Arguments For and Against Data Mining

Value Sim

Intro

 The world we live and the people we are surrounded by have a thirst to learn and find every answer to life. As data is collected and questions are asked and answered more questions are posed. Some of those questions may not be as ever spanding like why are we here they may be as simple as how to to people respond to some product or what is hot on the market currently. The ability to raise questions and think critically is what makes a good decision maker. Decisions are made in every line of work and everyday in life.  A job of a data miner is no different because they must answer how to get data and support product development or ad campaigns. Data mining gives mass amounts of data that can be used to support and often direct crucial decisions. Although data mining can provide insight into companies and consumer there is an “inherent risk that what might be inferred may be private or ethically sensitive (Fule & Roddick, 2 004, p.159).”

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 Before we can go further into the paper we must establish what data mining is. Data mining is the process of discovering and interpreting patterns that were once hidden in data. These patterns are then used to make predictions on what may occur next.

 The process of generating these patterns and mining become an ethical issue “when the results found affect people or when when mining customers data unwittingly compromises the privacy of those customers (Fule & Roddick, 2 004, p.159).” Data miners and people meant to protect the data must take these issues into account and asset what dilemmas exist in the current time.

 Most of the world’s top technology companies have seen this dilemma or have been accused of mishandling people’s personal lives, thus the ICCP was formed which tried to set rules in place for how anyone in the cyber field are supposed to act when handling confidential data.

 The ICCP is not the best solution to this answer because a company  must accept the issue at hand and make sure its employees follow the guidelines set forth to them. Without this guidance it is up to the data mining team and the decision makers behind them which they may have bias  or predetermined judgments about the groups they are collecting from.

 A data miner who aware of their own emotional intelligence can be essential not only to his company but to the safety of consumers. A data miner needs to know there is a lot of grey areas and that their personal beliefs about a product or a group of people need to be set aside when finding the patterns. One huge argument against data mining is the racism present by the people behind it, this leads to police monitoring and people being put down. The miners need to be aware of their predetermined notions. 

Argument Against Data Mining

 Computers and other technology have completely redefined public and private information making what was once private public. As a result we lose privacy, “Privacy is the freedom granted to individuals to control expose to others( brey, 2000, pp. 14). Most things about people can be found on there facebook which in turn can be used to target them with advertisement and invade their space. People of other races and sexual orientation are then targeted by hate groups making them have to go to great lengths to avoid the prying eyes of people. The idea of this privacy which is established by Brey is called relational privacy which is the control over one’s environment when this environment is breached the person can become distrustful, hurt, or possibly suicidal. In any way this type of breach is unethical a data miner in no way should take someone’s race or sexual orientation into account but it happens often.

 Another form of privacy established by brey is informational privacy which is your collective thoughts ideas, text messages, pictures or anything of that matter(Brey p. 15).  This privacy is more hard to control because this is out there anyone can see pictures but there is a fine line when using it to predict shopping habits of a person.

 Another issue with data mining besides privacy is the transactional side of it, “most people do not have an issue with the factual data which can be used to determine good students or medical issues the problem becomes with what the people do the transactional which is used to determine criminals or terrorists(Adomavicious and Tuzhilin, 2001). There is issue with the transactional because its filled with bias and predetermined thoughts. In a recent court case data mining was used to find a suspect of a crime the only issue was that the bias of the miner went into finding  the suspect and they arrested and jailed the wrong man for 2 years. Rep. Curt Weldon who is a former house Chairman of Military research has gone on record and stated “33 federal agencies use data analysis and each have issues linking data together(Verton p5)”. Steve cooper the former head of Homeland has stated the same with him not being able to see collaboration with other federal services to best match suspects. This failed and bias data mining can not continue because you are wasting time and resources of the american taxpayer.

These tactics aren’t just used in police work they are used in immigration as well with ICE using biased data mining from social media to “detect” potential illegal threats leading to the false detainment of hundred of legal people(Verton pg. 10).

Data mining is flawed but its flaw lies within the people using it because there are many good things that can come out of data mining like technological breakthroughs, environment changes, Education ,and early detection of medical issues.

