Available via license: CC BY 4.0
Content may be subject to copyright.
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=rfdj20
Download by: [185.158.104.234] Date: 09 September 2017, At: 10:07
The Design Journal
An International Journal for All Aspects of Design
ISSN: 1460-6925 (Print) 1756-3062 (Online) Journal homepage: http://www.tandfonline.com/loi/rfdj20
Interface and Data Biopolitics in the Age of
Hyperconnectivity. Implications for Design
Salvatore Iaconesi
To cite this article: Salvatore Iaconesi (2017) Interface and Data Biopolitics in the Age of
Hyperconnectivity. Implications for Design, The Design Journal, 20:sup1, S3935-S3944, DOI:
10.1080/14606925.2017.1352896
To link to this article: http://dx.doi.org/10.1080/14606925.2017.1352896
© 2017 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group
Published online: 06 Sep 2017.
Submit your article to this journal
Article views: 15
View related articles
View Crossmark data
Design for Next
12th EAD Conference
Sapienza University of Rome
12-14 April 2017
doi: 10.1080/14606925.2017.1352896
© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under
the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted
use, distribution, and reproduction in any medium, provided the original work is properly cited.
Interface and Data Biopolitics in the Age of
Hyperconnectivity. Implications for Design
Salvatore Iaconesi*
ISIA Design Florence
*Corresponding author e-mail: salvatore.iaconesi@artisopensource.net
Abstract: This article describes their biopolitical implications for design from
psychological, cultural, legal, functional and aesthetic/perceptive ways, in the
framework of Hyperconnectivity: the condition according to which person-to-
person, person-to-machine and machine-to-machine communication progressively
shift to networked and digital means.
A definition is given for the terms of "interface biopolitics" and "data biopolitics", as
well as evidence supporting these definitions and a description of the technological,
theoretical and practice-based innovations bringing them into meaningful
existence.
Interfaces, algorithms, artificial intelligences of various types, the tendency in
quantified self and the concept of "information bubbles" will be examined in terms
of interface and data biopolitics, from the point of view of design, and for their
implications in terms of freedoms, transparency, justice and accessibility to human
rights.
A working hypothesis is described for technologically relevant design practices and
education processes, in order to confront with these issues in critical, ethical and
inclusive ways.
Keywords: Hyperconnectivity, Algorithms, Biopolitics, Ethics, Data
1. A Hymn
In her “Hymn of Acxiom” folk singer Vienna Teng (2013) starts off with lyrics “Somebody hears you,
you know that…”, in what seems to be a church choir. After listening for a bit, the real topic the artist
is discussing about becomes clear: Acxiom is not a benevolent divinity somewhere in the cosmo-
sphere caringly waiting to hear the troubles of his beloved human beings, but, rather, a high-
powered data broker which has been described as “the Private NSA” (Tom’s Guide, 2013), as the
silent, largest consumer data processor in the world (Fortune Magazine, 2004) and as “Big Brother in
Arkansas” (NY Times, 2012). The topic of the song is data-surveillance. The idea for the song came
while the author was pursuing an MBA at the University of Michigan: a colleague working with
Acxiom data was shocked about the amount of information the company had available about herself
and her husband. An interesting thing about the song is that the creepy, Orwellian, lyrics also
empathize with databases as well as excoriating them.
S3935
Downloaded by [185.158.104.234] at 10:07 09 September 2017
SALVATORE IACONESI
2
This is, in fact, an interesting point of view. As, on the one hand, we – directly and indirectly –
consent tour data to be collected through our behaviors and basically accepting our lifestyle, on the
other hand we feel deeply uneasy about that and from its implications. As we benefit from
enterprises being able to provide us with products and services which are “more relevant” for us
(more on this later in the article), we are simultaneously wary of the fact that a single subject knows
so much about us and uses it to “sell us” to the highest bidder, and what this possibility implies for
our liberties, freedoms and rights. Even more, it is progressively harder, if not impossible, for us, to
know and understand what parts of our online and offline environment are determined from these
data collection processes, or about which subjects have this data about us available, or how they are
using it and for what purposes (Lafrance, 2014).
In fact, the entries we see when we browse search engines, social media websites, and other online
services are completely determined by these processes: the operators of these services feed the data
they acquired about us to their classification algorithms which, in return, use it to determine what
we may be more and less interested about, or where their optimal business opportunities lay in
relation to our profile.
