Materializing the implications of data gathering in a
Nina Cecilie Højholdt
Master’s Programme (120 credits) 15 credits
implications of data
gathering in a domestic
Nina Cecilie Højholdt
Thesis project 1 - 2017
Interaction Design Master’s Programme Malmö University
1.0 Introduction 5
1.1 Research area and scope 5
1.2 Introducing Tomo 6
1.3 Research approach and method 7
2.0 Background 8
2.1 Smart, connected, everything 8
2.2 Early explorations: Creating a critical smart artefact for the home 10
2.3 Inspirational projects 13
3.0 Theory 15
3.1 Speculative design 16
3.2 Data collection and privacy in the age of pervasive computing 18
3.3 Big data and AI 19
3.4 Expressing data through manifestation in the physical world 21
3.5 Facilitating attachment 22
4.0 Design experiments 24
4.1 The Data Counter 24
4.2 The Data Mission 30
5.0 A creature that feeds on data 32
5.1 Breathing as the output 32
5.2 Physical form and materiality 36
6.0 Reflection and discussion 36
6.1 The design process 36
6.2 Design outcome - a more nuanced problem 37 6.3 Reflections on the craft of the design 38
7.0 Conclusion and ending remarks 39
This project investigates the implications surrounding increased data collection in a domestic setting. Applying a research through design approach, the project uses sketching and prototyping as a way to materialize and explore the field. Topics such as privacy and Big Data are explored, and the complex relationship between people and data gathering is investigated. This relationship is embodied in the final prototype, an
interactive creature named Tomo, which feeds on the data people produce in their homes. The design of Tomo seeks to communicate these issues applying theory on information visualization, facilitating attachment between humans and computational artefacts and expression of emotion in robotics.
I would like to thank my supervisor Clint Heyer for supporting me throughout this project, for being available when he had no obligation to do so, and for not losing patience or optimism when everything took longer than expected.
I would also like to thank Jesper & Linn for participating in my research, and Thomas & Victor for the great input, discussions and designerly advice throughout this project. And finally, I would like to express gratitude to my roommates for not minding that I researched and set up a “man in the middle” device in order to sniff all activity on our shared home network. I promise I did not look at what you were doing online!
Computers are rapidly moving from being screen-based tools for productivity into the realm of everyday life. From using biometrics to unlock our phones to having intelligent thermostats that regulate the heat in our houses and asking our digital home assistants to note down our grocery list, we invite computers to enter the more private and intimate parts of our lives, which were previously reserved for a select few. Networked sensors and artificial intelligence is put in everything from pillows, juice machines and ovens, to
menstrual cups and toothbrushes. Astonishing amounts of data is collected and this data is becoming more detailed, more sensitive and more valuable. The trade-off between
services, conveniences and benefits in exchange for data becomes increasingly complex, and as more personal data is at stake, privacy concerns become more severe. However, while people are increasingly worried about their privacy, opinion and behavior does not necessarily go hand in hand. We gladly invite data-collecting devices into our lives and enjoy their services, while at the same time fearing what consequences they might have on our lives. At the same time, the rise in Big Data has provided us with increasingly sophisticated methods of analyzing and extracting information from these growing datasets. Artificial Intelligence driven by these data sets give rise to new discoveries, improved services, greater efficiency. As this paper will show, some argue that these new data-driven technologies will be what solves food security and climate change. And others argue that the surveillance society has effectively materialized and that it will bring
discrimination and abuse of power.
This project takes a research through design approach to exploring the above mentioned problem space, and results in a final prototype, Tomo.
1.1 Research area and scope
This project seeks to explore some of the implications that arise when the objects we surround ourselves with start gathering data about us. The project seeks to illuminate the topic from multiple angles and discourses, covering issues such as privacy and Big Data. The project focuses on data submission from everyday objects in a domestic setting, in order to focus on a novel problem, but also limit the scope. The problem sought to explore then becomes:
What are the implications surrounding data collection in a domestic setting and how can
these be embodied in an interactive artefact?
Being placed within interaction design, the project seeks to employ a research through
design approach, using prototypes as a way to materialize ideas and the knowledge gained. The project does not seek to find solutions to problems or answers to questions, but rather to ask questions and challenge values.
