Wrt301 thesis

ETHICAL DILEMMA OF DATA MINING
THE ETHICAL DILEMMA OF DATA MINING
TO TARGET MARKET
An Honors Business Thesis
By
Pamela Hernandez
Dr. Shyam Sharma
WRT 301: Writing in the Discipline
Stony Brook University
Stony Brook, NY

ETHICAL DILEMMA OF DATA MINING 2
ABSTRACT
Data mining used to target individuals for promotional means requires constant collection of
information which is usually accomplished without consent from consumers. This incites issues
that are within legal boundaries but fails to recognize serious ethical issues that must be
addressed. This thesis explores the ethical tensions and concerns that arise when companies
collect consumer information, how it is managed, and whether actions are taken in the best
interest of the consumer or to benefit companies at consumers’ expense. It does so by
questioning the public’s focus on surveillance from the government and comparing how business
uses it. The ethical issues are highlighted to demonstrate that attention should be focused on
business also. It begins with an example of a student’s experience with targeted marketing and
her reaction to it. Later, it goes on to introduce the topic and general issues, discuss ethical
tensions from two cases, and propose possible methods of addressing the difficult issues of data
mining to target market. It concludes by arguing that businesses must be held accountable for
consumers’ personal information and how they collect data to assure they are protecting
individuals and not taking advantage of them. The public needs to be more aware of businesses
and their practices to be able speak against them.

Table of Contents
ABSTRACT......................................................................................................................................2
CHAPTER 1: INTRODUCTION .....................................................................................................4
CHAPTER 2: INTRODUCTION TO THE MAIN ISSUES.............................................................8
Focus on Government Use.............................................................................................................8
What about Business?...................................................................................................................9
Uses and Abuses of Data Mining: Ethical Implications ...............................................................10
Profiling ......................................................................................................................................10
Discrimination and Equality .......................................................................................................11
Violation of Privacy ....................................................................................................................12
Technology’s Role.......................................................................................................................13
Benefit: Consumer and Business.................................................................................................14
CHAPTER 3: SPECIFIC CASES...................................................................................................17
Case 1: Involvement ofBusiness and Government: The Case of Verizon....................................17
Ethical vs. Legal..........................................................................................................................17
Privacy and Transparency as a Main Concern............................................................................19
Domestic Surveillance .................................................................................................................20
Social Implications......................................................................................................................21
Case 2: Business Involvement: The Case of Facebook.................................................................23
Selling Information.....................................................................................................................24
Navigation Freedom....................................................................................................................25
CHAPTER 4: SOLUTIONS...........................................................................................................27
Violation of Privacy ....................................................................................................................27
Lack of Transparency.................................................................................................................28
Abuse of Information..................................................................................................................29
CONCLUSION...............................................................................................................................31
REFERENCES...............................................................................................................................34

CHAPTER 1: INTRODUCTION
Imagine a college student is conducting research on the use of data mining. As she sits
down to draft her research paper, she notices boots on the side of her screen. She becomes
alarmed when she notices that the particular brand of boots correspond to the online website she
visited a few weeks ago. The student assumes it is probably a coincidence, but then becomes
aware that she had been window shopping and clicked to view those specific boots for a closer
observation. She has become a victim of the cyber realm and its devious ways of displaying what
it assumes is of interest to her. It relates to what she is researching at the moment: that data
mining intrudes and violates privacy for marketing means. She's trying to take a neutral position
on the subject and produce formal, scholarly work, but she cannot stop thinking about how those
boots, from a few weeks ago, are right there. She cannot ignore how she feels or the fact that
some way, somehow, someone or something had to have been documenting her every move as
she obliviously shopped for boots.
This is a serious issue of privacy. The news indicates that data mining and surveillance is
the government's form of invasion but, incidentally, the above is a description of what happened
as I sat to start writing this chapter. Right before my eyes, there was a prime example that could
not be ignored.
Data mining is a topic that tends to evoke many emotions. These emotions can range
from gratefulness to anger or excitement to uneasiness. It tends to be uncommon to recognize
these actions when they are the result of targeted marketing. Instead, it may be considered
“creepy” or experienced so frequently that it is disregarded altogether. But when put in a
different context, when attached to a societal category such as the government, the public reacts

based on feelings of “being watched” and not having any privacy. Situations like the above raise
a number of critical questions about privacy. What makes it different from government
surveillance? Why does it seem that when an advertisement is present on the side of a screen,
individuals pay minimal attention to it but when it is discovered that the government is keeping
track of phone conversations, everyone is alarmed?
This thesis attempts to convince readers that although data mining assists in providing in
depth information about consumers and their buying habits and preferences, it is an issue that
should be taken seriously even when the government is not involved. The evidence before me
shows that my searches were being paid close attention. It is almost impossible to not wonder
how much more businesses know and can find out. So why does the public not seem to mind that
businesses are watching them too? By clearly displaying the ethical implications of targeted
marketing, consumers will be able to understand the complexity of the issues.
First, this thesis will discuss the theoretical issues and then demonstrate them in two
particular cases. It will explore the complexity of data mining and its use in targeted marketing
by emphasizing the current focus on the government’s use. After, the second case will
demonstrate how business and government use of data mining create similar issues.
In the second chapter, I will introduce the current focus and highlight the main issues of
abuse, profiling, discrimination, equality, the violation of privacy, and technology. By providing
examples of a Midwest grocery store and its discovery of the behavioral patterns of fathers, one
will begin to understand how businesses gather information from buyers and strategize to use it
at their expense. By briefly explaining the main issues, more specific ethical implications will
arise from using data mining to target market.