This is not only true for our online lives: the offline world is quickly catching up. Physical mailings;
fidelity cards; algorithmic research and control applied to stores, services and spaces of the city;
imaging through security cameras; object and facial recognition on devices and architectures; the
Internet of Things (IoT) and its sensors, possibilities for user identification and biometrics. These all
combine with a plethora of other options which are turning us into data subjects, which can be
recognized and tracked on databases as in the physical world.
2. Asymmetry
This scenario also describes a progressive asymmetry in the distribution of power, rights, freedoms
and opportunities (Tufekci, 2014; boyd, 2012).
As a matter of fact, it is practically and psychologically impossible for human beings to understand
which and how much data is captured about them, how and why it is used, and what effects it has
about their lives.
The complex interplay among users; organisation; algorithms; national, international and global
regulations and agreements, or lack of them; data and information flows within user experiences in
the physical and online domains cause grey areas to emerge, at levels which are legal, cultural,
psychological, ethical and philosophical (White, 2016).
"Code is Law", Lawrence Lessig (2006) once said. And this is really the case nowadays. With
thousands of updates and modifications to the interfaces, algorithms, data capture and usage
profiles which are performed each month to the systems of popular services, potentially provoking
radical changes to the implications for privacy, control and accountability, it is practically impossible
for legal and cultural systems not only to adapt and react, but also and more importantly to perceive
such changes and the effects they have on our freedoms, rights and expectations. If a national
government needs to pass through a whole legislative process to approve a new privacy law, an
operator like Facebook can change a few lines of code and yield substantial impact on users’ privacy
profiles. With hundreds of thousands of modifications on platforms like these each year, it is easy to
comprehend the reach of this kind of issue. Moreover, many of these changes are temporary, beta
versions, running in parallel for different users for A/B testing purposes, making the situation even
more complex.
S3936
Downloaded by [185.158.104.234] at 10:07 09 September 2017
Interface and Data Biopolitics in the Age of Hyperconnectivity
Things get even more radical in the case of algorithmic governance of processes, where technological
entities assume progressively higher degrees of agency (and opacity). The Flash Crashes of the stock
markets in 2010 are a demonstration: autonomous algorithmic agents gone berserk causing losses
for billions of dollars, outside of any legal or cultural or perceptive framework (Menkveld, 2013).
As a result, the levels of power and control exercised on human beings and their societies by the
systems that they use are augmenting at exponential levels, and there are progressively fewer and
less effective ways for people to perceive and comprehend such processes.
On top of all of this, the dissemination of interfaces ubiquitously across devices, applications,
websites and other products and services for which today everything can represent a front-end for
digital and data based systems, further augments the incapability to understand the data and
information which is captured from our behaviour and its flows and uses (Weber, 2010).
Sharing a picture of our holidays at the beach on social networking sites does not imply the fact that
it is clear, for us, that we are producing marketing relevant data about our tastes, consumption levels
and geographical locations. And neither is the fact that while using wearable technologies or smart
IoT appliances in our daily lives the data that gets captured can be used for marketing, health,
insurance, financial and even job purposes.
Furthermore, the rise of the Stacks (Madrigal, 2012) and, more in general, of “walled gardens”, or
those situations in which applications, services and products pertain to closed, proprietary
ecosystems which are not open source and for which both the front-ends and back-ends of the
systems are opaque and inaccessible for inspection and understanding further aggravate this
problem.
Both those applications directly and, indirectly, the service levels they provide (for example through
APIs, social logins, application frameworks) on the one hand make applications and services easy and
rapid to develop and deploy, but, on the other hand, subject them to the concentration of power
which these large operators represent. It is very convenient to design and develop anything from
online services to network-connected physical products using, for example, Google’s, Apple’s, or
Facebook’s platforms and services. But, by doing this, it is automatic that our products and services
start producing data and information for these large operators, allowing them to interconnect these
across a rich variety of domains: if I develop application A and someone else develops application B
which is completely different, and we both use, for example, Facebook’s social login to implement
access services, Facebook will benefit from the data generated from both applications, from the
analytics which it desires to capture without even sharing them with A or B, and will be also able to
interconnect both data flows with their own. For example, if application A captures, for example, my
geographic location (it is, for example, an application which allows me to find where I parked my car)
and I have configured my Facebook account so that Facebook is not allowed to know my geographic
location, Facebook will have my position anyway, through application A. This kind of reasoning can
be applied to all the applications, products and services that use these frameworks.
