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Identity in a Big Data World - IDENTITY-Talk in the Tower®
Mareike Ahrenson 13 March 2014
Transcript of Identity in a Big Data World - IDENTITY-Talk in the Tower®
is an interdisciplinary and international discussion focused on the
FUTURE OF IDENTITY:
the impact of technology, norms and values that influence identity, and the key issues of its regulation and control.
Obviously, that discussion needs to look at the new data power:
Why are we talking about Big Data activities
over the last decades?
How is Big Data
Big Data is about both
Why should about Big Data? What connection is there to
The mechanisms of Big Data are
Big Data is very much about
– the opinion others have of us and the basis of their interactions with us – might be affected by Big Data: Even if a data set is cleansed of directly identifying information such as names, ID or phone numbers, the data will still often
within a data set.
However, Big Data also provides the to solve important and to
through improved services and products. Let’s have a look where Big Data is being used:
is one of the key factors in the
through a population.
Scientists from the School of Computer Science, University of Birmingham, used the datasets provided by mobile operator Orange to
of a large number of individuals in Ivory Coast.
The scientists observed how epidemic spreading is influenced by people’s mobility and social ties.
Then, they simulated several epidemic scenarios and evaluated mechanisms to contain the epidemic spreading of diseases, based on the information about people’s mobility and social ties also gathered from the phone call data.
How can the disease be
You see: This Big Data based research helps to
for a whole nation.
is a big buzzword nowadays leading to big questions:
And where do we encounter
Another research project in Ivory Coast by the University of California/San Diego, La Jolla looked at the
It can provide insights about the
structure and geography of social ties.
It can help authorities to understand how
the different communities of a country are structured
how they interact
with each other.
Using data provided by Orange, they mapped connections among 1216 cell phone towers for five months. The volume of calls passed from one tower to the next revealed
“communities” of antennas
based on the strengths of the connections, a geographical map of who talks with whom throughout the country.
They compared this to a second
map of which languages
are spoken by the majority of people in each region. With 60 different languages spoken by local majorities, the comparison was computationally intensive.
Telecommunications data can provide
valuable information about language communities
that would otherwise be difficult to obtain. This methodology could prove very useful internationally when trying
to gain information about populations
to – for example - target aid or information in languages that will be understood.
Source: O. Bucicovschi, R. Douglass, D. A. Meyer, M. Ram, D. Rideout and D. Song, "Analyzing social divisions using cell phone data", UCSD preprint (2013); awarded Best Scientific Prize in the Data for Development (D4D) competition at NetMob 2013, MIT, Cambridge, MA (1-3 May 2013).
In the last decade there has been an impressive
The enabling technology is GPS: GPS receivers can
accurately place users outdoors
(with a precision of about 10m today and less than 1m in the next few years). By projecting this position onto digital maps, navigation systems can be built on top of the GPS-data.
growth of car-navigation systems.
The key Big Data issue is to
track a car’s position in real-time:
the car sends its GPS coordinates to a back-end service; this data-flow is merged and analyzed; the service sends back useful information to the car and services to the user (car).
I provide a web-based service with
in return, I receive, as a “reward”,
Traffic information on the planned route
A much more accurate time-to-destination prediction
Suggestion of re-routing to optimize the time-to-destination, according to the traffic conditions
Intersection support (run-time alert on potential hazards given by vehicle-to-vehicle interaction)
Energy-optimization for electric or hybrid vehicles (knowing in detail the movements of vehicles just ahead on its route, an electric/hybrid car can significantly optimize its energy usage)
Fully-automated driver (ultimate scenario: all the moving vehicles know the planned routes of other vehicles in advance; global traffic optimization becomes possible, with major benefits in terms of energy-savings, reduction of emissions, traffic-throughput, and increased safety)
Google navigation system with traffic information
Waze application & services (social network specializing in car navigation)
of a car/person/mobile device are tracked in detail,
stored and analyzed
. This is one of the
relating to a person.
How is our
in a Big Data world?
Big Data co-exists with the
They are not subject to special norms. Hence, so far, for policymakers does not deserve a different treatment compared to
The significant change is
in which such data protection needs to be ensured: Technological innovations, the nature of data and the specific features of certain processing highlight a new context.