To better understand data mining, it is necessary to explain how consumers and
companies benefit from its use. By portraying it in a way that has pros and cons, one may begin
to think of the core issues and why it tends to be viewed negatively, thus allowing for possible
improvement by addressing those issues.
Chapter three will display two cases that demonstrate specific examples of when two
businesses used data mining and will hone into specific ethical controversies. The first case,
Verizon, will demonstrate a gray area with respect to the subjects involved. The collaboration
between Verizon, one of the top communication companies, and the government will allow the
reader to not only understand that the combined effort was necessary for the government to
acquire requested information but also the extent to which Verizon contributed. This case will
showcase a time when the public would typically blame the government, but, by stressing
Verizon's involvement, its role will be recognized. This case will bring forth issues of privacy,
lack of transparency, and increased surveillance. The Verizon case will also allow for a brief
introduction of technology and how it is the core of functionality and a rise of social
implications. Case two, Facebook, will demonstrate more issues by Facebook’s use of data
mining. By showcasing an example that has no government involvement in the debate, this thesis
will illustrate that an attention to business action is of concern also. The Facebook case will
focus on two issues: the selling/transmitting of public and private information and whether one
can navigate “freely” as they are taught to believe.
The fourth chapter will propose solutions to the issues believed to be most prevalent:
violation of privacy, lack of transparency, and abuse of collected information. These solutions
will attempt to solve the issues for both the consumer and business. It seems that getting to a
point that allows data mining to provide for a company while also considering consumers may

allow for a better perception of it. What makes such an issue so complex is that the “ideal”
solutions may take away from its intended purpose or may allow for a dysfunctional and
manipulated system that does not produce useful results.

CHAPTER 2: INTRODUCTION TO THE MAIN ISSUES
Data mining tends to be associated with the government and its appliance of it. It seems
the public does not associate data mining with business when, in reality, it is far more frequently
used in this field. The beginning of this chapter will introduce the current focus on government
surveillance in relation to business. To appropriately demonstrate such a focus, it is necessary to
compare government involvement in data mining to that of business in order to highlight the
ethical implications. When it comes to this topic, it is important to note, though both uses are
meant to meet different goals, their practices are similar. This chapter will demonstrate that while
the use of data mining by the government and business differ in function and purpose, many of
the same ethical implications are pertinent.
Focus on Government Use
In general, data mining “is the process of analyzing data from different perspectives and
summarizing it into useful information” (Anderson & Frand, n.d., p. 1). When it comes to this
practice, there seems to be a focus on governmental issues and not those of business. After the
attacks on 9/11, there has been an increase in security attention to keep the country safe. One
method of doing so is data mining. The government has the capability to access our personal
information such as emails, text messages, social media accounts, and even the web cameras on
laptops. Edward Snowden’s revelation of NSA practices and their abuse of power is one of the
biggest leaks in United States history and has created debates of its own that cause Americans to
fear what possible information could be gathered on them. In an interview, Snowden revealed
that the NSA has access to the “vast majority of human communications” which is
“automatically ingested without targeting” (MacAskill, 2013, para. 1). This infrastructure to
combat and identify threats in advance, in Snowden’s opinion, is “disturbing” and “abusive”.

The sense of uneasiness that stems from the “horrifying” capabilities of the government that
caused the public to feel unsafe was enough for Snowden to expose the controversies and ethical
implications created by this practice (para. 10). To better understand its inclusion in business, it
must be understood that the limit of the use of data mining is not simply within the government.
What about Business?
The majority of data mining attention is focused on the government’s practice to keep the
country safe while businesses use similar tactics for less crucial processes such as promoting.
They use software to analyze patterns or relationships to provide information on consumers and
directly market to them. This is not a matter of social security; instead, it is one of the markets.
It is important to study businesses that use data mining as well as the
government. Businesses keep track of purchase history to utilize for promotional efforts. In
theory, this is usually an effective idea, but the data gathered is used to create assumptions that
may or may not represent the person it is linked to. For example, what is communicated by a text
message or email may represent an individual better than what they buy because they are
consciously thinking of the message they are trying to deliver. A common defense of targeted
marketing is that the data is anonymous, but with enough information about someone,
technology can analyze this data to identify an individual by name, address, age, picture, and
other demographics that weaken that argument (Narayanan & Shmatkikov, 2009, p. 173). If this
is the case, why is the attention to security with respect to business neglected? The practices are
similar and though I do not wish to disclose my position in support nor opposition of the
government’s practices, I do believe business must be paid close attention to as its goals are to
target individuals not for the security of a country, but for profit gain and progression means.