The project’s aim is to result in an artefact designed for a possible future, seeking to illustrate the problem of data collection in a domestic setting from multiple dimensions. However, the goal is not to create a fully-functional final product or prototype. The prototypes created are intended as design tools and as means of inquiry and exploration.
1.2 Introducing Tomo
In order to illuminate the implications regarding data gathering in a domestic setting, I have created a series of conceptual design experiments and prototypes. These have resulted in a final prototype, a critical design artefact, named Tomo. Tomo is a creature that lives in one’s home and feeds on data. The more data there is produced and captured in the home, the happier and healthier Tomo is, illustrated through calm, rhythmic breathing (the artefact moving up and down). If undernourished, Tomo will start gasping, and eventually decrease in size and die.
Figure 1, Tomo
Tomo is designed to facilitate a relationship between the human user and itself, in order to illustrate the complex relationship we have with data submission. By giving away our data, we are in return given better services, personalized experiences and convenience. Furthermore, we are contributing to the Big Data pool and Artificial Intelligence systems, promised by some to solve the world’s problems. This is illustrated by the happy, cute creature living with you, which depends on you for its survival. At the same time, it feels forced; data is largely collected without our informed consent and knowledge, and though most of us feel invaded on our privacy, it is too complicated, inconvenient or downright impossible to opt-out. This is illustrated by the pressure Tomo puts on you to keep it alive, keep it happy - because who would want to kill such a cute little thing?
1.3 Research approach and method
My methodological approach has relied mainly on applying research through design (RtD), a method which draws on design practice and processes as a way to conduct research. RtD seems appropriate for the research problem, as it “allows researchers to rely on
designerly activities as a way of approaching messy situations with unclear or even
conflicting agendas” (Zimmerman, Stolterman, & Forlizzi, 2010, p. 310). When applying RtD, the focus lies not on designing for the present or past, but using prototypes and
materialized ideas to reflect on potential and/or desirable futures. Zimmerman et al. (2010) describes RtD as a non-formalized approach without a specific way of documenting the knowledge gained. Rather, it revolves around applying an iterative approach to make a concrete design artefact, which then becomes the carrier of the knowledge gained; an implicit theoretical contribution. Additionally, RtD can lead to theory for design, theory that is developed in order to improve design practice. This can take the form of conceptual frameworks, guiding philosophies, implications for design or design implications (Zimmerman et al., 2010).
In order to apply research through design, my project has taken an iterative approach, using design experiments and prototypes as a way to reframe and reflect on the problem at hand. Using practices and processes from the field of design, I have used sketching and various levels of prototyping in order to drive my project forward and gain new insights.
This chapter seeks to uncover some of the underlying motivations for this project. The first section is a review of the current state of smart home products - that is, data collecting artefacts designed for a domestic settings.
Following that, a short overview of some of the explorations, inquiries and ideas which formed the beginning of this project is presented. While these are not directly relevant to the final problem space and resulting design, they laid the foundation for my further work, and I have therefore chosen to include them.
Finally, I will present two inspirational interaction design projects, which have made an impression and inspired my project.
2.1 Smart, connected, everything
Throughout the project I continuously explored existing data collecting products for the home. A deep understanding of the context and current state of your design field is important; knowing the newest developments and the extend of the situation, enables a designer to create something meaningful and insightful.
While most products mentioned in this section are re-designs of existing products, “home assistants” (smart speakers embedded with microphones and intelligent virtual assistants) on the other hand is a new category of connected devices. These include the Google Home1 and the Amazon Echo . While these device’s always-listening microphones have 2
caused debate, the announcement of the Amazon Echo Look was even more
controversial. The Echo Look is described by Amazon as a “Hands-Free Camera and Style Assistant” ,3 but has received much criticism for being a way for Amazon to embed a camera in your most private sphere, gathering very vulnerable data, on a doubtful foundation (Barrett, 2017; Vincent, 2017).
From intelligent home assistants, let us move into the realm of pre-existing products, redesigned to be connected and smart or intelligent. While I had the impression that a large number of smart home products were already in development or on the market, I was surprised to learn just how many things has been re-invented into a smart version. Surveying technology news sites, such as Wired, The Verge and Forbes, as well as crowd-funding pages like Kickstarter and Indiegogo, numerous examples of relevant 1 Google Home website
2 Amazon Echo on amazon.com 3 Echo Look on amazon.com
products were found, all placed in the home, and all gathering huge amounts of data about their users.