These facts are valid and relevant for the users of these platforms, but also for the people conceiving
and creating these systems, including designers, engineers, managers, administrators, public and
private, who progressively lose the possibility (culturally and technically) to understand the
implications of their designs.
3. Bubbles, Guinea Pigs
An evidence of this occurrence is the emergence of knowledge and information "bubbles".
S3937
Downloaded by [185.158.104.234] at 10:07 09 September 2017
SALVATORE IACONESI
4
In the age of Hyperconnectivity (Wellman, 2001) information abundance quickly turns into
information overload (O’Reilly, 1980). Therefore, relevance becomes an invaluable competitive
advantage and attention a precious currency (Davenport, Beck, 2013).
This is why large operators (from social media services, to search engines, to news and media
operators, all the way up to the ones which extract information from devices, appliances and other
services) use specific algorithms to try to interpret users’ behaviors to try to understand which
content might be more relevant for them, filtering out all the rest (or giving it minor priority, visually
or hierarchically) and, at the same time, ensuring that the content which generates more revenue for
them is granted higher shares of our attention space, to maximize earnings.
These algorithms and software agents also have the effect of tendentially excluding all the rest,
closing us in "bubbles", in which what is outside is not even perceived, or very hard to perceive
(Pariser, 2011).
Information spectacularization (for example through data and information visualization) further
weights down on these processes. Bratton (2008) describes how spectacularized information
visualizations (also called “data smog”) “distance people—now ‘audiences’ for data—even further
from their abilities and responsibilities to understand relationships between the multiple ecologies in
which they live, and the possibilities for action that they have.”
These elements – bubbles, algorithmic governance of information and information spectacularization
–, thus, may bear the possibility that individuals progressively inhabit a controlled infosphere, in
which a limited number of subjects is able to determine what is accessible, usable and, most
important of all, knowable.
This power asymmetry also implies the fact that users can systematically be unknowingly exposed to
experiments intended to influence their sphere of perception to drive them to adopt certain
behaviors over other ones.
This is exactly what happened with Facebook in 2014 (Rushe, 2014; Booth 2014). In an experiment
(Kramer et al, 2014), Facebook manipulated information appearing on 689 thousand users’
homepages to study the phenomenon of “emotional contagion” answering the question: how to
users’ emotional expression change when they are exposed to content which is emotionally
characterized in specific ways. By algorithmically filtering in or out content with specific
characteristics they were able to induce particular expressions. The study (Kramer et al, 2014)
concluded: “Emotions expressed by friends, via online social networks, influence our own moods,
constituting, to our knowledge, the first experimental evidence for massive-scale emotional
contagion via social networks.”
This is not the first case: dozens of other experiments (Hill, 2014) dealing with hundreds of thousands
of unknowing users included analyses of A/B tests, content filtering for specific purposes, comment
and interaction analysis for predictions, spreading of rumors and manufactured information, self-
censorship, social influence in advertising, and more.
In 2014, Jonathan Zittrain described an experiment in which Facebook attempted a civic-engineering
feat to answer the question: “Could a social network get otherwise-indolent people to cast a ballot in
that day’s congressional midterm elections?” (Zittrain, 2014). The answer was positive. And the past
2016 elections also demonstrated further ways in which massive, algorithmic controlled social media
interactions can influence the determination of major events.
In her article describing the effects of computational agency during the Ferguson protests, Zeynep
Tufekci described:
S3938
Downloaded by [185.158.104.234] at 10:07 09 September 2017
Interface and Data Biopolitics in the Age of Hyperconnectivity
“Computation is increasingly being used to either directly make, or fundamentally
assist, in gatekeeping decisions outside of online platforms. [...] Computational
agency is expanding into more and more spheres. Complex, opaque and
proprietary algorithms are increasingly being deployed in many areas of life, often
to make decisions that are subjective in nature, and hence with no anchors or
correct answers to check with. Lack of external anchors in the form of agreed-upon
'right' answers makes their deployment especially fraught. They are armed with our
data, and can even divine private information we have not disclosed. They are
interactive, act with agency in the world, and are often answerable only to the
major corporations that own them. As the internet of things and connected, 'smart'
devices become more widespread, the data available to them, and their
opportunities to act in the world will only increase. And as more and more
corporations deploy them in many processes from healthcare to hiring, their
relevance and legal, political and policy importance will also rise.” (Tufekci, 2015)
4. Interface and Data Biopolitics
The scenario described in the previous sections has important impacts on the “knowability”,
“readability”, accessibility and usability of the world, both in how people use it and interact with it,
and in how they are able to design it.
