Wearable technologies in organizations privacy, efficiency and autonomy in work

to go far beyond step tracking and “unleash wearable devices to improve medical health monitoring and personal fitness; soft robotics to care for the elderly or assist wounded soldiers;

“Przegalinska’s solid academic insight into the pros and cons of wearable technology allows us to understand not only the technological, but also social, implications of this incoming revolution This fascinating and readable book will become an essential text for both practitioners and scholars, to whom I highly recommend it.”

—Dariusz Jemielniak, Professor of Management in Networked Societies

(MINDS), Kozminski University, Poland

Aleksandra Przegalinska Wearable Technologies

in Organizations

Privacy, Efficiency and Autonomy in Work

Library of Congress Control Number: 2018958596

© The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2019

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Preface

This book was written out of curiosity The Internet of Things is an open field with plenty of emerging, exciting possibilities And even though there already appeared a substantial amount of literature about it, in many ways it remains an unknown territory with numerous traps My motivation to put this book together was to attempt a more holistic view

of the complex landscape of wearable technologies, trackers, and sensors.Emerging technologies always fascinated me I work as Assistant Professor at Kozminski University I did my Ph.D in the philoso-phy of artificial intelligence Currently, I am also a Research Fellow at the Center for Collective Intelligence at Massachusetts Institute of Technology in Boston with tracking technologies at the core of my research interests My background includes diplomatic service at the Council of European Union in Brussels and as an international repre-sentative of the Ministry of Culture and National Heritage in the matters related to media and technology regulations

The broad sphere of high technologies has always been at the core

of my private and professional interests Currently however, even those uninterested have to face the fact that it is going to matter more and more in their our daily lives

Over the past few decades, we have observed how technology has emerged as a strong power and key factor in the effectiveness, collabora-tion, and disruption of organizations and individual lives

We have all experienced the ambiguous impact of various aspects of high-technologies’ acceleration in our daily routines that span from the

positive empowerment of collaborative efforts to its negative aspects envisaged in addictive behaviors, the disappearance of privacy, and sur-veillance Moreover, high technologies fiercely impacted workspaces and the workforce as recent developments range from security and manage-ment to wellness applications Software can manage group discussions that, often enough, result in shared understandings, new meanings, and collaborative learning Cloud technology, mobile technology, col-laboration applications, and highly specialized artificial intelligence bear the promise of radical enhancement of the way we perceive the world, work, and human interactions Technology plays a fundamental role in this process because it allows the Internet users to optimize their time, enhance interactions, promote visibility, and drive continuous collabora-tion Furthermore, with the rise of the Internet of Things, smart data, and increasingly sophisticated machine learning techniques, we will all experience the growing impact of technology in the future.

Warsaw, Poland Aleksandra Przegalinska

Writing this book was supported by Aleksandra Przegalinska’s Polish Ministry of Science and Higher Education’s Grant Mobility Plus (DN/MOB/102/IV/2015).

contents

2 Privacy, Safety, and Autonomy 15

3 Addiction and Distraction 25

6 Context Awareness and Ambient Intelligence 57

7 Wearable Technology: Summary 67

about the author

Aleksandra Przegalinska holds a Ph.D in philosophy of artificial

intelligence She is an Assistant Professor at Kozminski University, rently a Research Fellow at the Center for Collective Intelligence at Massachusetts Institute of Technology (MIT) in Boston She was a recent visiting scholar at The New School for Social Research/Brown University

cur-in New York City (2014) In 2011 Aleksandra worked as the Chairman

of Media Regulation Working Party at the Council of European Union

in Brussels As a William J Fulbright Scholar Aleksandra also majored in Sociology at The New School for Social Research in New York (2012), where she participated in research on identity in virtual reality, with par-ticular emphasis on Second Life

Aleksandra’s current primary research interest include consequences

of introducing artificial intelligence systems to people’s social and sional sphere as well as wearable technologies and human/bot interaction

list of figures

Fig 7.3 Quantification of mental and physical phenomena

Participants could choose more than one category 70 Fig 7.4 Aggregated answers to the question “What are you currently

quantifying?” shows the proportion of physical to the mental

Fig 7.5 The chart presents the motivation for self-tracking expressed

Fig 7.6 The chart presents the frequency of self-tracking

The “irregularly” category means that, for instance,

a person engages in self-tracking only when she reads

a book and wants to take a note of it, or when a person

does not remember when precisely she uses apps

Abstract This chapter is the introduction to the whole book It

discusses the rise and history of wearable technologies as well as the growth of self-tracking communities that extensively use wearable devices In this chapter the reader can also find the outline of the whole book, its concept and main hypothesis related to the future direction of wearable technologies What I am arguing for is that from tracking of simple and easily quantifiable activities, we are currently moving to more complex, robust collaborative and sophisticated forms of tracking the Self and others, also in the organizational context

Keywords Wearable technologies · Wearable electronics ·

Self-tracking · History · Organizations

Towards the end of his presidency, Barack Obama started wearing that Fitbit Surge (Ryan 2015a) and it was related to greater plans for the integration of wearable tech into the American society The administra-tion also announced that the Department of Defense would invest $75 million in a “flexible hybrid electronics” innovation center in Silicon Valley called the Manufacturing Innovation Institute for Flexible Hybrid Electronics The teams in Silicon Valley were supposed to be led by FlexTech Alliance (“Semi’s Technology” 2018), a public–private manu-facturing consortium based in San Jose, to “secure U.S leadership in next-generation bendable and wearable electronic devices.” The goal was

to go far beyond step tracking and “unleash wearable devices to improve medical health monitoring and personal fitness; soft robotics to care for the elderly or assist wounded soldiers; and lightweight sensors embed-ded into the very trellises and fibers of roads, bridges, and other struc-tures across the globe.” Overall, the Manufacturing Innovation Institute for Flexible Hybrid Electronics received a total investment of $171 mil-lion to lead a consortium of 162 companies, nonprofits, labs, and uni-versities, including Apple, Motorola, Kodak, John Deere, and Boeing

At the time of the announcement, the White House published a list of possible wearable tech applications (“Obama Administration” 2015), including monitoring vital signs and physical states to optimize health and lifestyles decisions as well as dramatically improving medical technology delivery—through biomarkers and device implants—which can monitor vital signs for the elderly, those with chronic conditions, and “the soldiers during combat [… ] enabling embedded sensors to monitor the state of commercial automobiles and aircrafts operating in harsh environments such as undersea pressures or extreme temperatures [… ] improving security operations,” with applications in lightweight robotics, as well as,