Uses and Abuses of Data Mining: Ethical Implications
To understand the ethical implications of data mining for targeted marketing, one must
first be aware of the issues of abuse, profiling, discrimination and equality, and violation of
privacy that arise from this practice. The following example is one that demonstrates abuse. One
Midwest grocery chain used Oracle software to identify a relationship between fathers that
bought diapers on Thursdays and Saturdays. The grocery chain recognized that those shoppers
tended to also buy beer during the visit. The information could be used to move the beer and
diaper displays on these days closer to each other which would be an appropriate action since a
relationship was discovered. In the text, it was suggested the items be sold at full price on these
days (Anderson and Frand, n.p., p. 1).
The issue that arises with the second approach is how buying behavior can be used to
benefit the grocery chain and not the customers that provided the information. Without the
actions of the fathers that provided these results, the grocery chain would not know there was a
relationship between beer and diapers on specific days. Instead of using the information to
simply increase the effectiveness of the store by placing both items closer to each other and
making it easier for fathers when they shop, the suggestion was to make both products less
susceptible to price demotion on those specific days. Such an approach provides a benefit for the
store and none for the customer. When looked at from a critical perspective, it is an opportunity
at their expense.
Profiling
I will discuss profiling and its participation in this practice as a method to dehumanize
and strip one of everything except their interests and purchases. Profiling is a result of the vast
amount of data that is collected. To simplify matters, companies place consumers into categories

in the databases with others who have similar buying habits. The information collected creates a
profile for individuals. These profiles may be utilized by a company to reveal the best time to roll
out a product, have a sale, determine a layout, and may gives clues to something that should be
introduced in the future.
The issue that arises from profiling is that behavioral buying habits represent buyers and
serve as their identification. This takes away from a consumer’s value as an individual. To claim
that one’s purchases determine who they are, lacks respect of their individuality and strips them
of their identity. This approach fails to recognize their purchases simply as behaviors and
converts consumers into subjects by viewing purchases as characteristics. Because consumers are
unaware, there is something worth exploring about this practice and the value it places on
individuals that make it possible.
Discrimination and Equality
Segmentation may restrict one from being able to access what they please. When
categorizing of this nature occurs, businesses tend to market to similar people in corresponding
segments. This exposes consumers to what companies think they would be interested in based on
previous purchases or views of a product, website, or search. There tends to be a lack of
understanding that at one point or another in their lives, interests change.
To address the issue of discrimination and equality, there should be a limit to restricted
information available to individuals based on prior history. In a TEDTalk, Eli Pariser (2011)
demonstrated how a simple Google search for one individual produces different results for
another because of “algorithmic gate keeping” (Pariser, 2011). A search on information such as
specific news in another country (as demonstrated in the video) show different results for
different people. This is a result of data mining that brings light to discrimination of information.

So, does this mean that we must stick to what we are comfortable with and not seek new
opportunities? Questions like these allow one to process an understanding that consumers are not
predictable and cannot be treated in such a way that allows for limited spontaneity, individuality,
and growth. Duhigg (2012) mentions consumers go through stages in life that change their
buying behaviors whether it is the coming of a child, purchase of a new home, or starting a new
chapter in their lives (p. 1). Targeted marketing does not advertise items out of routine buying
habits which may lead to a loss of opportunity for some buyers.
Violation of Privacy
I will discuss the issues of the potential violation of privacy and charges of lack of
transparency from the perspectives of different stakeholders. The issue that arises with privacy is
the taking of information to form conclusions which will be demonstrated by two examples.
Target used data mining to identify pregnant customers. When approached by two members of
Target’s marketing team about the possibility of finding out if a customer was pregnant, Andrew
Pole, a statistician, began a project to find out (Duhigg, 2012, p.1). He identifies pregnancy as a
time "when old routines fall apart and buying habits are suddenly in flux” (p. 1). Once specific
behaviors were monitored, Target was able to find a pattern that allowed them to send
promotional deals used during pregnancy and after child birth. When asked how women would
react to this, Pole responded:
If we send someone a catalog and say, ‘Congratulations on your first child!’ and they’ve
never told us they’re pregnant, that’s going to make some people uncomfortable…We are
very conservative about compliance with all privacy laws. But even if you’re following
the law, you can do things where people get queasy (Duhigg, p. 11).

He makes a clear statement that allows one to comprehend that legality is not the only concern.
Instead, there is a matter of ethics involved.
The second example will illustrate how the involvement of data mining in the personal
lives of individuals violates their privacy at a deeper level. A year after Pole’s creation of his
pregnancy prediction model, the father of a high school student walked into a Target store
outraged that his daughter was receiving coupons for baby clothes and cribs (Duhigg, 2012, p.
11). He had the coupons as proof, but the manager of the store did not understand what was
really happening. A few weeks after, the father apologized for the confrontation and let the store
manager know that his daughter was pregnant. Upon reflection, one may notice that the father
found out about something as personal as pregnancy not from a doctor or his daughter, but from
Target. This is where the line is drawn. “The mining of personal information has raised privacy
concerns” such as the one previously illustrated (“Think”, 2004, p. 3). There were good
intentions for this project but they failed to think of the possible consequences.
Technology’s Role
Technology’s rapidly advancing capabilities further complicate the ethical implications
within the government and the market. The issue is the extent to which it is growing and being
utilized. Technology allows for domestic surveillance to occur with ease, simplicity, and secrecy.
As technological software advances, these systems can gather information and interpret trends.
Computers are heavily relied on to sort the data accordingly and make use of it. These are tasks
humans cannot accomplish in a manner as efficient as these systems. As technology progresses,
acts like that of the court order previously discussed will be more consistent and present. The
question then becomes, when will the line be drawn?