Starting in the bedroom, along with the Echo Look, several smart pillows are in
development and production, such as the Zeeq Smart Pillow and Sunrise Smart Pillow . In 4 5
addition to playing music and waking you up, these pillows are able to monitor your sleep patterns, using technology such as microphones, gyroscopes and accelerometers.
Figure 2, the Zeeq Smart Pillow & the Toasteroid
Moving on to the bathroom, after being woken by a smart pillow, one could clean their teeth using the Ara toothbrush, which is claimed to be “the first toothbrush with Artificial Intelligence” ,6 using deep learning algorithms to analyze your brushing data. Or if that’s not sufficient, there is the Prophix which, in addition to tracking your dental care like the Ara, 7
also live streams video of your brushing to your phone. Furthermore, the Nokia Hair Coach smart hairbrush will use various sensors to analyse your hair and send you the results via
Bluetooth or Wi-Fi.
Continuing to the kitchen, most appliances seem to exist in a smart version. Examples includes SMALT , a smart salt shaker, Samsung’s range of Wi-Fi connected stoves which 9 10
enables the user to monitor their stoves remotely as well as turn the oven on. And the Toasteroid ,11 a toaster that will remind you to pay bills or have loved ones remotely send you messages, burned into your morning toast. And last in the kitchen: The often ridiculed Juicero, a $400 juice presser, which only works when connected to Wi-Fi (see figure 3).
4 Zeeq Smart Pillow on kickstarter 5 Sunrise Smart Pillow on kickstarter 6 Ara website
7 Prophix website 8 Hair Coach website 9 SMALT website
10 Samsung smart stove announcement 11 Toasteroid website
Figure 3. Retrieved from Twitter on August 17 2017
Furthermore, one might use one of several smart water bottles and cups to track fluid 12 13 14
consumption, or keep an eye on ones pets with Furbo , a digital “dog sitter”, featuring a 15
HD camera and microphone, able to notify you when your dog is barking, as well as a treat dispenser. And then there’s LOONCUP , a bluetooth enabled menstrual cup, which comes 16
with an app for tracking one’s cycle, as well as color and volume of the blood. While some of these products might seem silly or harmless, we can not deny that
introducing them to your home will result in massive amounts of data gathering about your daily activities.
And while having these artefacts in your possession might not be a commonplace thing (and some of them are not even available on the market yet), their existence is a reality, which invites for a discussion on the implications of such artefacts.
2.2 Early explorations: Creating a critical smart artefact for the home
This section will cover some of this project’s early research and ideas. While the research was eventually largely irrelevant and the ideas abandoned, they laid the foundation for the further work, and I have therefore chosen to include them.
12 Hidrate Spark on kickstarter 13 Vessyl website
14 Ozmo Smart Bottle website 15 Furbo on Indiegogo 16 LOONCUP on kickstarter
For quite some time, the project was focused on redesigning everyday objects in the home, making them smart, but from a critical design (see section 3.1) point of view. I sought to create artefacts so obscure that they would surely provoke reflection on the need for embodying the objects surrounding us with technology.
2.2.1 Field Research DONE
In order to find design openings for designing an obscure smart artefact for the home, I conducted two types of field studies; a personal inquiry into my own home, as well as two field inquiries in the homes of friends.
The first study into possible objects of interest, was done from a very personal point of view, by exploring and pondering about which objects I myself surround myself with, and which would be interesting design openings. For three days, I went through my daily routines, noting which objects I interacted with and my experience with them, e.g. how useful, interesting and pleasant the object felt. These observations were then collected, and the ones that stood out as notable were chosen for further considerations.
The objects that people chose to surround themselves with and interact with daily undoubtedly varies greatly, so in order to gain more perspectives and insights, I chose to conduct field studies. Due to time restrictions, I ended up doing two inquiries, in the homes of friends. The two friends, however, were chosen because of their very contrasting relationships to technology; one is an avid user and developer, the other just recently acquired a smartphone.
From this research, I gained several interesting insights. Firstly, I found that although the market for everyday objects embedded with technology is huge and growing, neither myself nor my friends had many online objects in the home. One respondent and myself have a “smart TV”, but besides that, computers and smartphones were the only connected objects to be found. This suggest that the prevalence of smart, connected objects might not be as common as I had anticipated.
