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Data Warehousing and Data Mining

notes unethically by offering these vulnerable people inferior deals. For example, Mrs. Smith’s husband
was diagnosis with colon cancer, and the doctor predicted that he is going to die soon. Mrs.
Smith was so worry and depressed. Suppose through Mrs. Smith’s participation in a chat room
or mailing list, someone predicts that either she or someone close to her has a terminal illness.
Maybe through this prediction, Mrs. Smith started receiving email from some strangers stating
that they know a cure for colon cancer, but it will cause her a lot of money. Mrs. Smith who is
desperately wanted to save her husband, may fall into their trap. This hypothetical example
illustrated that how unethical it is for somebody to use data obtained through data mining to
target vulnerable person who are desperately hoping for a miracle.
Data mining can also be used to discriminate against a certain group of people in the population.
For example, if through data mining, a certain group of people were determine to carry a high risk
for a deathly disease (eg. HIV, cancer), then the insurance company may refuse to sell insurance
policy to them based on this information. The insurance company’s action is not only unethical,
but may also have severe impact on our health care system as well as the individuals involved.
If these high risk people cannot buy insurance, they may die sooner than expected because they
cannot afford to go to the doctor as often as they should. In addition, the government may have
to step in and provide insurance coverage for those people, thus would drive up the health care
costs.
Data mining is not a flawless process, thus mistakes are bound to happen. For example, a file of
one person may get mismatch to another person file. In today world, where we replied heavily
on the computer for information, a mistake generated by the computer could have serious
consequence. One may ask is it ethical for someone with a good credit history to get reject for a
loan application because his/her credit history get mismatched with someone else bearing the
same name and a bankruptcy profile? The answer is “NO” because this individual does not do
anything wrong. However, it may take a while for this person to get his file straighten out. In
the mean time, he or she just has to live with the mistake generated by the computer. Companies
might say that this is an unfortunate mistake and move on, but to this individual this mistake
can ruin his/her life.

2.11.2 organizations’ point of view

Data mining is a dream comes true to businesses because data mining helps enhance their overall
operations and discover new patterns that may allow companies to better serve their customers.
Through data mining, financial and insurance companies are able to detect patterns of fraudulent
credit care usage, identify behavior patterns of risk customers, and analyze claims. Data mining
would help these companies minimize their risk and increase their profits. Since companies are
able to minimize their risk, they may be able to charge the customers lower interest rate or lower
premium. Companies are saying that data mining is beneficial to everyone because some of the
benefit that they obtained through data mining will be passed on to the consumers.

Data mining also allows marketing companies to target their customers more effectively; thus,
reducing their needs for mass advertisements. As a result, the companies can pass on their saving
to the consumers. According to Michael Turner, an executive director of a Directing Marking
Association “Detailed consumer information lets apparel retailers market their products to
consumers with more precision. But if privacy rules impose restrictions and barriers to data
collection, those limitations could increase the prices consumers pay when they buy from catalog
or online apparel retailers by 3.5% to 11%”.
When it comes to privacy issues, organizations are saying that they are doing everything they
can to protect their customers’ personal information. In addition, they only use consumer data
for ethical purposes such as marketing, detecting credit card fraudulent, and etc. To ensure that
personal information are used in an ethical way, the chief information officers (CIO) Magazine

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