Technology plays a similar role in both governmental and business uses of data
mining. The use of cyberspace allows for increased connectivity and the ability to perform tasks
at an extent that was not available in the past. Web technology makes it easier to link records by
the click streams left behind. Click streams allow service providers like Double Click to develop
a record of web activity that represents what interests individuals (Gandy, 2012, p. 1). This
information is used for various reasons, one being targeted marketing. As patterns are being
discovered, individuals are being monitored on a set of constraints such as high and low value
customers or location that allows for segmentation. The government uses constraints also. An
example of one is race as an element in profiles used by State police to identify possible suspects
in a crime.
Benefit: Consumer and Business
To fully understand data mining, one must be willing to give attention to both sides of the
argument, understand the ultimate goal of data mining, and how it benefits the company and
consumer. It is popular in the business sector because the speed of computer processing power
increases accuracy of analysis at a low price (Anderson & Frand, n.d., p. 1). For companies with
a strong consumer focus, data mining allows for simplification of determining what consumers
want. In order to accurately do so, they must have ample information on purchasing habits. Aside
from monitoring individuals’ behavior, companies target to a group of related people, such as
friends, because they tend to have similar interests (Bagherjeiran & Parekh, 2008). Companies
will target market one person within a group with the hope that the information is passed on to
their friends. This can be useful to consumers as it blurs the line of the limited information
available to specific persons because it is not always connected to past interests. Data mining
can also benefit a customer who does not have a clear idea of a specific purchase in mind. If an

individual is seeking to purchase gloves on the internet, they will begin to see suggestions on the
side of the website for other gloves, thus making the search simpler and possibly less time
consuming. If they feel that specific website does not have gloves they desire, they will also
receive advertisements for gloves on other websites which gives them the option to make the
best purchase according to their preferences.
Businesses may be able to understand what customers may want, and therefore, can
create a desirable image catered to those wants and needs. This is important because it helps
build a brand image and may lead to consumer loyalty, one of the strongest ties a consumer can
have to a company (Peterson, 1997, p. 171-172). A method of doing so would be observing what
buyers in that particular store frequently purchase. The store may choose to offer more of these
products when they realize demand is high or could strategically plan sales around them. This
may help a company create a long lasting relationship and increase sales.
When it comes to data mining, a company is like a business student who needs to
network, have a good resume, and continue to learn and develop skills for success. Networking
represents meeting the right people who would like to buy their product. These are typically
those with an interest in it or something related to it. Resumes represent providing consumers
with what they want and tailoring it to them as one would for a specific job description. Lastly,
developing themselves represents keeping up with trends that, in this case, are utilizing the
internet or in-store checking out scanners for the information provided that also cut advertising
and research costs. Businesses essentially use their sources to be able to accomplish this. In their
opinion, they gain nothing by trying to “spy”; instead, this information is used strictly for
business. Still, this does not eliminate the fact that the amount of information collected is

inappropriate which often make customers feel “watched”. It is necessary to address its intended
purpose to better understand this practice.
With the following approach and perspective, there appears to be a win/win situation. As
companies cater to specific consumer needs, consumers are able to come across products of
interest which also saves time for them to acquire the items. It seems the issues with data mining
do not entirely result from the storage of too much information, but the way we come across it
and how specific advertisements tend to be. If an individual were to search for a pair of boots on
Stevemadden.com and there was a suggestions box on the side, with similar boots, the assistance
would be appreciated as it would introduce them to another option. On the other hand, if they
were already purchased and advertisements continued to appear on the side of their Facebook
page, there is a high chance they may be upset, feel uncomfortable, and even annoyed. These are
feelings that produce negative emotions toward data mining.
In general, data mining used to target market creates various issues that must be further
explored to fully comprehend that the government is not the only party that utilizes this method.
To continue to demonstrate involvement and generate more issues, I will expand my argument
by providing two specific cases that demonstrate the complexity of this practice.