Furthermore, I learned that the scope of objects in the home one might interact with on a daily basis is lower than expected. When asked about what objects my respondents would use throughout their day, the number was small; mostly objects residing in the kitchen and bathroom were mentioned. However, to both of my respondents, the usefulness of an object did not correlate with its value. Sentimental value, aesthetics and politics (e.g. being environmentally friendly) counted much beyond usefulness and often of use, in regards to what objects they cherished the most. While not inherently groundbreaking, this insight pointed me towards designing an object that is not necessarily useful, but can be appreciated (or resented) for its embedded values or story.
These insights, of course, cannot be generalized, as they are drawn from a very narrow set of data. Both in quantity as well as diversity (everyone belonging to the same social group) the scope of the research is very limited. The intentions behind the inquiries however, was not to gain representative insights and knowledge, but rather to get a more personal perspective on the state of smart homes, than what is presented by the media and especially the manufacturers of smart home products.
2.2.2 Conceptual ideas
Following this research, concepts for a number of obscure, critical smart-home products, were sketched and explored. The electric kettle was chosen as the object of interest, as it was mentioned by both field study subjects as a part of their daily routine; redesigning an object which everyone can expected to be familiar with and have a conceptual model for was intriguing). Furthermore it was interesting to me because of its single-purposeness (to boil water).
The idea of The Vitamin Kettle was conceptualized in order to play on a prevalent societal trend; the pursuit to stay extremely healthy. Juice detoxes, speciality diets and, on a technological level, fitness tracking as a part of the quantified self movement, all play into this. The Vitamin Kettle was thought as a critical design piece, appropriating such trends in order to become an object of desire, while collecting some of the most intimate and vulnerable personal data - blood samples.
Figure 4, Mapping of the features of a kettle
With The Vitamin Kettle, the user would experience a small needle prick on the finger as they turn on the kettle. From the resulting blood sample, the user’s nutrition levels would be analysed and appropriate vitamins and minerals would be added to the boiling water. Thus, making sure the user would always be the healthiest version of themselves, while simply consuming their morning coffee or tea.
After conceptualizing The Vitamin Kettle, however, the survey of the existent smart-home market covered in section 2.1 was conducted, which eventually led to the abandonment of the concept.
2.2.1 A fresh focus
While this project should not deal with my personal experiences, it would be neglectant not to mention the eerie feeling that crept over me, as I wrote section 2.1. Up until that point, this project sought to create a critical, satirical artefact, which would surely question the need and usefulness of data-collecting, connected, smart artefacts. However, after researching the current state of these products and continuously sketching on The Vitamin Kettle and similar concepts, I came to a realization: I would not be able to create
something adequately extreme for a critical design piece on the topic. While the
shock-factor greatly resides in the sum of the connected products, some of them stand out individually as very provoking to me, not far from the reality of The Vitamin Kettle. The pillows collecting data in your bed, undoubtedly making the receivers able to interpret the users’ sexual lives. The menstrual cup, residing in one of the most private of all places, collecting data which will inform the analyst of not only the user’s reproductive health, but her whole body.
While these devices might not be extreme on their own, or as merely collectors of data, it is the opportunities they foster that can seem eerie, both in the wake of the data being analysed, and especially when they exist in unison. As I will cover in subsequent section, the large amounts of data we submit about our online activities have great value for a number of parties. And as this data collection is literally moving into our homes, and the data becomes increasingly personal, how will that challenge our values and ideas about privacy?
I therefore made the decision to shift focus and abandon the Vitamin Kettle. Undoubtedly, there is room for making critical smart home design pieces, however, for me personally, the data resulting from these artefact and the implications surrounding this, became more interesting than the objects themselves.
2.3 Inspirational projects
Throughout the process, I have looked to existing interaction design projects for
inspiration, teachings on method and fresh perspectives. In the following, I will go over a selected few of those who have made an impression and inspired my design.
2.3.1 Erratic Appliances
Erratic Appliances is a series of critical interaction design objects by Anders Ernevi, Samuel Palm & Johan Redström (2005), addressing issues related to energy consumption. By re-designing everyday objects, the designers sought to explore energy as a design material, as well as making the users aware of their energy consumption when using the objects.