“next-generation imaging and sensing capabilities, used across the entire spectrum of land, air, sea, and space-based systems [and, last but not least] reducing the electronic systems package size and weight through electronics that conform to complex shapes such as aircraft wings or unattended vehicle platforms, and integrating electronics in clothing and fabrics” (Ryan 2015b)

the rise of wearable technology

“Wearable technology” and “wearable devices” are terms often used to describe electronics and computers that are integrated into clothing and other accessories (watches, glasses, headbands and jewelry) that can be worn on the body (Bousquet et al 2012) Such devices always stay in touch with the body, unless users willingly keep it off The equipment comes with a limited CPU power, battery life, and connectivity In some cases, the devices work better than a smartphone or other devices in the exchange of data in real-time Recently, wearable devices began to have a very large impact in the areas of fitness, health, and medicine Moreover,

in the last few years, wearable devices saw increasing attention of venture capitalists, technology startups, established electronics companies, scien-tists, and consumers Their most popular functions include measuring

or self-appropriated by users These products measure physical activity

in terms of calories burned, record daily activities, track sleep efficiency, and provide extensive information on these activities to the user They could generally be classified as measurement-oriented and passive, but one should also mention that this variety also holds such whose main fea-ture is an active disciplining of the user For example, Pavlok administers electric shocks in the event of user’s breaching of rules Other examples

of such active technologies will also be presented in the further chapters.Monitoring, measuring, and recording the elements of one’s body and life as a form of self-improvement or self-reflection have been dis-cussed and realized since ancient times However, the introduction of digital technologies—particularly biosensing ones—has put them on

a different level and created space for communities organized around tracking activities (Swan 2012b)

Self-tracking has a long history and prehistory that started with ries, scales, wristwatches, thermometers and other simple devices People discussed and engaged in tracking since the ancient times In other words, we monitored, measured, and recorded elements of our body and life as a form of self-improvement or self-reflection Long before the development of the Internet of Things, the seventeenth-century Chinese abacus ring allowed bean counters to perform mathematical tasks by moving tiny beads along nine rows In the 1960s, Edward O Thorpe and Claude Shannon created a smart shoe that could fairly accurately predict the end position of the roulette ball However, few knew about these solutions, which limited them to experimentation (da Costa and de Sá-Soares 2016; Guizzo 2003)

dia-Personal informatics that we know today began in the 1980s with life-logging: the tracking of personal data generated by behavioral activ-ities (Calvo and Peters 2014) However, even though people have long used simple, analog devices to record, reflect upon and regulate their bodily states and processes, we are currently witnessing a dramatic efflo-rescence in the use of digital technology to self-track (Crawford et al

2015)

The proliferation of mobile digital devices witnessed life-logging tools break out of research labs and move to the hands of the masses One could mention here at least two interest groups formed in the sec-ond half of 2008 to explore, brainstorm, and share their self-tracking experiences: the Quantified Self in the San Francisco Soon, others like PatientsLikeMe and DIYgenomics followed

These communities coined and developed the idea of ‘n = we’

under-stood as coming together in health collaboration communities that

made their n = 1 discoveries less anomalous, and statistically

signifi-cant These groups gradually started to resemble social movements

by including in their claims proposals what does it mean to be a bio- citizen (Cooter 2008; Swan 2012a) They advocated for data-sharing, a more proactive health self-management, and playfully performed, gam-ified responsibility-taking Their ultimate goal is to smoothly integrate technology with the human body and make it a part of people’s daily life Within this context, the human body becomes the central element

of Human–Computer Interaction (HCI) through a departure from the desktop-based interaction towards mobile and wearable applications (Bordegoni et al 2012)

The underlying assumption here is that data is an objective resource useful for quick bring visualization and information of a situation, and that—psychologically—data should entail an element of empowerment, control, and fun The goal is not only to gain access to data, but also

to build a motivational system that helps to remove habits that one ceives as harmful from daily routines This objectification of data com-bined with self-regulation is in itself very interesting Wearables, and other sensors, are marketed and perceived as digital coaches whose con-tinuous tracking capacities, big-data analytics and feedback loops can help consumers navigate the field of everyday choice making and better control how their activities affect their health

per-1 INTRODUCTION 5

self-tracking communities

As mentioned above, the appearance of tracking devices on the market generated an outburst of communities that consist of self-tracking enthu-siasts willing to share experiences and collaboratively experiment with the gadgets So far, the most prominent one among them—the Quantified Self—mainly focused on medical tracking applications However, we currently observe the need for an “ambient intelligence” (Zelkha et al

1998; Achten 2005), a notion we will come back to later in this book—not only within self-tracking communities but also among various con-sumers groups—in which intelligent devices can integrate into the everyday surroundings and provide diverse services to everyone This

“ambient intelligence” should be personalized, embedded, unobtrusive, and usable anytime and anywhere The main factor that distinguishes wearable computing from other applications such as smart environments

is the nature of the sensors that are used Smart environment sensors are embedded in the environment themselves They typically consist of wired or wireless sensors detecting or measuring motion, light, temper-ature, humidity, and other conditions that are descriptive of the envi-ronment In contrast, wearable biosensors are positioned directly or indirectly on the body (Nafus and Sherman 2014) and not on the physi-cal environment

Among those biosensors, there is a particular group that attempts to encode something that for a long time was not transparent outside the laboratory context This group consists of brain activity trackers that can be associated with affective computing, that is: bridging emotions and computers The term “affective computing” was coined in 1995 by Rosalind Picard (Picard 1995; Nissan 1999; Picard and Wolf 2015), but had to wait two decades for material manifestations Today we know that the machine can measure emotions in different ways: using text analy-sis, studies of physiological parameters, observing behavioral patterns, facial expressions, and recognizing emotions in voice or body posture of users Concerned by the capacity for new technologies to produce cogni-tive overload, a group of researchers turned to the development of what they call “attentive user interfaces” (Vertegaal et al 2003) Particularly, precise measurement of facial expressions is gaining popularity, because results of this type of tracking can be sold to marketing departments and advertising content producers By tracking the user’s gaze, an interface

can adaptively highlight urgent issues and background those of less importance Furthermore, there appeared new applications in affective computing concerning mental health and mental self-care.