CHAPTER 3: SPECIFIC CASES
I will discuss the contribution of data mining to business with two cases that illustrate
how both business and the government can abuse the privacy of individuals and act irresponsibly
when keeping information safe. In this chapter, I will build on the arguments from chapter two
through examples that demonstrate the various issues that arise from data mining to target
market.
Case 1: Involvement of Business and Government: The Case of Verizon
As previously mentioned, there has been a higher focus on actions taken by the
government and a failed attempt to do so with those of business. I will consider the controversy
from a different perspective, a perspective that makes it difficult to distinguish whether Verizon
is the main party involved or whether it is a combined effort of the company and the government.
It is necessary to illustrate such a case that will bring forth participation and how the business
equally contributed to the intervention of privacy, lack of transparency, and increased
surveillance of its customers.
Ethical vs. Legal
The Verizon case represents a situation when it seemed the government was taking action
without legal approval. After finding out that the government had been using a secret court order
to approve surveillance, no longer was the problem was that it was not committing a legal
mistake, instead, it was an ethical one with dishonesty in not being transparent. The actions were
legal but still unethical which shows how complicated the legal vs. ethical tension is. The
broader political environment allowed the government and Verizon to cross ethical boundaries
without violating existing law.

People tend to settle for the legal argument, but if it is proved legal and that is not the
only issue, the problem has yet to be solved. CNN reported that Verizon, one of the most well-
known communications providers had, by law, been ordered to provide the government with
“call detail records and Verizon Business Network Services” (Martinez, 2013). Requested by the
FBI, this top-secret plan was intended to gather local and foreign telephone calls and telephone
metadata, fax numbers, and other means of communication. It was supported by political
members such as Senator Dianne Feinstein and Senator Saxby Chambliss because it was legal
since it was authorized under the Patriot Act under Section 215 (Martinez, 2013, para. 27).
Because it had been done before, Feinstein claimed that it was a renewal that allowed the United
States “to understand that a plot [had] been hatched and to get them before they get to us”
(Martinez, 2013, para. 27). Since it was proved to be legal, the issue now becomes an ethical
one.
As mentioned earlier, legality may be enough to “prove” that something can be done but,
it is not the only criteria necessary to measure this. "Legal" simply means that it complies with
the law but how many times in history have laws been legal yet, at the same time,
righteously unacceptable? Chambliss defends the order as effective because it has been used in
the past to gather information that has assisted in catching “bad guys” and only bad guys
(Martinez, 2013, para. 32). The senator's defense implies that because something works
sometimes it will always work; therefore, it is free of error. It is a naive and poorly developed
approach. If it is so effective, why is it that this court order has led to controversy and negative
opinions about the government's actions? The general public seems to believe that if something
is legal there is not a problem. The question is if it is ethical. Ethics is a matter of morals and

though legality may assist in determining what may be ethical, one must approach such a
situation by looking at it through a moral scope and deciding whether it is socially acceptable.
Privacy and Transparency as a Main Concern
The issues of privacy and transparency arise from a legal and ethical perspective. For the
sake of the main argument of this essay, I will not go into legal and illegal issues but rather into
the ethical ones. Mark Rumold, staff attorney at the Electronic Frontier Foundation, believed
there was nothing legal about this government request of phone records and that the main
problem was privacy and transparency (Martinez, 2013, para. 20). In a tweet, Former Vice
President Al Gore, expressed his opinion on the importance of privacy by commenting, “Is it just
me, or is a secret blanket surveillance obscenely outrageous?” (Martinez, 2013, para. 22).
Though the court order does not wire tap into the content of communication, it does document
the caller, receiver, time, location, and duration of the call to gather information about patterns
and call activity relating to terrorism. It then stores this data into a database to be analyzed.
Privacy advocates criticize the law as an abuse of power on behalf of the FBI to “spy” on
Americans (Martinez, 2013, para. 5).
The issue is that data was collected from all individuals including those without any
connection to terrorism or danger to the country (GPO, 2001). The act allows for the collection
of data from all calls not only those of suspicion. Jonathan Turley, a law professor at George
Washington University, questioned, "At what point do citizens stand up and say this is the
tipping point? We're getting toward authoritarian power” (Martinez, 2013, para. 14). Another
ethical impact is that this section of the Patriot Act focuses on relationship/connection and not
content. Though content would create a larger issue when it comes to privacy, connection, in a

sense, is still as bad. Who is to say that a terrorist does not associate with individuals that have
no relation nor intention to cause terror? This order bases its results on assumptions that may put
innocent people at risk of being perceived as suspects. It does not base itself on facts, simply
inclinations.
The use of data mining poses the issue of transparency as well. The Obama
Administration obtained this court order in secrecy for phone records from Verizon (Martinez,
2013, para. 2).The main concern is that Section 215 of the Patriot Act that provides, “Access to
records and other items under the Foreign Intelligence Surveillance Act” was interpreted
wrongly to allow for the order to be implemented (GPO, 2001, Sec. 215). Aside from that, the
order was so top secret that the public would have never known if The Guardian had not
published an article providing the information. As “subjects” of the order, we should be informed
that information is being collected and what that information includes. Citizens have the right to
privacy and there is not a specific reason to target an entire population of Verizon users. Turley
points out, “‘the problem is, every administration, every politician will say we're getting
something from this....you can make that argument to remove all civil liberties”’ (para.
15). There was no intention to reveal this decision to the public and could not have been done so
without the consent of the director of the FBI (Martinez, 2013). If this was done in secrecy, what
else could be happening that we do not know about?
Domestic Surveillance
Concerns of domestic surveillance arise from privacy and transparency issues.
Understanding this perspective of data mining aids in the understanding of the ethical
implications of targeted marketing. Monitoring to such an extent gives rise to issues of domestic
surveillance. When the government imposed the Patriot Act in the Verizon case, domestic