The implications, together with the systematicity and opaqueness of the scenario, calls for the
emergence of new areas of scientific, technological and humanistic investigation which can be
defined as Interface and Data Biopolitics.
There are multiple definitions for the term “biopolitics”: Kjellén's organicist view and his description
of the “civil war between social groups” (Lemke, 2011); the political application of bioethics (Hughes,
2004); the interplay between biology and political science (Blank, 2001); Hardt and Negri’s (2005)
anti-capitalist insurrection through daily life and the body; Foucault’s (1997) “biopower”, through
governments and organizations applying political power to all aspects of human life; and many more.
We refer here mainly to Foucault’s definition, which described biopolitics as “a new technology of
power...[that] exists at a different level, on a different scale, and [that] has a different bearing area,
and makes use of very different instruments”. (Foucault, 1997, p. 242)
In his analysis Foucault mainly referred to national states and institutions. Therefore his observations
need adaptations to be considered in today’s globalized, financial, digital economies and political
apparatuses of power. For example the rise of large corporations, which match the power, influence,
and reach of national states, the different role of money, its virtualization, and the “finacialization of
life” (Lapavitsas, 2013) are things that need to be integrated in such frameworks.
Fundamentally, Biopolitics can be defined as the study of systems as they leverage as many
manifestations as possible of our daily lives, activities, relations and bodies to exercise power and
control over their users and participants, in explicit and implicit ways.
As demonstrated in the previous sections, today’s scenarios of Hyperconnectivity bring about
multiple forms of biopolitically relevant contexts. Online and application interfaces, biometrics,
wearable computing, IoT, social media and, in general, all human activities with a direct or indirect
digital information counterpart generate data which is harvested by large operators in order to be
processed to influence our actions, behaviors, beliefs and perceptions, and, thus, to exercise power.
The shift to the digital sphere also provokes a shift from “biopower” to “neuropower” (Väliaho,
2014), as the medium for control shifts from body to mind.
S3939
Downloaded by [185.158.104.234] at 10:07 09 September 2017
SALVATORE IACONESI
6
For example, the elements forming an interface exercise a certain degree of power on their users. If
only options A and B are available on an interface, the user will not be able to adopt option C. In
many cases the user will not even be able to perceive that option C is possible. Hence, the interface,
its designer, and the ideology and strategy that comes with both, have a degree of authoritarian
agency over the user.
While registering to online services, many times users are asked to select their gender, to
characterize their online profile. If, for example, only the “male” and “female” options are available,
other options will be excluded and, thus, this could prove to be a problematic, upsetting and
troubling scenario for those who feel neither “male” nor “female”. The business requirements of the
operator, who would need to tag the users with predefined categories that are convenient to be
commercialized to marketing and advertising partners, would have the prevalence.
In another scenario, a wearable biometric device could record data for health purposes. For example,
a recording of a level of 1.5 to 1.8 from the device for a certain bodily value could indicate a
“healthy” condition. If users had a readout of 1.6 they would be considered “healthy”, maybe
corroborating the fact with a reassuring green light visible on the device, or on the associated
application. If, for any plausible reason, the “health” threshold would be changed to a 1.7-2.0 range,
the same users would be described as “not healthy”. The light would turn to red, maybe
accompanied by a message: “visit your doctor!” The body of the users would be the same. They
wouldn’t feel an additional headache or hurt in some other part of their body. By simple variation of
a parameter their status would change, accompanied by a series of authoritative notifications.
This is a very powerful condition. Even taking simpler, less radical and more common examples still
shows how a direct possibility to exercise power through asymmetric capacity of capturing,
processing and visualizing data, and through designing interfaces in certain ways is available to the
operators which own these platforms, systems, devices and services.
With the Internet of Things, this scenario manifests ubiquitously, affecting appliances, our homes
through domotics, our schools, offices, stores and, potentially, the public, private and intimate
spaces and contexts of our lives. As Pasquinelli (2008) puts it: “it is impossible to destroy the
machine, as we ourselves have become the machine.”
On top of that, the power asymmetry manifests itself also in another way. While it is users that
generate data and information by using interfaces, services and products, at the same time this data
is not available to them, nor they have the possibility to perceive the full spectrum of its implications
(Blanke et al, 2015).