The era of personalized “mind-tracking” that basically consists in direct or indirect tracking of brain activity has long been pronounced upon us (Starner 1996; Axisa et al 2005; Cao 2013) and it is just begin-ning to take shape

Another interesting marker of this change is that wearable gies and sensors are becoming parts of national and supranational strat-egies indicates their potential in transforming societies and economies Already now we can see how they are becoming widespread in healthcare and wellness, hospitality and tourism, as well as the financial app market Health-care and medical industry use wearable apps to collect the clinical data such as blood pressure, pH, as well as other tests like steps taken or calories burned What is more, they quite surely share the biggest bite of the market and emerging as the strongest competitor in the coming days When it comes to travels, tourism, and hospitality industry, wearable apps mainly facilitate location-based tracking of places of interest along with keyless access to real estate and services In banking and fintech sec-tor, the financial institutions, particularly banks, have more opportunity

technolo-to explore the wearable application possibilities, including balance ing, money transactions, or locating the nearest ATM Nevertheless, the economic and financial potential of these devices is much broader, just like the scope of their future applications

check-the outline

In this book, I concentrate on the striking metamorphosis that wearable technologies currently undergo My focus will be rather on the devices and their diverse affordances (Zhang and Patel 2006; Jones 2003; Norman 1999) I will try to show how changes in the usage of tracking devices—even on a very personal and private level—can introduce impor-tant changes in management and organizations For instance, along the lines of humanistic management perspective (Melé 2003; Kostera

2015), companies and institutions should emphasize stimulating ees motivation, activity, and creativity to administer operations through understanding, respecting, and provoking the enthusiasm of people

employ-In general, tracking can bring about several issues that require sive deliberations in this context Development and usage of wearable

More than a century ago, in 1909, Frederick Winslow Taylor

pub-lished The Principles of Scientific Management (Taylor 1914) and started the scientific management movement by studying how work was per-formed and how this performance affected worker productivity Thus, Taylor proposed that by optimizing, automating and simplifying jobs, productivity would increase He also advanced the idea that workers and managers needed to cooperate with one another which was again very different from the way work was typically done in businesses beforehand Taylor believed that all workers were motivated by money and better performance meant more money and individualized assessment of work With bricklayers, he experimented with the various motions required and developed an efficient way to lay bricks His scientific method consisted

of calculating the time needed for the various elements of a task and through that developing the “best” way to complete that task Taylor’s principles included, among others, matching workers to their jobs based

on capability and motivation, and training them to work at maximum efficiency, monitoring worker performance, and providing instructions and supervision to ensure that they were using the most efficient ways

of working as well as allocating the work between managers and workers

so that the managers spent their time planning and training, allowing the workers to perform their tasks efficiently

Taylorian methods have changed the very meaning of work itself and the economic and social integration of most of the working population Far from being rejected by workers, Taylorism became one of the most recognized symbols of progress Far from being an authoritarian and deskilling system, it was constructed as a positive system, giving protec-tion and security It is worth noting, however, that the major problem with Taylorism lay not in the strive for perfection but in the methods of achieving them Taylor’s idea was emphasizing maximizing efficiency and that—from Taylor’s perspective—lay mainly in monitoring performance

to ensure the most efficient ways of working

At the time when Taylor was introducing the principles of scientific management, technological tools for detailed monitoring and control

were rather scarce and limited Nowadays, however, with the exponential growth of the Internet of Things and all connected devices (among which smartphones and wearables play a crucial role) the situation has dramatically changed As Natasha Dow Schull notices, wearable technologies under-stood as key artifacts in a new cultural convergence of sensor technology and self-care are marketed as digital compasses whose continuous tracking capacities and big-data analytics can help consumers navigate the field of everyday choice-making and better control how various physical activities affect their health (Schüll 2016) “By offering consumers a way to simul-taneously embrace and outsource the task of lifestyle management – Schull writes – such products at once exemplify and short-circuit cultural ideals for individual responsibility and self-regulation.” However, with the arrival of new ways of self-tracking and more complex devices, it is no longer about physical activity What is more, private tracking intersects more and more often with professional tracking and a clear distinction between the two is more difficult to find Self-tracking overlaps with tracking others, and pro-fessional performance (where productivity again becomes a key feature) becomes one of the most important parameters to follow.

What I would like to argue for is that from self-tracking of simple and easily quantifiable activities, we move to more complex, robust collabo-rative and sophisticated forms of tracking the Self and others, also in the organizational context During the formative years of the wearable tech-nology boom, marketing was centered almost entirely on consumers However, recent trends indicate that giants in the wearable tech industry are now designing their products with business applications in mind The recent wearable tech influx in the business world was launched with the promise of improving workplace productivity and the overall efficiency of organizations Despite their long history, only recently did these devices begin to significantly impact the areas of fitness, health, and medicine Recently, we could experience and observe the proliferation of tracking hardware and applications along with the emergence of new, collabora-tive aspects of self-quantification, in which the focal point moves from the individual to the platform and its virtual community How and to what extent will the new Internet and Communication Technologies (ICT) technologies have novel cognitive potentialities? What may we expect from these potentialities? What role and degree of agency do we have in the deployment and use of these technologies? How do we build commu-nities through and around them (Swan 2012b; Calvo and Peters 2014)?Wearable devices and smartphones reveal tensions and ambiguous influence of tracking This book presents a balanced view that reveals

1 INTRODUCTION 9

both the positive and negative aspects of wearable technologies My approach toward wearable technologies is unbiased, as I will not present another take on wearable technology only embedded in critical theory Moreover, I will discuss the potential future scenarios for wearable tech-nology in the context of rapid developments of the IoT and as a social and organizational phenomenon

The main hypothesis of my book is that—when it comes to wearable technologies—we have not seen anything yet In other words, it is just a beginning of a revolution that will truly transform our lives in the next two decades We are yet to develop devices that will be “intelligent,” “adapt-able,” and allow significant physical or cognitive enhancement However,

we still may detect the early signs of their arrival Wearable devices like Google Glass and smartwatches open up new opportunities, including robust data collection and insights into user interaction We no longer have

to wake up our smartphone and open an app because wearables allow us

to stay connected at all times And with that connection comes a constant flow of live data that is an opportunity but also a challenge for the most forward-thinking companies, teams, and research groups to create new technologies, services, and even entirely new industries

Often, scholars depict a vision of the future of the Internet of Things

as an abundance and multiplication of sensors This corresponds with the vision of the “quantified body” covered with many wearable technolo-gies and widespread use of such futuristic inventions as “smart dust.”