Lack of transparency and awareness: data controllers/processors often act
about data processing and relevant implications. Smartphone apps, where users are not properly informed about the data processing purposes.
Lack of purpose: it is very common for personal data to be processed for purposes
provided to the individual- also due to the fact that Big Data might not be used to verify or falsify a specific idea but to find some as yet unknown relations.
Lack of meaningful consent: with Big Data it will also be
Music on demand platforms, where users’ personal data are also processed for marketing purposes without acquiring their express and prior consent.
Icons could create a common set of symbols for how websites use data.
Our three Big Data examples rely on data which are
already harvested and tracked by the service providers
, e.g. the mobile operator or the provider of bidirectional GPS systems. They
do not require the users to disclose more data than usual.
Big Data multiply the potential for
such as a quicker route home, or social benefits, such as disease control.
For Big Data to generate value for individuals and society, they must be
disclosed to third parties
(e.g. the health ministry) and usually
with other data.
It is not “I share a bit more, I risk a bit more”, but rather
“I share a bit more,
Data about connections and mobility can
improve the quality of life in developing countries
. But at the same time, a very granular analysis of population’s distribution and location is an extremely
e.g. in case of ethnic clashes.
In addition, looking at the
Do we want a situation where the
is anonymous but can be
used/tracked by the police
; and the police, using this piece of information, can physically
reach the vehicle and check
if the driver is driving properly or not?
Or take it a level further: The transmitted position/speed is
used/tracked by the police
; in case of improper driving behavior the fine can be issued by
simply analyzing the recorded data.
Law enforcement and driver-behavior monitoring using simple data-analysis could
save enormous amounts of money
, and guarantee much more accurate monitoring. However, from the individual (driver) point of view, this is a
that could strongly discourage (unless mandatory) sending his/her data.
Is there the danger of ending up in
a surveillance state
in large datasets could drive various forms of
sorting, ranking, and profiling
. Such uses of Big Data raise concerns about
unjustified or undesirable discrimination
based on false data or erroneous and invasive inferences. Example: Denying a specific individual credit because of the poor financial health of his or her neighbors.
Such analyses may even provide a path by which to
not been disclosed
guess at characteristics
cannot be observed
, and to
avoid the need to obtain that information
from others, unsettling deep-seated intuitions about
and some of the foundational assumptions of
Users may control what information feeds big data only if technology empowers them to do so, for instance a button on cell phones that I can push in order not to be tracked.
as a complement
to (substitute for?) Big Data regulation
Users’ control of
Big Data – do not track me button - creates dilemmas:
Shall I trust that button? What about data that companies have to collect for legal/operating reasons, and from which, therefore, no technological opt-out is possible, but that could still feed big data platforms?
How can we trade-off the user’s right to control data via technological means with the public good that Big Data are supposed to provide? Should we be entitled to “switch off” a tracking technology whose purpose is disease control?
One possible approach:
Privacy Enhancing Technology (PET) / Privacy by Design (PbD) including all kinds of technical and organizational measures to ensure that individuals’ data protection rights are respected.
PET examples: anonymous browsing; self-deletion of personal data after use, or after a certain time period.
a technology collects only the data necessary to the service – it knows that you are above 18 but not that you are 24 years old.
Other efforts include industry self-regulation, for instance the establishment of privacy enhancing principles, such as the GSMA
Privacy Design Guidelines for Mobile Application Development
“apps and services should be developed in ways that respect and protect the privacy of users and their personal information”.
To be effective, they must be included in Big Data platforms from the start so that they may increase the effectiveness of users’ legal rights.
But: What business models are we shutting down by seriously (i.e. compliance-proof) mandating the use of privacy enhancing technologies and privacy by design organizational arrangements?
Effectiveness, whereas legal means are difficult to enforce; trust and third-party (public) control is still necessary
not create rights
heading from here?
In yesterday’s world, it appeared safe to upload personal data: seemed to be able to
This has now changed:
detect certain patterns in behavior, recognize faces on pictures, predict decisions, and classify individuals with respect to social and economic categories.
There are at least four technical drivers towards even Bigger Data:
such as the physical world to the virtual world by measuring all kinds of data such as location, orientation, temperature, brightness, sound; they record images and voice data, they measure vital functions of the human body, they detect magnetic fields and infrared radiation and so on. All these recorded data are available as digital information.