As of today, most online services offer opportunities for users to download their own data (for
example through “Google Takeout”). But these options are misleading, because they let users
download their “content”, but not the data, information and knowledge that was generated through
it by processing it. For example, there is no way for users to know in which marketing categories they
have been classified, or what actions they performed led to being classified in such ways.
For example, let’s pretend that Facebook identified the category of “potential terrorists” as their
machine learning processes discovered a pattern in the frequency with which radical extremists use
the letter ‘f’ in their messages. If certain users, by complete chance, created messages using the
same ‘f’ frequency, they would be classified as “potential terrorists”. They would know nothing about
it, and this could have implications on their freedoms and rights. Of course this is a paradoxical
example, just to make clear the dynamics of this phenomenon.
S3940
Downloaded by [185.158.104.234] at 10:07 09 September 2017
Interface and Data Biopolitics in the Age of Hyperconnectivity
Moreover, all this data capturing and processing is designed, as stated in the previous section, to
confront with relevance and attention, thus resulting in information, knowledge and relations
bubbles. While these processes are useful in the scenario of information overload, they also
progressively lock out difference from users’ perception: the more we are exposed to content which
we “potentially like” and to “people we potentially agree with”, the more “otherness” disappears
from our reach. This brings on a series of negative effects, such as the diminished sensibility to and
acceptance of diversity (Bozdag, van den Hoven, 2015), rising levels of cognitive biases (Bozdag,
2013), diminished tolerance, social separation (Ford, 2012), and more.
5. Conclusions: Implications for Design
The scenarios described in this article pose great challenges for Designers and, most important of all,
for Design Education.
On a first level of inspection, it is simple to verify how all of these situations and configurations of
power schemes, practices and behaviors are at the border of what is assessed by laws, regulations,
habits and customs. They are at the same time familiar and new, unexpected, unforeseen, unsought.
To confront with these issues, approaches which are trans-disciplinary are needed, because no single
discipline alone is able to cover all of the knowledge, attitude, perspective which are needed to grasp
and understand them.
The possibilities and opportunities to meaningfully deal with the issues presented in the article
emerge only at the intersections between law, psychology, culture, philosophy, sociology, ethics and
other sciences, humanities and practices.
This fact represents an important opportunity for design, which can act as a convenient, practical and
methodologically sound interconnector among disciplines and approaches.
For this, it is of utmost importance that Design curricula natively host such trans-disciplinary
approaches, not only combining disciplines as it is common practice in multi-disciplinariety, but
traversing them, generating not only contaminations, but also methodological boundary shifts.
The same state of necessity can be detected also for the topics of openness, transparency and
access. As seen in the previous sections of the article, most of the times power asymmetries manifest
themselves through lack of openness, transparency and access.
Interoperability, data openness and accessibility, usage of open licensing schemes, use of open
formats, open access to APIs: these are all types of practices that enable to confront with these
problems.
These topics should be standard part of any form of design education, highlighting not only the fact
that they enable the emergence of the ethical approaches necessary to resolve the issues described
in the article, but, also, represent potential competitive advantages for any organization, as well as
the opportunity to create meaningful actions.
The necessity of openness, transparency and access pave the way to another necessary axis for
innovation in Design Education, represented by the necessary evolution in which Design needs to
confront with Public, Private and Intimate Spheres.
As seen in the previous sections, it is now practically impossible to determine the boundaries of
these spheres. Content harvesting, sensors, analytics, and algorithms: these processes know no
boundaries. Data and information that appears to be private or even intimate is captured,
intercepted, inferred, diverted, producing results for marketing, advertising, or even for surveillance
S3941
Downloaded by [185.158.104.234] at 10:07 09 September 2017
SALVATORE IACONESI
8
and control. In designing these ecosystems to confront with these issues it is necessary to make
every possible effort to clearly and transparently define the boundaries of public, private and
intimate spaces, as well as the rights and freedoms which are granted within each of them. This is a
complex process, which involves the aforementioned trans-disciplinary approaches as well as
considerations that regard current business models, legislations, human rights, and (often national
and international) security. There is no simple way to confront with this type of problem. Rather, it is
a problem to be dealt with through complex approaches, combining not only different disciplines and
practices, but also society as a whole. Here again lies the potential role for design, which can
rediscover its humanistic and social elements and act as an interconnector between multiple types of
agencies. This is also an evolutionary opportunity for design education practices, in which this
modality can be implemented directly into the learning process, by opening it up to the city, the
territory and its inhabitants.