As I described above, this is a revolution related to context-awareness However, another way to think about it is not as a plethora of devices, but the minimal number that focuses on more holistic tools This approach envisions the rise of wearable technologies as more dependent on the advancements in artificial intelligence and machine learning If major progress happens in this sphere, there may soon emerge truly context- aware systems that do not exist yet (Ilyas and Mahgoub 2016; Perez and Kreinovich 2018)

What I will also try to show is how changes in the use of tracking devices—even on a very personal and private level—can be translated into important changes in management and organizations In this con-text, self-tracking in general, and mind-tracking in particular, can bring about several issues that require extensive deliberations Development and usage of wearable tracking tools par excellence is both a challenge and chance, as tracking technologies can quite obviously become tools

of control and scrutiny at the level not experienced before while taneously bringing back long forgotten management paradigms that

simul-almost entirely focus on increasing productivity Thus, the book hensively overviews the current changes in self-tracking practices and the way they affect productivity and the organization of work.

compre-Moreover, the book is purposefully specific about the examples It critically observes different types and ranges of trackers without put-ting all eggs in one basket Thorough tracing of different functionalities leads to their better understanding I do not discuss self-regulation in the health context, as this has already been diligently done in many dif-ferent ways (Swan 2012b; Schüll 2016), and only touch upon the issue

of discourse around trackers, as there is plenty of literature dedicated to this topic as well (Cederström and Spicer 2015; Pedersen 2013) Thus,

I focus on exposing the more general shift that currently happens within individual self-tracking practices and tracking communities, as well as its potential impact on organizations and group work As the book summa-rizes no particular study results, it opens the subject of wearable tech-nologies and the Internet of Things not only to scholars but also IT and management professionals along with everyone else interested in the cur-rent technological developments

The book comes in two main interrelated parts and consists of six chapters preceded by an introduction The introduction to weara-ble technologies describes their past and current usage both in private and organizational context Here, the work particularly focuses on the evolution from simple trackers like pedometers to more complex and context-aware systems such as such as neuro-trackers and wearable brain–machine interfaces that allow users to measure more sophisticated activities and mental states The tension and ambiguous influence of technology particularly surfaces in tracking The introduction of digital technologies—particularly bio-sensing—has shifted the ancient idea of tracking to a different level and created a space for communities organ-ized around tracking activities

After the introduction, I focus on issues related to challenges and potential threats of the rise of sensors I address the following problems and controversies related to wearable technology:

1 issues with safety, privacy, and the lack of control over data bility (based on the examples of typical trackers such as Fitbit);

accessi-2 the lack of work efficiency due to various online distractions (based

on notification systems of smartphones and smart rings such as Ringly), as well as addiction to social media and technological gadgets (based on the examples of Thync)

1 INTRODUCTION 11

In the second part of the book, I concentrate on the various ments of autonomy, solidarity, and collaboration related to the rise of trackers and sensors such as:

enact-1 autonomy and self-enhancement (based on the examples of vidual tracking devices like the smart jewelry Bellabeat Leaf and the so-called mindtrackers);

indi-2 collaboration (based on the examples of collaborative tracking tools such as sociometric badges);

3 context awareness and ambient intelligence (based on the examples

of bots and such smart sensors that adapt external environment to individual needs)

The last chapter is an extended summary that presents the results of a study related to the usage of wearable technologies, as well as final con-clusions and outline of possible future trends

I illustrate all the challenges and opportunities related to wearable technologies with specific examples of wearable technology with thick description of its functionality, design, and means of interaction with users Even though some examples of technologies appear in chapters about the negative consequences of the technological shifts, this does not mean that the specific technologies are bad Similarly, the technolo-gies that represent the positive impact of technology are not necessarily exclusively good in the way they affect their users

On a more formal note, this book sometimes interchangeably use the notions of wearable technologies, tracking devices, and sensors Smartphones are usually mentioned separately because of their distinctive features and popularity in the society, even though it could be argued they belong to the wearable technology realm In the past wearables and sensors were not necessarily overlapping The size of sensors and front-end electronics made it too difficult to use them in wearable tech to gather physiological and movement data However, today’s sensor is a system that responds to a physical stimulus—such as heat, light, sound, pressure, magnetism, or a particular motion—and transmits the result-ing impulse Such a sensor may be both a single device or a whole mod-ule, whose purpose is to detect events or changes in its environment and send the information to other electronics, frequently a computer proces-sor Sensors and wearables allow continuous physiological monitoring with reduced manual intervention at low cost and can be integrated

into various accessories such as garments, hats, wristbands, socks, shoes, eyeglasses, wristwatches, headphones, and smartphones Some, mostly medical-grade sensors, function on a stand-alone basis, but some cases may still be dubbed “wearable telemedical devices.”

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Axisa, Fabrice, et al 2005 “Flexible Technologies and Smart Clothing for

Citizen Medicine, Home Healthcare, and Disease Prevention.” IEEE Transactions on Information Technology in Biomedicine: A Publication of the IEEE Engineering in Medicine and Biology Society 9 (3) (September): 325–36.

Bordegoni, Monica, et al 2012 “When Technology Has Invisible Hands: Designing Wearable Technologies for Haptic Communication of Emotions.” ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference American Society of Mechanical Engineers, 581–89.

Bousquet, J., et al 2012 “Allergic Rhinitis and Its Impact on Asthma (ARIA):

Achievements in 10 Years and Future Needs.” The Journal of Allergy and Clinical Immunology 130 (5) (November): 1049–62.

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229–43 Oxford: Woodhead Publishing.

Cederström, Carl, and Andre Spicer 2015 The Wellness Syndrome Oxford:

da Costa, Filipe, and Filipe de Sá-Soares 2016 “Authenticity Challenges of

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of Wearable Technologies, edited by Andrew Marrington, ‎Don Kerr, John Gammack, 33 Hershey, PA: IGI Global.

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of Proposed Wearable Devices.” 2013 IEEE International Symposium on Technology and Society (ISTAS): Social Implications of Wearable Computing and Augmediated Reality in Everyday Life, 201–2.

Perez, Jose, and Vladik Kreinovich 2018 “Gartner’s Hype Cycle: A Simple

Explanation.” International Journal of Computing and Optimization 5 (1): 1–4.

Picard, R W 1995 “Affective Computing.” MIT Media Laboratory Perceptual Computing Section Technical Report No 321 1–16.

Picard, Rosalind, and Gary Wolf 2015 “Sensor Informatics and Quantified

Self.” IEEE Journal of Biomedical and Health Informatics 19 (5): 1531.