While the issues at hand differs (energy consumption rather than data collection), the approach taken by the designers is very similar to the one adapted in this project. The following quote from their paper “Erratic Appliances and Energy Awareness” (2005) could apply to this project just as well: “If we consider a lack of energy awareness to be, at least
in part, related to the design of our electronic appliances then the obvious question is to
what extent we could use design to promote reflection and critical questioning” (Enervi et al., 2005, Energy Awareness and Interaction Design section, para. 1). While some products make attempts to inform their users of the data collection happening (e.g. Android users being asked for permission the first time an app will try to access some information), claiming that most data collection exists hidden in the background of the design is surely not controversial. Enervi et al. (2005) make the same claim for energy use, and their response is to make designs where energy is taken from being some abstract concept “hidden under increasing technical perfection” (Enervi et al., 2005, Discussion section, para. 1) to making it a central part of the design. Furthermore, by making it more
immediate, embedded in everyday objects, and less user friendly, the user is prompted to reflect on something that is usually hard to comprehend. As the authors write, energy systems, just like big data, are “enormous, intangible structures that are hard to grasp, and
although aware that our actions might have effects also at a global scale such issues are
often remote from our local experiences. To close this distance, or at least remind us of it,
we have created things that respond more directly to local conditions” (Ernevi et al., 2005, Concluding remarks section, para. 1).
The FeltRadio by Erik Grönvall, Jonas Fritsch and Anna Vallgårda (2016) is a project that seeks to explore and make people reflect upon what it would be like to sense and feel wireless traffic. The project seeks to explore the hidden world of the wireless technology we are surrounded by, the Hertzian Space, as named by Anthony Dunne. As such,
Grönvall, Fritsch and Vallgårda’s (2016) project bears much resemblance to mine, as I, too, seek to work with the invisible signals continuously flowing through the air and render them perceivable.
Figure 5, the FeltRadio
In order to explore this topic, the authors created the FeltRadio (see Figure 5), a portable device that “renders Wi-Fi perceivable to the human senses” (Grönvall, Fritsch, &
Vallgårda, 2016, Perceiving and exploring radio and Wi-Fi sectio, para. 5). The device detects signals on the 2.4GHz band, which is often used for Wi-Fi traffic. This signal is then translated into visualisations on an LED display, as well as a wearable electronic muscle stimuli (EMS) device. With the EMS device, the user’s sensorial apparatus is augmented, allowing them to feel the invisible signals surrounding them. The device is calibrated in such a way, that only strong signal presence is expressed.
3.0 Theory DONE
In this section, I seek to outline the theory and knowledge which lies as a foundation for the project.
The first section covers Speculative Design and Critical Design, which builds upon my
research through design approach to this project.
The second section seeks to uncover some of the privacy implications of data gathering in a pervasive computing society, while the third section will look at the consequences of this, namely Big Data and Artificial Intelligence.
The fourth and fifth sections cover some of the theory used to motivate and support my design decisions, covering respectively data visualization and ways of facilitating attachment between humans and computational artefacts.
3.1 Speculative design
Seeking to question and challenge the consequences surrounding smart artefacts in a domestic setting and the data emerging from these, this project positions itself within the broad term of critical design. First introduced in 1999 by Anthony Dunne (and later expanded upon by Dunne and Fiona Raby), “Critical Design uses speculative design
proposals to challenge narrow assumptions, preconceptions and givens about the role
products play in everyday life” (Dunne & Raby, 2007). Rather than being affirmative and problem-solving, critical design is questioning and dissenting, striving to provoke reflection and debate.
Within the large and rather fuzzy field of critical design, we find speculative design, also pioneered by Dunne and Raby. As suggested by the name, speculative design uses design to speculate about how things could be in order to “create spaces for discussion
and debate about alternative ways of being, and to inspire and encourage people’s
imaginations to flow freely” (Dunne & Raby, 2013, p. 2). Rather than enforcing status quo, it asks “what if” questions, which are used to open up for discussion about desirable and less-desirable futures. As such, it is like RtD, which according to Zimmerman et al. (2010) forces researchers to focus on the future. The core of speculative design, however, lies on creating an experience of a plausible future, rather than designing for the probable future.