Which brings on the next relevant pattern: the one of participation, inclusion and social engagement.
Opening up data and processes, using open licenses and formats all are necessary items, but not
sufficient. If these actions do not match cultural, social, philosophical ones, they remain ineffective in
society. Open Data, as of now, remains a tool for the few, for those researchers, engineers and
designers who mediate it for others. For these types of action to become relevant for society design
processes must include the patterns of active participation, inclusion and social engagement. This
notion must be built into design processes and education, and all possible actions must be
performed to inject these ideas into the strategies of those businesses, organizations and, in general,
clients who commission the designs.
All leads to the concluding argument of this article, which points out the necessity for design to
embrace all possible strategies and actions to promote human dignity, freedom and joy, avoiding
atomization and loneliness which have become typical of the years we live in.
The risk society (Beck, 1992) has brought on
“[...] a mad, Kafkaesque infrastructure of assessments, monitoring, measuring,
surveillance and audits, centrally directed and rigidly planned, whose purpose is to
reward the winners and punish the losers. It destroys autonomy, enterprise,
innovation and loyalty, and breeds frustration, envy and fear. Through a
magnificent paradox, it has led to the revival of a grand old Soviet tradition known
in Russian as tufta. It means falsification of statistics to meet the diktats of
unaccountable power.” (Monbiot, 2014)
All this is fundamental to current models that insist on comparison, evaluation and quantification.
Design practice and education can, instead, have a positive role in this, acting as a complex, inclusive
and critical interconnector, promoting human dignity, joy and freedom.
References
Behar, R. (2004) Never Heard Of Acxiom? Chances Are It's Heard Of You. Retrieved December 26,
2016, from
http://archive.fortune.com/magazines/fortune/fortune_archive/2004/02/23/362182/index.htm
Beck, U. (1992) Risk Society, Towards a New Modernity. London: Sage Publications.
Blank, R. (2001). Biology and Political Science. Psychology Press.
Blanke, T., Greenway, G., Cote, M., & Pybus, J. (2015). Mining mobile youth cultures. In Proceedings -
2014 IEEE International Conference on Big Data, IEEE Big Data 2014.
S3942
Downloaded by [185.158.104.234] at 10:07 09 September 2017
Interface and Data Biopolitics in the Age of Hyperconnectivity
Booth, R. (2014) Facebook reveals news feed experiment to control emotions. The Guardian.
Retrieved December 26, 2016 from
https://www.theguardian.com/technology/2014/jun/29/facebook-users-emotions-news-feeds
boyd, d., Crawford, K. (2012) Critical questions for big data: Provocations for a cultural, technological,
and scholarly phenomenon. Information, Communication & Society, 5(15).
Bozdag, E. (2013) Bias in algorithmic filtering and personalization. Ethics and Information Technology
15(3), pp 209-227.
Bozdag, E., van den Hoven, J. (2015) Breaking the filter bubble: democracy and design. Springer.
Retrieved December 26, 2016 from http://link.springer.com/article/10.1007/s10676-015-9380-y
Bratton, B. H, Jeremijenko, N. (2008) Is Information Visualization Bad for You? Situated Technologies
Pamphlets 3: Suspicious Images, Latent Interfaces. New York: The Architectural League of New
York.
Davenport, T. H., Beck, J. C. (2013) The Attention Economy: Understanding the New Currency of
Business. Cambridge: Harvard Business Press.
Ford, E. (2012) What's in Your Filter Bubble? Or, How Has the Internet Censored You Today?
Retrieved December 26, 2016 from
http://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=1078&context=ulib_fac
Foucault, M. (1997) Society Must Be Defended: Lectures at the Collège de France, 1975-1976. New
York: St. Martin's Press.
Hardt, M, Negri, A. (2005) Multitude: War and Democracy in the Age of Empire. Hamish Hamilton.
Hill, K. (2014) 10 Other Facebook Experiments On Users, Rated On A Highly-Scientific WTF Scale.
Forbes Magazine. Retrieved December 26, 2016 from
http://www.forbes.com/sites/kashmirhill/2014/07/10/facebook-experiments-on-users
Hughes, J. (2004). Citizen Cyborg: Why Democratic Societies Must Respond to the Redesigned Human
of the Future. Westview Press.