Ryan, Caitlin M 2015a “Fitbit Surge Spotted on Obama, Cycling Tracking to Come.” Wearables.com

Ryan, Caitlin M 2015b “Wearable Tech R&D Launched by Obama Administration in Silicon Valley.” Wearables.com

Schüll, Natasha Dow (2016) “Data for Life: Wearable Technology and the

Design of Self-Care.” BioSocieties 11 (3): 317–33.

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Abstract This chapter is devoted to challenges and potential threats of the

rise of sensors and wearable technologies The focus is put on the usage of wearable technology in the context of safety, privacy, and the general lack of control over data accessibility One of the examples discussed is a popular activity tracker, Fitbit, that struggled with various data leaks Another exam-ple discussed in the cybersecurity context are spambots, zombiebots and malicious bots An attempt is made to delineate different types of problems related to the way these devices interact with their users, voluntary data shar-ing, and structural capacities of the said devices in terms of data exchanges

Keywords Privacy · Safety · Data · Leaks · Control · Transparency

Quite obviously, alongside the interactive possibilities, wearable nologies enable unprecedented opportunities to surveil individuals In fact, one of the first things that comes to people’s minds when they start using a new device is whether their data is safe and how the device could potentially be hacked This surveillance is problematic for privacy but can also offer novel cognitive and collaborative affordances as the technol-ogy begins to ever more closely fit our cognitive profiles This intimate and ever-present nature of our smartphones and wearable technologies means that ICT ever more closely binds with our organic cognitive fac-ulties and the collaborative nature of our tasks When beacons, fitness trackers, affective sensors, and smartglasses become ubiquitous, fully

interoperable and interconnected it will suddenly become possible not only to check where a person is, but also how he or she feels and even what he or she is possibly up to—which in itself is an actual manifesta-tion of “The Minority Report” scenario The same information that is currently used to help in various medical conditions and motivates to train can be used by an employer to hire or fire somebody This problem has reached into the public consciousness Currently, the first thing that comes to many people’s minds when tracking devices are implemented

in their near surroundings is whether their data is safe Most of us share concerns related to the possible misusage of sensitive data, especially because several scandals related to data leaks were revealed in the recent years (Techworld Staff 2018; Ingram 2018) The recent infamous case

of political consultancy Cambridge Analytica illegally harvesting sensitive data from Facebook affected up to 87 million users, mostly in the United States With the rise of the Internet of Things that allows for building a dense map of accurate and rich data points many people are afraid that data leaks will become even more frequent and problematic

exer-According to Fitbit, the customers use their devices to count the steps they take, measure the distances they travel, track the calories they burn Fitbit builds a very strong and appealing discourse of how their assistive technology can serve the users throughout the day:

2 PRIVACY, SAFETY, AND AUTONOMY 17

You can measure how long you sleep, your sleep quality, your heart rate Want to talk sex? You can measure that too (the fitness aspect and not the size) Add it all up, and you get a huge amount of useful medical informa- tion Here’s the wake-up call: None of it’s private It’s available to every- one and anyone through a public online search (“Why Fitbit” 2018 )

A user of Fitbit benefits from the constant assistance of the device in many ways but so can others The data that he or she generates is very sensitive Let us assume one is wearing a fitness tracker now, and might want to check to see if his or her heart rate is going up In terms of free data flow, the life of a wearable device owner means that one often agrees on releasing that data for uncontrollable circulation There is essentially no doctor/patient privacy or patient privacy or any privacy for that matter That is why monitoring one’s health and collecting data is quite often compared with publishing one’s own medical autobiography online This is because many of the wearable devices come with certain privacy statements Quite obviously, there are various regulations and federal laws that protect our medical information The fitness trackers, however, get a free pass from federal regulation and privacy protection.The Health Insurance Portability and Accountability Act, better known as HIPAA (Centers for Disease Control and Prevention, USA

2003) passed in 1996, set out rules concerning protecting the privacy of the users’ medical information Medical companies, hospitals, and doc-tors have to jump over all these hurdles today to ensure they are meeting strict security standards HIPAA was, however, written way before fitness devices that store data on the Internet came around

Taking into account the US regulatory context, apart for HIPAA, there is also Federal Food, Drug, and Cosmetic (FD&C) Act, which devotes an entire chapter to drugs and devices, and that lays down the law However, according to its general policy, neither it nor the Center for Devices and Radiological Health currently are or intend to examine

if these devices, categorized as low-risk general wellness products, ply with the FD&C Act and implementing regulations The only way a device gets the once-over is if it pertains to a specific disease or medical condition The issue is that the technology has exceeded the law suppos-edly regulating it (Weinstein 2016) As a result, some owners of Fitbit exercise sensors noticed that their sexual activity details, such as duration and the effort involved was being publicly shared by default Fitbit closed

com-a loophole in their dcom-atcom-a to prevent further sexucom-al com-activity dcom-atcom-a lecom-akcom-age,

but the holes are really much bigger and not entirely solvable even by a willing single device producer Moreover, in certain cases, the govern-ment or legal institution could request one’s fitness tracker information and then use it against the owner in a court of law That is what hap-pened to Chris Bucchere, a San Francisco cyclist who struck and killed

an elderly pedestrian Bucchere was charged with felony vehicular slaughter, carrying a potential penalty of six years in prison Prosecutors obtained his data from his GPS-enabled fitness tracker to show he had been speeding before the accident Bucchere’s self-monitoring became a piece of evidence against himself due to a lack of privacy This is not to condone Bucchere—clearly, he committed a crime—rather this just illus-trates one example of surprising use cases for what one might think is harmless personal data

man-Bucchere’s case is perhaps to many of us a positive outcome of nological means of analyzing dense webs of more and more complex data The wearable industry’s boom, is, however, drawing more atten-tion from cybercriminals, and data breach risks are on the rise The global market for mobile health-care apps hit $1.4 billion in 2016 and

tech-is expected to reach $11.2 billion by 2025, according to a recent report from Edina, Minnesota-based BIS Research The wearables present a number of pathways that hackers can use to access patient data Many

of the devices include minicomputers that are vulnerable to cyberattacks, and others have the capability to transfer personal health-care data for storage in remote servers, which presents another vulnerability

armies of bots and the Possibility

of hacking “everything”

In 2015, two security experts from Wired, Charlie Miller and Chris Valasek, demonstrated on a willing victim how a dashboard computer used to connect a vehicle to the Internet could be hacked The experts took control over the steering, brakes, and transmission With the advent

of sensors, possibilities of hacking grow enormously Already now data breaches are an everyday occurrence and the constant flow of data has led to a huge spike in identity theft What the abovementioned exper-iment has also shown is that it is quite impossible to build security measures into every device Other examples support this too Recently, hackers have broken into Internet-enabled baby sleep monitors and spo-ken to the sleeping child They have taken control over home utilities