Figure 6. Adopted from Dunne & Raby (2013)
Figure 6 illustrates the scope of different kinds of potential futures that Dunne & Raby (2013) cover. Possible futures refers to things that could happen, but probably won’t. This is a space of wild imagination, where everything that does not break the fundamental laws of physics is possible. The next cone is the space of plausible futures; a space for
exploring what could actually happen. It is not about prediction, but rather preparing for plausible shifts in society. The innermost cone is the space of probable futures. This is the prevalent space for designers to operate within, refering to the future we expect to happen. Finally, the last cone, the preferable future, is what Dunne & Raby (2013) is interested in; the intersection between the probable and the plausible. It is “not in trying to
predict the future but in using design to open up all sorts of possibilities that can be
discussed, debated, and used to collectively define a preferable future for a given group
of people: from companies, to cities, to societies” (Dunne & Raby, 2013, p.6). It is a room for speculation and exploring scenarios alternative to the probable, as a way to make them tangible and debatable before they occur. And while it is referred to as preferable futures, it is also a space for exploring less-preferable futures, that lie within the probable and plausible, before they happen.
As mentioned above, speculative design is not about prediction, but about possibilities. As a result, it relies on fiction, which “requires viewers to suspend their disbelief and allow
their imaginations to wander, to momentarily forget how things are now, and wonder
about how things could be” (Dunne & Raby, 2013, p. 3). By creating a fictional narrative about the future, the designer can free themselves of current trends, predictions and norms, and use design as a mean to explore ethical and social issues.
Furthermore, when designing for questions, reflection and debate, we step into the realm of conceptual design. Conceptual design is design about ideas, but also ideals. Dunne & Raby come from an industrial design background, and as so, stepping away from the marketplace and into the world of conceptual exploration is less normative than in other fields, however, the concept can be applied to interaction design as well. Creating design that is conceptual, rather than being inherently useful and feasible, is beneficial for all fields of design. With conceptual design, one can speculate using “hypothetical or, more
accurately, fictional products to explore possible technological futures” (Dunne & Raby, 2013, p. 14). By creating fictional products, designers are able to stimulate their imagination and open up for new possibilities in both technology, materials and manufacturing. And by presenting consumers with these products, they can engage critically with them and explore ethical and social issues in the context of everyday life.
3.2 Data collection and privacy in the age of pervasive computing
In the 2005 article, “Privacy in Pervasive Computing Environments –A Contradiction in Terms?”, Johann Čas predicted that the future of computing would significantly increase the amount of data generated and collected about people. “Keyboards or other artificial
input devices will be replaced by natural-language interfaces that observe spoken words,
gestures, or mimics and interpret them as potential commands. Biometric procedures
render it unnecessary to remember passwords or to actively prove any authorization” (Čas, 2005, p. 25). Such a rise in ubiquitous computing would have huge implications for privacy, shaking the very pillars upon which our privacy protection stands. And merely 12 years later, Čas’ predictions are becoming reality. Talking to our phones and using our fingerprints to unlock them is only a small part of our daily interactions with the
increasingly pervasive computers, which, as shown in section 2.1 can reside in almost any domestic object. Čas wrote that pervasive computing conflicts with the principles on which our privacy protection is based, and as we venture into a society where every activity (or inactivity) is monitored, a panoptic society is created. In their 2016 book, Networks of Control, Christl & Spiekermann (2016) argue that the surveillance society has effectively materialized, and Acquisti, Brandimarte & Lowenstein (2015) states that privacy certainly is the issue of our time. As information technology has encroached upon increasingly every aspect of our personal and professional lives, the issue of informational privacy (privacy related to personal data) is becoming increasingly complex and difficult to navigate for individuals. With every action we do whilst online there is a trade-off; privacy in exchange of services, conveniences and benefits. And while more and more data is being collected, the ability to aggregate, analyze, and draw sensitive inferences from individuals’ data is advancing too (Acquisti et al., 2015; Čas, 2005). Christl & Spiekermann (2016) write that people feel a sense of powerlessness in modern data collection, which leads to frustration.
Through an extensive review of informational privacy, Acquisti et al. (2015) uncover three themes that relates to how we, as individuals, handle our privacy whilst online; uncertainty,
context-dependence, and malleability and influence.