Kramer, A. D. I., Guillory, J. E, Hancock, J. T. (2014) Experimental evidence of massive-scale emotional
contagion through social networks. PNAS 111(24).
Lafrance, A. (2014) Why Can't Americans Find Out What Big Data Knows About Them? The Atlantic.
Retrieved December 26, 2016 from
http://www.theatlantic.com/technology/archive/2014/05/why-americans-cant-find-out-what-big-
data-knows-about-them/371758/
Lapavitsas, C. (2013) The Financialization of Life. Retrieved December 26, 2016 from
https://www.youtube.com/watch?v=QsXmi58N3CA
Lemke, T. (2011) Biopolitics: An Advanced Introduction. New York: NYU Press.
Lessig, L. (2006) Code. New York: Basic Books.
Madrigal, A. C. (2012) Bruce Sterling on Why It Stopped Making Sense to Talk About 'The Internet' in
2012. The Atlantic. Retrieved December 26, 2016 from
http://www.theatlantic.com/technology/archive/2012/12/bruce-sterling-on-why-it-stopped-
making-sense-to-talk-about-the-internet-in-2012/266674/
Menkveld, A. J., Yueshen, B. Z. (2013) Anatomy of the Flash Crash. Retrieved December 26, 2016
from http://vu.nl/nl/Images/SSRN-id2243520_tcm289-336546.pdf
Monbiot,G. (2014) Sick of this market-driven world? You should be. The Guardian. Retrieved
December 26, 2016 from
https://www.theguardian.com/commentisfree/2014/aug/05/neoliberalism-mental-health-rich-
poverty-economy
O'Reilly, C. A. III (1980) Individuals and Information Overload in Organizations: Is More Necessarily
Better? Academy of Management 4(23).
S3943
Downloaded by [185.158.104.234] at 10:07 09 September 2017
SALVATORE IACONESI
10
Pariser, E. (2011) Beware online "Filter Bubbles". Retrieved December 26, 2016 from
https://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles
Pasquinelli, M. (2008) Animal Spirits, A Bestiary of the Commons. Rotterdam: Nai Publishers.
Rushe, D. (2014) Facebook sorry – almost – for secret psychological experiment on users. The
Guardian. Retrieved December 26, 2016 from
https://www.theguardian.com/technology/2014/oct/02/facebook-sorry-secret-psychological-
experiment-users
Singer, N. (2012) Mapping, and Sharing, the Consumer Genome. New York Times. Retrieved
December 26, 2016, from http://www.nytimes.com/2012/06/17/technology/acxiom-the-quiet-
giant-of-consumer-database-marketing.html
Teng, V. (2013) Hymn of Acxiom. Retrieved December 26, 2016, from
https://www.youtube.com/watch?v=0mvrKfcOnDg
The Private NSA: See What Acxiom Knows About You (2013). Retrieved December 26, 2016, from
http://www.tomsguide.com/us/how-to-axicom,review-1894.html
Tufekci, Z. (2015) Algorithmic harms beyond Facebook and Google: Emergent Challenges of
Computational Agency. Colorado Technology Law Journal. Retrieved December 26, 2016 from
http://ctlj.colorado.edu/wp-content/uploads/2015/08/Tufekci-final.pdf
Väliaho, P. (2014) Biopolitical Screens: Image, Power, and the Neoliberal Brain. Cambridge: MIT Press.
Verhaeghe, P. (2014) What About Me?: the struggle for identity in a market-based society. London:
Scribe Publications.
Weber, R. H. (2010) Internet of Things – New security and privacy challenges. Computer Law &
Security Review 1(26).
Wellman, B. (2001) Physical Place and Cyberplace: The Rise of Personalized Networking. International
Journal of Urban and Regional Research 2(25).
White, G. (2016) Big Data and Ethics: Examining the Grey Areas of Big Data Analytics. Issues in
Information Systems 4(17).
Zittrain, J. (2014) Facebook Could Decide an Election Without Anyone Ever Finding Out. New
Republic. Retrieved December 26, 2016 from
https://newrepublic.com/article/117878/information-fiduciary-solution-facebook-digital-
gerrymandering
About the Authors:
Salvatore Iaconesi teaches Near Future Design at ISIA Design Florence. He is a robotic
engineer and a philosopher of science. He is TED Fellow, Eisenhower Fellow and Yale
World Fellow. He created the Art is Open Source international network, and founded
Human Ecosystems.
S3944
Downloaded by [185.158.104.234] at 10:07 09 September 2017