Argument For Data Mining

 Data mining has lead to massive changes in the world and has benefited many in terms of a better life. Facebook and other social media was designed to gather data and collect social profiles of people’s lives in term it connected the world and made platforms for people to share their voice that they may not have had before. It’s given some people purpose in life and it also has created jobs and businesses that couldn’t have opened without the online marketplace. Data mining grows economies it allows business to develop products people want and in turn it keeps the money flow at a steady rate.

 Data mining also allows for environmental watch. It can used to assess the population of phytoplankton and the water temperature and make prediction of the population effect on whales. This can be done with any species modeling but it allows environmental protection agencies to make changes to the environment like introducing a species of algae that can help the growth of phytoplankton to keep the whale population up after years of whale fishing.

 This in turn can used to figure out the best course solution to global warming. Data mining for environmental reasons has no privacy violations but it has an effect on human life with it we can save the world for future generations and even our own.

 Another pro to data mining is its effects on the education system here in the United States. We’ve all had state testing for PA its the PSSAs which test students 5-12 on math, reading and writing abilities to identify the schools with the best scores. “These scores in turn can be used to find the problem schools and identify where they are failing their students, it can also find what schools are doing well that can be applied to other schools(Mergel pg. 236).” There is a fine line with this do to child protection laws data mining schools is a tough task you can not receive any data on a particular student, but racism again rears its ugly head because these scores are then used to give state funding and the best scores get the highest amount of money and this usually gives inner city schools less money hurting test scores causing less money the next fiscal year. 

 Data mining is a tricky subject it’s hard to move away from it because the technology that is used is so intertwined with our culture. Our economy runs on targeted advertising there are business meant to collect data and sell you as a number, yet there are so many benefits of it we can figure out how a generation thinks, can determine stocks just by what’s trending on social media, Doctors can find out if someone has cancer just by recent illness and history.

 These are massive issues that people can take many different ways it all depends on their view of the world and tolerance level of other people that are different from them. In no way should a non trained or not certified data miner go collecting data because you can inflict so much damage on people without properly handling the information collected.

 After this paper I fully believe a data miner needs to be able to put aside their beliefs and bias so not to infringe on people’s rights, because when done properly data mining can find answers to the many questions we have about the world. They need to be tolerant of other people’s emotions due to the fact that they will come across people that they don’t agree with. There needs to be a level of emotional intelligence to put aside difference and just look at the numbers.

 At first data mining looked like a black and white job you had the information you could get and the information you can’t but this is a truly poor way of looking at this field its grey they need a very Utilitarian view of the world because there are no clear answers. Their is a line not be crossed though and that is in Brey’s form of relational privacy.

Work Cited

• Adomavicius & Tuzhilian. Using data mining method to build customer profiles
• Brey, Disclosive computer ethics. Computer and Society, 10-16
• “Code of Ethics, Conduct, Practice.” PROFESSIONAL CERTIFICATIONS FOR EMERGING TECH, iccp.org/code-of-ethics-conduct-practice.html.
• Dinev, Tamara, and Paul Hart. “Internet Privacy Concerns and Social Awareness as Determinants of Intention to Transact.” International Journal of Electronic Commerce, vol. 10, no. 2, 2005, pp. 7–29. JSTOR, www.jstor.org/stable/27751182.
• Fule & Roddick. Detecting Privacy and ethical sensitivity in data mining results.
• Mergel, Ines. “Big Data in Public Affairs Education.” Journal of Public Affairs Education, vol. 22, no. 2, 2016, pp. 231–248., www.jstor.org/stable/44114760
• Richterich, Annika.“Big Data-Driven Health Surveillance.” The Big Data Agenda: Data Ethics and Critical Data Studies, by Annika Richterich, vol. 6, University of Westminster Press, London, 2018, pp. 71–90. JSTOR, www.jstor.org/stable/j.ctv5vddsw.7.
• Slobogin, Christopher. “Government Data Mining and the Fourth Amendment.” The University of Chicago Law Review, vol. 75, no. 1, 2008, pp. 317–341. JSTOR, www.jstor.org/stable/20141910.
• Verton. Congressman says data mining oud have prevented 9-11. Computer World, 5.
• Verton. Database woes thwart counterterrorism don’t’ work. Computer world. 14