Individuals experience considerable uncertainty regarding their stance on privacy. For one thing, this arises from the fact that people are not clear on the extent of the information other entities may possess about them, how that information is used, how it is shared and sold, as well as the consequences of this (Acquisti et al., 2015; Christl and Spiekermann, 2016). Collection and usage of personal data is becoming more hidden, and this
intangibility makes it more difficult to grasp possible consequences and thus make informed decisions about one’s informational privacy. Acquisti et al.’s (2015) main focus is
on the web, but it can be argued that this problem of uncertainty following invisibility, is only enhanced by the rise in pervasive computing. “As more and more devices and
objects include sensors and network connections, data collection is happening invisibly“ (Christl and Spiekermann, 2016, p. 119). Another important aspect about uncertainty is that thought and action does not necessarily go hand-in-hand, when it comes to protection of one’s privacy. Even when people know their privacy preferences (which people are unlikely to, despite being aware of the consequences of their decisions), there is often a discrepancy between attitude and behaviour. Even people who claimed to be highly concerned with privacy, were proved to show little concern with it in their daily behavior (Acquisti et al., 2015).
Related to uncertainty, is the theme of context-dependence. “Applied to privacy,
context-dependence means that individuals can, depending on the situation, exhibit
anything ranging from extreme concern to apathy about privacy” (Acquisti et al., 2015, p. 511). Privacy attitude and behaviour can depend on a number of cues, amongst others, but not limited to, other people’s behavior, government regulation, physical environment, as well as one’s own culture.
Lastly, privacy preferences seem to be malleable and influenceable; “various, sometimes
subtle, factors can be used to activate or suppress privacy concerns, which in turn affect
business practices are still the norm and even misleading rhetoric is used to trick people
into one-sided and disadvantageous data contracts” write Christl & Spiekermann (2016, p. 119). Furthermore, opting out of data collection is becoming nearly impossible as many common things now requires users to sign privacy contacts (Christl & Spiekermann, 2016)
3.3 Big data and AI
However, privacy concerns are not the only outcome of the increased data collection resulting from increasingly pervasive computing. As Acquist, et al. (2015) point out, that
there are many benefits of the increasing interferences drawn from informational data collected online. “Both firms and individuals can benefit from the sharing of once hidden
data and from the application of increasingly sophisticated analytics to larger and more
interconnected databases” (Acquisti et al., 2015, p. 509).
These large datasets are referred to as Big Data, a phenomenon that is rapidly spreading across fields and industries, enabled by the exponential growth in computing power (Crawford, Miltner & Gray, 2014; Christl & Spiekermann, 2016).
A common definition of Big Data by Gartner (formerly META Institute, cited in Christl & Spiekermann, 2016) cite three V’s: Volume (the size of the data), velocity (the data is being produced and handled and high speed) and variety (the types and formats of the data are highly diverse). However, an abundance of definitions exists, and according to Jennifer Dutcher (2014) on Berkeley’s data science blog, it can be argued that “it’s not the size of
data that counts, but the tools being used or the insights that can be drawn from a
dataset” (Dutcher, 2014). Dutcher then further lists 40 definitions from thought leaders in different industries, illustrating the ambiguity of the term. Similarly, Christl & Spiekermann (2016) write that Big Data can refer to the processing, analysis, prediction, and even application of these large data sets.
3.3.1 Applications of Big Data
Processing of Big Data sets can find correlations, which leads to new discoveries, business practices and policies. As an example Acquisti et al. (2015) points to the discovery of novel drug interactions when medical records were combined. Another example, also from the medical industry, is an Artificial Intelligence (AI) currently helping radiologists work more efficiently towards diagnosing cancer and other diseases. In order to train the AI, founder Chen Kuan says that what they need “is a lot of data” (Kuan in Marr, 2017a). Hence, Artificial Intelligence is one field in which Big Data is being applied vigorously. “Even
though AI technologies have existed for several decades, it’s the explosion of data—the
raw material of AI—that has allowed it to advance at incredible speeds” writes Bernard Marr (2017b) in an article on Artificial Intelligence’s reliance on Big Data. While Chen Kuan’s AI needs radiology scans to train, other systems rely on more human data in order to grow their intelligence and thus provide new problem-solving solutions. Marr (2017b) points to the billions of networked sensors which are used to teach AI how humans think and feel. As artificial intelligence is being increasingly embedded in our daily lives this data is extremely valuable. As an example, all the products mentioned in section 2.1 gather data about their users which help them incorporate various degrees of artificial intelligence into their services.