surveillance was an issue that created privacy concerns for the public. On the other hand, when
businesses monitor, why are concerns not as prevalent? Companies can collect information like
names, addresses, interests, and even friends' information that they link closely in their database.
So if the government is under scrutiny, what is it about business that allows all this attention to
be placed somewhere else?
Social Implications
The economy is a common ground that connects business to government. If businesses
know what customers want, they are able to produce desired products or services. In effect, the
information provided by data mining may allow for a rise in the economy because consumers
will spend if what they desire is easily accessible. When consumer actions provide companies
with these trends, there does not seem to be a return or benefit for the buyer. Instead, companies
seek the “rational pursuit of profits” at the consumer's expense as demonstrated in the Midwest
Grocery example in Chapter 2 (Gandy, 2012). Just because there is a purpose for data mining
does not mean that it is being used in a socially acceptable manner.
Lack of transparency worries society and is something that should worry business and
government also. Transparency is a social implication that must be addressed to measure the
nonexistent ability consumers have to defend themselves from the collection of their personal
information. One cannot stand up for themselves if they do not know something is happening
against them. They cannot speak against their profiles and the impressions created by them nor
can they “challenge their exclusion from opportunities in the marketplace” (Gandy, 2012, p. 12).
Gandy (2012) argues this limitation of information destroys the connectivity of society thus
ruining what is shared in terms of commonality (p. 13). Again, the issue is not only that of data

mining in its simplicity, but it as a means of influencing decisions such as one restraining from
internet use to protect themselves from being victims of this practice.

Case 2: Business Involvement: The Case of Facebook
The previous example presented a case that the blurred the line between governmental
and business involvement as it pertains to the releasing of information between the two parties.
In this chapter, I will demonstrate and discuss similar issues by strictly focusing on business. To
further explore and understand that data mining is not an issue that requires the involvement of
the government, that is to say, that can exist from a business to business exchange of
information, I will present the case of Facebook and external activities of its applications. These
activities will highlight the exchange of information and the violation of industry standards that
state “sites shouldn't share and advertisers shouldn't collect personally identifiable information
without users' permission” (Steel & Fowler, 2010, p. 3).
A Wall Street Journal series discovered that many “apps” on social-networking sites had
been sharing user identifying information and selling it to dozens of advertising and internet
tracking companies (Steel & Fowler, 2010, p. 1). This has made many question whether or not
Facebook can or cannot secure users’ information. Facebook’s team said they were trying to
limit exposure of personal information and mentioned that information could be collected
“inadvertently” by web browsers. After, they discussed a plan to introduce a method of
containing personal information (Steel & Fowler, 2010, p. 1). This makes one questions whether
they were actually confident with their current system. A Facebook official said, "Our technical
systems have always been complemented by strong policy enforcement, and we will continue to
rely on both to keep people in control of their information" (Steel & Fowler, 2010, p. 1).
Facebook's systems were not as efficient as they claimed to be.

Selling Information
Applications on Facebook were discovered to have transmitted user information to
outside parties. The purpose of applications is to provide additional activity on social networking
sites. Surprisingly, the majority of apps on Facebook were created by outside parties who were
granted permission to allow Facebook users to use them. Facebook claimed to not allow these
apps to access information and further transmit it to third parties (Steel & Fowler, 2010, p. 2).
The Wallstreet Journal investigation found that the ten most popular applications on Facebook
were transmitting user’s IDs to outside companies. These apps included Research Company
Inside Network Inc.’s Farmville, Texas Holdem, and Frontierville (Steel & Fowler, 2010, p. 1).
Three of the top ten applications were discovered to have transmitted personal information about
users’ friends while Facebook claimed it was unaware and later discontinued various
applications only after the Wall Street Journal’s findings were exposed (Steel & Fowler, 2010, p.
2).
Just because an individual turns their privacy settings off, does not mean they want their
information being shared. Alone, Facebook user IDs do not provide much information; but, when
searched, they provide a profile that is set to share with “everyone” (Steel & Fowler, 2010, p. 2).
The Wallstreet Journal discovered applications were sending ID numbers to at least 25
advertising and data firms in which several of them created profiles of users by tracking their
online activity (Steel & Fowler, 2010, p. 2). In a study that tested Facebook users’ concern with
information sharing from their profiles, Johnson, Egelman, and Bellovin (2012) discovered
privacy was a concern even for those who chose to keep all and some information about them on
the public setting (p. 5). When given broad scenarios of unwanted audiences viewing their
information, 10.8% were unconcerned while 85.7% of those had private profiles (p. 5).