2 PRIVACY, SAFETY, AND AUTONOMY 19

and medical devices These problems are partially stemming from the fact that the Internet, at its commercial beginnings, was not concep-tualized as something to be protected, but to be as open as possible (Greengard 2015) Thus, today it turns out to be necessary to deploy various protection measures such as malware detection, encryption, kill switches, complex password management systems or firewalls And this brings us to a serious dilemma related to the future development of the Internet of Things Reevaluation of security approaches stands in opposi-tion to the trend I highlighted in the introductory chapter—robustness Smart, robust, holistic devices and interfaces add convenience and bring new levels of interaction but at the same time are much more vulnerable exposed to risks of attacks

The growing proliferation of wearable devices provides these criminals with new avenues to attack and to obtain exponentially more sensitive health-care data The higher the number of connected health-care devices accessing, generating, and transmitting personal information, the larger the “attack surface,” which refers to the sum of all the pathways hackers can use The lack of privacy and security standards for health data not cov-ered under the aforementioned HIPAA is especially disturbing given the value that health information can fetch on the black market (Swann 2018).Another issue closely related to the intersection of trust and trans-parency, is who do we talk to and collaborate with on the Internet I was recently involved in creating bots and various experimentation with them (Ciechanowski et al 2018a, b), as I was observing how bots and chat-bots have spread in the past few years What is often omitted in discussions around wearable technologies and data safety is the issue of emerging bots and social robots which collect plenty of their users’ data and in many ways reseable wearable devices in their functionalities In fact, wearable technolo-gies as new data points present multiple attack possibilities for malicious bots Currently, the largest use of bots is in web spidering or web crawling (Zheng

2011; Olston and Najork 2010), in which an automated script fetches, lyzes, and files information from web servers at many times the speed of a human More than half of all web traffic comes from the activity of bots Online, one finds plenty of instructions on how to grow an army of bots:

ana-Some tag team buddies of mine have grown to over 50,000 twitter accounts each with 1000+ followers Currently they’re averaging a 12% CTR and 8% conversion What does that mean? That’s about 6,000 people clicking through to every CPA they sends out and 8%, or 480 going on

to buy the product If you are in a niche that gets $15 a conversion, that

$7,200 per campaign (they do them in 2–3 day intervals) I’ve seen their backend and his revenue numbers, it’s a lot more than that These guys are doing serious numbers daily, this is just a small glimpse into the potential

of blackhat automation It’s about seeing an opportunity and playing the numbers game (CCarter 2018 )

Today, we often do not perceive bots as helpful computer programs but tools for manipulation or even powerful weapons (O’Donnell 2017) There are plenty of fora and news items about spambots that bombard inboxes with unwanted content and interrupt chats by sending unsolic-ited instant messages Some unscrupulous advertisers use these bots to target individuals based on demographic information obtained from user profiles There are also zombie bots, which are compromised computer programs that become part of malicious botnets developed for large-scale attacks, in which all zombie computers act in unison, implement-ing commands from the master botnet owner For those particularly fond of online collaboration, there is also the threat of file-sharing bots, which are the opposite of anything we would call beneficial collabora-tion Users of peer-to-peer file sharing services usually encounter them when the bots take the user’s query term and respond by stating that they have the file available and offer a link Unsuspecting users follow the link, download the file, open it, and unknowingly infect their computers Moreover, currently, a widespread version of malicious bots are chatbots

so advanced that they neatly emulate human interactions and obtain sonal information from unsuspecting victims Finally, there are fraud bots that run as scripts that attempt to obtain financial gains by generating false clicks for advertisement revenue programs, creating fake users for sweepstake entries and generating thousands of fake votes

per-Taking all that into account, one may state that bots essentially undermine collaboration This is, however, not a complete picture Bots may exacerbate the problem of fake news but the role of bots in the field of collaboration and information sharing is, in fact, very com-plex To address the worldwide concern over the false news and the pos-sibility that it can influence political, economic, and social well-being, Vosoughi et al conducted a study that used a dataset of rumor cascades

on Twitter in 2006–2017 to understand how false news spreads About 126,000 rumors were spread by ∼3 million people False news reached more people than the truth; the top 1% of false news cascades diffused

to between 1000 and 100,000 people, whereas the truth rarely diffused

2 PRIVACY, SAFETY, AND AUTONOMY 21

to more than 1000 people Falsehood also diffused faster than the truth The degree of novelty and the emotional reactions of recipients may be responsible for the differences observed (Vosoughi et al 2018) The most important part of the study revealed that humans incline more to spreading false news, whereas bots spread both true and false informa-tion equally This discovery was contrary to conventional wisdom and provokes a few important questions On the other hand, perhaps we could take a more inclusive perspective towards these new agents that carry information and communicate with humans And, perhaps, we could then end with different criteria for web crawlers and chatbots?New problems are emerging also in relation to the complexity of devices Neural network-based deep learning systems are essentially black boxes will low degree of explainability (Petkovic et al 2018a, b

Shwartz-Ziv and Tishby 2017; “How AI Detectives” 2017) The lem of transparency and explainability is very troublesome itself because

prob-it means many different things and thus generates diverse consequences Neural networks break large computation problems into millions

or billions of pieces They then advance the process step by step—

an architecture famously inspired by our brain Most AI breakthroughs since 2009 have originated from it As impressive as it is, it is an engi-neer solution: throwing a massive amount of data and hardware to the problem Even “classical” machine learning can become unstable with multidimensional problems Many do not believe a data-driven sys-tem can capture human realities But even for simple applications, the black box problem is a limitation Data scientists make constant trade-offs between prediction and explainability In practice, the real “black box” issue is rare outside of large projects started at Google, Facebook,

or Amazon The real question is explanation and uncertainty trust (Hocquet 2017)

The picture is much wider, though Global investigations continue to establish the extent to which citizens are used by the advanced nudging techniques based on the combination of machine learning, big data, and behavioral science, which enable the subtle profiling, micro-targeting, tailoring, and manipulation of choice architectures for commercial or political purposes (European Group on Ethics in Science and New Technologies 2018) This presents many new problems and dimensions for defining what security, privacy, accountability, and transparency are in the twenty-first century

https://www.safetylit.org/citations/index.php?fu-Interaction.” In Advances in Cross-Cultural Decision Making, edited by Mark

Hoffman, 205–14 Cham: Springer.

