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 ContentsABSTRACT...............................................................................................................................................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 of Business 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......................................................................22

Selling Information..............................................................................................................................23

Navigation Freedom............................................................................................................................24

CHAPTER 4: SOLUTIONS...................................................................................................................26

Violation of Privacy.............................................................................................................................26

Lack of Transparency.........................................................................................................................27

Abuse of Information..........................................................................................................................28

CONCLUSION........................................................................................................................................30

REFERENCES........................................................................................................................................33


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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