Therefore, of the 89.2% of participants that were concerned, the majority were those whose
profiles were public. When participants were presented with 10 specific posts of their own and
asked if information could be shared with a complete stranger, each participant was concerned
about half of their posts being shared (p. 5). Therefore, claiming apps had access to information
that was set to public does not mean users are comfortable with unwanted parties acquiring or
being able to view it.
To accommodate for concerns regarding privacy, applications claim that anonymity,
therefore there is not a privacy issue. On the other hand, The Wall Street Journal detected data
gathering firm, RapLaf Inc., linked Facebook user ID information to its own database and later
sold it. Facebook said it prohibited applications from doing so but the journal questioned whether
they could stay on top of the 550,000 applications available on the site (Steel & Fowler, 2010, p.
2). They found that Facebook had transmitted ID numbers under circumstances like clicking on
advertisements and apps transmitted information to data firms that complied user information
(Steel & Fowler, 2010, p. 2). Facebook as well as its applications contributed to this transmission
that went from business to application to outside data and advertising firms. There was no
government involvement, yet when it comes to data mining, the government commonly is to
blame.
Navigation Freedom
Another issue is the concept of freedom. Madrigal (2012) introduces the contradiction of
“freely” moving online (p. 2). For example, the experiment of the 260 participants mentioned
earlier, demonstrates that even those who chose to have public profiles, were concerned about
strangers and unwanted audiences having access to at least some of their information (Johnson,
Egelman, and Bellovin, 2012, p. 5). Such discoveries of application sharing may force users to

pay closer attention to information they share and increase their privacy settings. Users are
already aware it is best to limit the type of information they choose to share, but, constantly
altered Facebook configurations such as the recent addition of automatic location recognition on
pictures and Facebook posts make it difficult to know how much additional information is being
unintentionally shared by the individual. The question of whether we can truly navigate freely or
navigate “freely” with close attention to what we post is one worth asking.
The cases of Verizon and Facebook show that the negative feelings created by the
government’s use of data mining do not seem to differ from the business' use of it. Concerns
regarding privacy and freedom are prevalent in both cases and though Verizon’s case
demonstrates a combined effort with the government, it also represents business and the gray
area of who is mainly responsible. In effect, both business and government shared information
that was not supposed to be shared.

CHAPTER 4: SOLUTIONS
The main issues that arise from data mining are violation of privacy, lack of transparency,
and abuse of the information collected by businesses. The complex ripple effect on consumers or
the public can only be addressed if we consider the causes, incentives, and social and/or cultural
perspectives of the practice. To address these problems, we need to look at these three areas to
provide solutions.
Violation of Privacy
The problem with businesses violating the public’s privacy can only be addressed if it is
viewed from a social/cultural perspective. Privacy needs to be approached as a social
phenomenon given that, in general, it is taken very seriously in the American culture but not as
seriously in the field of business. That is, for some reason, businesses have built platforms where
people have allowed them to acquire their information. Could this be because businesses are not
individuals so they can get away with invading privacy? Even so, no one should be able to get
away with that. This is why solutions must be provided to protect the privacy of individuals.
Consumers are not aware of how much information is collected about them because there
is no legal limit. In 1998, the Children's Online Privacy Protection Act was passed to ensure that
children under the age of 13 did not share personal information on the internet without their
parents’ approval. Such a law is not available for adults. Secondly, the amount and type of
information being collected needs to be regulated in a way that allows business to thrive, so the
question of ethics clashes with that of fair and responsible business practices. Data assists in
understanding customers to better service them. If the data collected was general, yet specific
enough, companies would be able to compile the information needed to help their business
function without "over collecting" and abusing their ability to do so. By rejecting information

such as age, name, etc. and accepting what was purchased, at what time, and maybe even method
of payment, without creating a profile, they would collect the information that is actually needed
and stray away from the unnecessary information of which they usually collect.
Another major problem that needs to be addressed is the reliability on technology to
violate privacy. Its influence on issues that impact society must be minimized and we need to
recognize that because it has the ability to discover personal information, it needs to be clear
when the dependence on technology has gotten too far. There needs to be some recognition that
humans are being affected and technology cannot delegate how individuals' information is
handled. It is challenging to not maximize technology's usage but crucial to understand that
consumers, not technology, are what keep businesses going. Just because it is possible to acquire
such private information does not mean that the power to do so can be abused by businesses.
Lack of Transparency
The first step to tackle the second major problem, lack of transparency, would be to
ensure customers know the details of this practice to accept, reject, or negotiate actions taken
against them. Businesses should be able to collect information only if consumers know so. There
is no consumer backlash because awareness of data mining by businesses is limited.
Transparency is necessary to display what is happening. Director Jules Polonestsky of the Future
of Privacy Forum, agrees, “It’s time… to take responsibility for ensuring that users know what
they’re doing, rather than leaving it to the platforms to play a game of Whac-A-Mole” (Perlroth,
2012, p. 2). If given the opportunity to give consent or simply know that the information they
unconsciously provided as they shopped was being collected for a purpose, consumers may feel
empowered which may allow them to grant permission to collect information in the first place.
Perlroth (2012) agrees lack of consumer knowledge needs to be addressed (p. 1-3).