Ciechanowski, Leon, Aleksandra Przegalinska, Mikolaj Magnuski, and Peter Gloor 2018b “In the Shades of the Uncanny Valley: An Experimental Study

of Human–Chatbot Interaction.” Future Generations Computer Systems: FGCS February https://doi.org/10.1016/j.future.2018.01.055.

European Group on Ethics in Science and New Technologies 2018 Statement

on Artificial Intelligence, Robotics and ‘Autonomous’ Systems Brussels March

9 http://ec.europa.eu/research/ege/pdf/ege_ai_statement_2018.pdf

“Fitbit Homepage.” 2018 Fitbit.com

Greengard, Samuel 2015 The Internet of Things Cambridge: MIT Press.

Hocquet, Philippe 2017 “Trust, and Don’t Verify: The AI Black Box Problem.” Medium.com

“How AI Detectives Are Cracking Open the Black Box of Deep Learning.” 2017 Science|AAAS July 6, 2017 https://doi.org/10.1126/science.aan7059 Ingram, David 2018 “Facebook Says Data Leak Hits 87 Million Users, Widening Privacy Scandal.” Reuters.com

O’Donnell, Andy 2017 “5 Types of Malicious Bots and How to Avoid Them.” Lifewire.com

Olston, Christopher, and Marc Najork 2010 “Web Crawling.” Foundations and Trends in Information Retrieval 4 (3): 175–246.

Petkovic, Dragutin, Lester Kobzik, and Christopher Re 2018a “Machine Learning and Deep Analytics for Biocomputing: Call for Better

Explainability.” Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing 23: 623–27.

Petkovic, Dragutin, Russ Altman, Mike Wong, and Arthur Vigil 2018b

“Improving the Explainability of Random Forest Classifier—User Centered

Approach.” Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing 23: 204–15.

Shwartz-Ziv, Ravid, and Naftali Tishby 2017 “Opening the Black Box of Deep

Neural Networks via Information.” arXiv [cs.LG] Arxiv.org

2 PRIVACY, SAFETY, AND AUTONOMY 23

Swann, James 2018 “Is Your Fitbit Data Safe?” Bloomberg BNA Bna.com Techworld Staff 2018 “The Most Infamous Data Breaches.” Techworld.com Vosoughi, Soroush, Deb Roy, and Sinan Aral 2018 “The Spread of True and

False News Online.” Science 359 (6380): 1146–51.

Weinstein, Mark 2016 “What Your Fitbit Doesn’t Want You to Know.” Huffingtonpost.com

“Why Fitbit.” 2018 Fitbit.com

Zheng, Shuyi 2011 Effective Methods for Web Crawling and Web Information Extraction State College: Pennsylvania State University.

Abstract This chapter addresses the issues of lack of work efficiency due

to various online distractions and addiction The problem of addiction

is discussed both in the context of the current social media landscape as well as the Internet of Things and wearable solutions focused on brain stimulation Additionally, one example of emerging technologies is used

to show how certain technologies that replace other technologies may add up to digital distraction Finally, a tension between technologically reducing distractions and digital absence is discussed

Keywords Digital addiction · Digital distraction · Gadgets ·

Stimulators · Teenagers · Negative effects of social media ·

Overstimulation · Replacement

There are many different problems that manifest themselves quite strongly in the current early IoT-era represented by the intense usage of smartphones In the previous chapter we have discussed privacy, safety and transparency of data, but for individual consumers another problem

is just as burning Quite often one gets to hear that increasing numbers

of people are obese, sedentary, and glued to screens On one hand, we frequently state that it is great that we can use mobile apps to learn lan-guages, play instruments etc., but the price to pay is becoming hooked

on smartphones in the process Kaspersky Lab recently conducted an experiment that unearthed a correlation between productivity levels and

Addiction and Distraction

© The Author(s) 2019

A Przegalinska, Wearable Technologies in Organizations,

https://doi.org/10.1007/978-3-030-00907-6_3

26 A PRZEGALINSKA

the distance between participants and their smartphone The ment (Kaspersky Lab 2016) tested the behavior of 95 people between the ages of 19–56 in laboratories at the universities of Würzburg and Nottingham-Trent Care was taken to balance experimental condi-tions and gender across laboratory sites The study revealed that when the respondents’ smartphone was taken away, participant performance improved by 26% What is more, nine out of ten respondents treated such devices as a “peripheral to the brain” and half of them as “exter-nal memory stick” (Bertrand 2016) In itself, it is an interesting sup-port for McLuhan’s and other scholars’ techno-deterministic speculation (McLuhan 1994; McLuhan et al 2011; McLuhan and McLuhan 1992;

experi-De Kerckhove 1981) on the medium as an extension of the brain This does not have to be negative at all Technology-enthusiasts’ and tran-shumanists’ discourses that will be mentioned in the chapter devoted to ambient intelligence, would actually applaud of the idea

social media

In the late 2017 senior Facebook insiders have admitted designing addictive technology that hooks users and may cause harm to children (Hymas 2018a) Sandy Parakilas, a former Facebook platform manager, claimed the firm’s goal was actually to “addict” people “They know what the negative effects are and they are not being honest,” he said Leah Pearlman, the Facebook product manager who invented the iconic

“Like” button, said she now advised vulnerable teenagers (Donnelly

2018) to beware of the site after she herself became addicted

In response to growing concern, Ime Archibong, a senior Facebook executive, admitted it was now investigating whether “habit-form-ing” behavior is “bringing harm” to users The disclosures are made

in a BBC Panorama program tonight, where the tech insiders express alarm at the way younger children are now being targeted with the launch of Facebook Messenger for six to 12-year-olds (Hymas 2018b) Also, Sean Parker, the 38-year-old founding president of Facebook, recently admitted that the social network was founded not to unite

us, but to distract us “The thought process was: ‘How do we sume as much of your time and conscious attention as possible?’” he said at an event in Philadelphia in November (Solon 2017) To achieve this goal, Facebook’s architects exploited a “vulnerability in human psychology,” explained Parker, who resigned from the company in 2005

con-Whenever someone likes or comments on a post or photograph, he said, “we… give you a little dopamine hit.” Facebook is an empire of empires, then, built upon a molecule (Parker 2018) Parker said that he has become something of a “conscientious objector” to social media Afterward, he reflected with some regret on his own role in helping to mold the sort of company that Facebook would become (Oremus 2017).Such accounts are frequent, the good news is, however, that very few people are genuinely addicted to social media However, many people’s social media use is habitual and it can start to spill over into other areas