Sensors, cell phones and tablets, photo and video devices, household appliances, are connected to the web and to each other and deliver local data to the world often referred to as the Internet of Things. This kind of multiplication and concentration is one of the origins of future big data volumes.
Millions and billions of users contribute to Web 2.0 sites and social networks, in particular audio and video content. This trend will continue, leading to ever growing volumes of data.
becomes cheaper and cheaper as memory and storage prices drop. At a certain point, it becomes cheaper to simply keep data than to select and discard. When looking at your personal stock of digital photographs this is a very common experience.
Do we need to critically discuss the impact of Big Data on our identity in every context?
Big Data used in the context of
the wear and tear of industrial
But the following questions should be
addressed by future research
What are the
for companies, public institutions and individuals so that Big Data is
? What DO’s and DON’T’s do we need and how can they be implemented?
strict data minimization
be implemented - meaning that data may only be processed to the extent necessary for a given defined purpose? Leading to the question: How can we preserve the
How do we deal with the fact that there are still many
and thus not contributing to Big Data?
Without a doubt, Big Data has an impact on identity if you focus on privacy and reputation issues. Society needs to decide:
For more information on Big Data projects in the developing world, see for “Data for Development”
This is a publication by the third Task Force of the IDENTITY – Talk in the Tower® initiative
And first of all:
A key difference exists:
I may risk a lot more”.
As more activities and a greater portion of our activities are
subject to observation, such records may begin to
that say more about individuals than they realize.
What has changed
The term Big Data derives from the
to verify or to find as yet relations among specific data for
processing of huge amounts of data
improve health conditions
of mobile phone activity between antennas.
The two maps correlate closely. It’s no surprise given the likelihood of talking most often with those who share your language, even beyond neighborhood relations.
my run-time position;
New issues arise
without correctly informing users
different from those established within the information notice
more difficult for controllers to adequately inform users by using simple consent
applied to all interactions
that occur in the digital domain, and many in the non-digital domain.
capturing the characteristics
of our identity
– our self from the perspective of others.
individual to be clearly identified
simplify people’s lives
challenging law enforcement
situations come up.
Where are we
handle such Big Data.
New analysis tools and faster computers
USER PROVIDED CONTENT:
STORAGE OF DATA
In future, new technologies such as will go even further. will learn to
of information. This will – as always – have its positives and , as we have shown.
Where do we draw the line?
spread of diseases
the mobility and call pattern
, Doctoral student in the Department of Media, Culture, and Communication at New York University
, Research Fellow F.R.S – FNRS; PhD Student Louvain School of Engineering
r, Director Technology Management, Giesecke & Devrient
, Partner, Identity Alliance
, Senior Researcher, Deutsche Telekom Chair of Mobile Business & Multilateral Security of the Johann Wolfgang Goethe University Frankfurt/Main
, Researcher at the CEPS - Center for European Policy Studies
Sergio M. Savaresi
, Full Professor in Automatic Control at Politecnico di Milano
, Group Vice President R&D, Division Banknote, Giesecke & Devrient
, Independent data protection centre, Schleswig-Holstein (ULD)
The people involved in the production
of this prezi may have acted in their personal capacity. Thus, this work does not necessarily reflect the opinion of the organization
For more information, contact
Giesecke & Devrient GmbH
Fabian Bahr, Head of Berlin Office
Phone: +49 (0)30 2009 5480
Mareike Ahrens, Project Manager
Phone: +49 (0)30 2009 54812
In our cars.
Their Big Data analysis shows that
restricting mobility does not delay the spreading
of the disease because the disease is not spread by human-to-human transmission. Instead, people are and about the disease
with the members of their social group so that they can get information about prevention techniques, hygiene practices, nearby vaccination campaigns etc.
by one-to-one phone conversations
Source: Exploiting Cellular Data for Disease Containment and Information Campaigns Strategies in Country-Wide Epidemics. Antonio Lima, Manlio De Domenico, Veljko Pejovic, Mirco Musolesi. Third International Conference on the Analysis of Mobile Phone Datasets (NETMOB'13). Boston, USA. May 2013.
unknown and unexpected
most sensitive pieces of
current European data protection legal framework.