Consumers can enhance data mining through awareness and consent. Companies should
allow the public access to their profiles or the ability to know what information will be obtained
so customers can complain if they need to. Google and Apple have attempted to address this
issue by building platforms in their apps that “force developers to notify people what data, if any,
they plan to access” (Perlroth, 2012, p. 2-3). By granting consumers access to these profiles, they
may accept or deny their representative image that was created through the profiles. According
to Madrigal (2012), “people have not taken control of the data that’s being collected and traded
about them” which is difficult to do if they do not know what that data is (p.3).
On top of the public knowing what information companies acquire, individuals should
have the opportunity to opt out, report to authorities, or at least complain to management. A
method of consent could be the option of “opting out” which limits the type of data collected
(Madrigal, 2012, p. 5). After trying this method, Madrigal discovered it only stopped him from
receiving targeted ads and did not stop data collection. A method of opting out that gives an
individual the option to stop receiving advertisements and data collection is necessary.
Abuse of Information
Consumers' personal information should be kept confidential within the business. In one
way or another, individuals confide in businesses to handle their information appropriately and
not use it to assist others such as outside parties. Abuse occurs when obtained information is
mishandled and/or sold. As demonstrated through the Facebook case in Chapter 3, the company
was not aware of its users’ information being collected by applications. Even worse, Facebook
was “unaware” the information was being sold to outside parties. There is a possibility customers
are aware that some information is collected when they make purchases or browse the web, but
this does not mean they expect the information to be passed along to others.

Chris Soghoian (2012) proposes the solution is to not have any information to offer when
it is requested. This will put companies in jeopardy because the data allows them to understand
their customers. Such an approach fails to look at all functions of data mining. He mentions that
10-15 years ago when the FBI needed information about possible suspects, they had to
investigate to find the information they desired. Now, when surveillance requests are issued by
the government, companies must hand the information over especially because the government
knows they are collecting it. He suggests companies do “not keep the data in the first place” so
they do not have anything to offer when asked by the government. An appropriate solution
should not jeopardize the success or personal information of any parties involved.
An ideal solution may or may not be possible but a combination of the ones listed above
will increase awareness that may eventually lead to compromise. In general, consumers and
businesses must participate in information processing and handling. By making decisions based
on what is in the best interest of the public while providing social awareness, data mining issues
may be successfully addressed.

CONCLUSION
Data mining poses ethical concerns that have been around for a while. Concerns are
present when the government "spies" on the public which is why we are advised to watch what
we say or do on the internet, phone, or other means of communication. Mentioning or doing
something that may be viewed as suspicious is avoided at all costs. Individuals are even advised
to be careful with what they research online. The control of the government outrages the public
and makes them want to fight for their rights. This thesis attempted to compare the government's
use of data mining to that of business' to inform that there are issues with uses from both parties.
The introduction provided an example of data mining used in business. Chapter two introduced
specific issues such as the focus on government as a threat, profiling, discrimination and equality
and the violation of privacy. The next chapter provided cases of data mining by businesses and
demonstrated ethical vs. legal, privacy, transparency, dependence on technology, and issues of
abuse and irresponsibility. Its intention was to display public concern about feeling “spied” on
and invoke questions of why it is that consumers are not angry at businesses also.
We’ve reached too far with the senseless amount of prying into people’s lives. There is
no justifiable purpose for all the actions taken to produce information simply to target market.
Honestly, it is particularly disturbing from an ethical perspective that businesses (and not just the
governments) seem to have decided that they have the right to own, use, sell/buy private
information. At the same time, it is shocking how widespread and yet how “accepted” it is that
we seem to allow this to happen. The cultural shift has led to a big blind spot and if not
addressed, could lead to the possible elimination of privacy all together.

This is a serious issue that cannot be left alone. It seems as though businesses are able to
get away with their actions because they are within legal boundaries and the government is
viewed as more of a threat because of the amount of power it holds. Unfortunately, if we
continue to accept legality as an answer to something being right or wrong, the problem will
never be fixed. Actions should be taken in the best interest of the public.
What was envisioned to be the future of data mining does not fall in line with how it is
used today. There were ideas of its basic uses for companies to know what consumers wanted so
they could later deliver that to them. Targeted marketing was an opportunity to connect buyers
and sellers by providing a method of understanding consumers and using that information to
please them (Peterson, 1997, p. 165). It was intended to allow business to be in tune with the
public and improve the market (Peterson. 1997, p.167).
To acknowledge the possibility of solutions, one needs to question the initial vision of
“electronic marketing”. Peterson (1997) proposes its intent was to help buyers locate products
and services according to “shopper-defined criteria” (p. 165). It was envisioned that once
someone searched online they would receive advertisements which is exactly how things are
now. The incentive was for consumers to customize purchases such as furniture, apparel, etc. that
comes with “increased consumer information, delivered on demand” (p. 165). Customization
was exciting and was envisioned to invoke these feelings and opportunities in the buyer.
Eventually, there was hope for the emergence of new market intermediaries. It was apparent
there might be issues of privacy and responsibility which is why privacy and security concerns
were forewarned. Information was said to be “carefully managed” with policies so consumers
could have control over how information about them would be used in the future (p. 172). The
vision from 1997 includes a solution to the problem. With further research about the emergence

of data mining, it may be possible to address it in such a way that allows for clarity and proper
use of it.

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