of their lives and be problematic and dangerous, such as checking social media while driving Other behaviors may be annoying rather than dan-gerous, but may be indicative of problematic social media use, such as checking social media while eating out with friends or constantly check-ing your smartphone while watching a movie at the cinema Others may snub social contact with their loved ones or friends and prefer to check out social media on their smartphone instead (so-called phubbing; Chotpitayasunondh and Douglas 2016) When it comes to solving the problem of reducing individuals’ use of social media there is no magic bullet While individuals are ultimately responsible for their own social media use, policymakers, social media operators, employers, and edu-cational establishments all need to play their part in reducing excessive social media use

ringly and thync

Our online culture has promoted meaningfulness in terms of online fame and numbers of viewers, and converted time previously spent building face-to-face relationships into interactions online with peo-ple who may not be who they say they are What we have helped to create, willingly or not, often diminishes the social-emotional relation-ships and activities that promote physical, mental, and social health Moreover, our workplace culture escalates stress, provides unlimited caffeine, distributes nutrition-free food, holds back-to-back seden-tary meetings, and encourages overnight hackathons and unhealthy sleep behavior Smartphones were the first wave of devices that worked

as hubs for communication Sherry Turkle who wrote Alone Together:

Why We Expect More from Technology and Less from Each Other (Turkle

2017) believes that current technology has an alienating effect Various studies have shown that our attention spans are growing shorter and the

28 A PRZEGALINSKA

instant reward system that social media provide causes overstimulation

A Pew Research Internet Project (Duggan and Smith 2013) has shown that 87% of teachers say that while digital tools have had a pos-itive impact on learning at the same time they caused “easily distracted generation.” Even the example of pedestrians and vehicles shows it (Dultz et al 2013)

Quite interestingly, there are several devices that are actually trying to solve the problem of devices For instance, Ringly is a piece smart jewelry that keeps the user “active, mindful, and in the moment.”

The bracelet includes activity tracking, mobile alerts and guided itation discourse It allows for fitness tracking, mobile alerts, guided meditation, has an all-day battery and is water resistant The producers promise: “a healthy lifestyle requires balance Track your steps and calo-ries burned while also taking a breather Set mediation goals, and use our in-app guided breathing exercises to help you achieve them.” This prom-ise is followed by a persuasive appeal to the potential customers:

med-Women deserve technology that helps them live healthy, balanced lives without sacrificing style or comfort The days of clunky fitness trackers are behind us Unlike most wearable tech, Ringly stands out as beautiful jew- elry equipped with features to help you stay connected to the people and activities that matter most Enjoy a night out, worry free Be the one who isn’t glued to her phone during dinner Tuck your phone away, but still know when there’s an important call or message.

Thync is a wearable technology that tries to tackle problems with focus by transdermal direct current stimulation (Thync Homepage 2018; Salmanowitz 2016; Goldwasser et al 2014; Pal et al 2015; Shelley

2017) “using the nervous system to change medicine.” Thync is a electronics company developing pioneering treatments for autoimmune disorders and mental health Their fairly noninvasive, bioelectronic platform targets autonomic nerve pathways important in a number of disease processes while providing a relative to pharmaceutical interven-tions The team is focused on Psoriasis as our lead indication and are conducting clinical studies to pursue FDA Thync’s core technology for noninvasively modulating the autonomic nervous system was developed

bio-by a team of neuroscientists from MIT, Harvard, & Stanford It has been tested and used in the consumer health market and subsequently enhanced to become a therapeutic platform

As the founders state, Thync was started “with the vision of creating the first personal technologies that would interact directly with the brain and the nervous system After years of research, our small but power-ful team of neuroscientists and engineers were first able to create a bio-electronic platform to lower stress and anxiety acutely.” Thync brought this technology to the consumer health market via its wearable prod-ucts, Thync Edition One and Thync Relax Pro With over 10,000 peo-ple using Thync products we learned that our technology was used most consistently by individuals with a high need to manage stress, anxiety, and improve their sleep We also learned it was nearly impossible to val-idate the impact of our products on mental health by remaining a con-sumer products company.

As this was taking place, they discovered our bioelectronic platform had the potential to impact autoimmune disorders This discovery was reinforced by increasing evidence and awareness that the nervous sys-tem plays a key role in autoimmune disorders Thus, they took advan-tage of our greatest strength as a start-up and rapidly pursued this direction to generate striking pilot data results in Psoriasis By helping psoriasis patients manage their lifelong condition in a drug-free man-ner, the Thync team argues they can help millions of people and estab-lish a strong foundation for bioelectronics therapies Success will lead to treatments for tens of millions of patients that suffer from mental health, inflammatory disorders, and skin conditions Already as a bioelectronics medicine venture, they are conducting clinical studies to prove that our bioelectronic therapies are not only a new way but a better way to treat

a number of chronic, autoimmune and mental disorders In the sense of

a turbulent journey from nonmedical consumer level and possibly tive device to a professional biomedical device Thync is a very interesting case of the wearable technology incubation process

addic-In this context, the big question is what the addic-Internet of Things and the next wave of sensors will bring Quite ironically, the potential solution to both distraction and addiction is offered by such devices

as Ringly Also, when it comes to lack of attention, a vehicle, cockpit, glasses or a helm could be equipped with sensors designed for facial expression and recognition systems (which channels such as an eye- trackers, gyroscope and many others) to detect tired, drowsy and inat-tentive drivers Here however, yet another dilemma arises The trend of delegating the social role of an expert tracker or tracking community by trusting a device/user community rather than an expert in the field such

30 A PRZEGALINSKA

as doctors, dieticians, trainers, managers is quite visible here Tracking devices were originally meant to complement professional services, but increasingly replaced such services The development and professionalism

of tracking (this term is also known as neurotrackery) and the increase

in trust can be correlated with the deprofessionalization of many sions as well as the increase in generalized lack of trust in experts and by building trust in procedures, averaged algorithms, and machines Finally,

profes-if confidence in experts is replaced by trust in devices perceived as experts and in communities that validate user actions, what role does self- confidence play? Does it depend on the continued use of the trackers? Does trust in one device increase trust in others? What social process emerges from the allocation of trust in devices and the communities around them, and what organizational changes are behind them? If the quantification of values is construed as a deprofessionalization trend

or a peculiar manifestation of bureaucracy, will society lose trust in its supporters and devices? Lastly, what is the impact of self-analysis on the identity: who is “I” as there is a clearly separated “control centre” from the controlled individual?

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