion, motivation,and behaviour in response to a variety of eliciting stimuli (Fleeson, 2001) Each ofthe well-known Big Five personality traits (conscientiousness, agreeableness, neu-roticism, openness, and extroversion) are therefore another form of behaviouralantecedent From a nurture perspective, a spoiled or abused child may turn into apathological liar– a common trait observed in Narcissistic Personality Disorder.Skinner’s laboratory rats may have been nurtured to be the very first rats addicted

to electricity or, more precisely, ‘pedal over-connectivity’ Scores on personalitytests have been significantly correlated to patterns of cognition, emotion, motivation,and behaviour (Eysenck & Eysenck, 1980; Fleeson, 2001)

In contrast, cognitivists see the mind as a pre-existing built-in architecture thathas universal properties They predominantly support a nature perspective of themind Cognitivists regard personal differences to be based on the information proces-sing capacity (IPC) that are resources deployed to cope with the limited nature ofthe memory system Revelle (1994) argued that“personality effects can be under-stood in terms of differences in the way and in the rate at which parameters of thecognitive control system are adjusted to cope with changes in a constantly varyingworld” (p.347) Cognitivists predominantly use cognitive style and expertise instead

The brain and paradigms of the mind 31