In the United States and around the world, people who are willing to consider both sides of an issue without jumping to conclusions can be quite valuable. When it comes to the intertwining topics of data mining and public wellbeing, a consensus as to whether the practice is inappropriate or enlightened cannot be easily reached. Instead, it can be recognized that the use of data mining for safety and health purposes produces a mixture of pros and cons. Although the positives of potentially reduced crime and improvements in the treatment of patients may seem attractive, many people have raised concerns over the implications of racial profiling and inaccurate data.
Within the healthcare community, data mining has become increasingly relied upon for clinical emergency medicine. According to the National Institutes of Health, the data mining technique called clustering is used to “make predictions” and to “take proper and timely treatment decisions and reduce hospital costs” (Parva et al. 1). This may be a surprising strength for hospitals because the organization of information can be directly linked to more effective treatment. Another study by National Institutes of Health examined the role that data mining on Twitter has in tracking drug abuse patterns. Although more efficient clinical emergency medicine and an increased ability to combat drug abuse are potentially valuable, what happens when patients and the people being studied voice misgivings about their privacy and individuality being infringed upon by hospitals and medical researchers?
Similarly to the medical industry, police departments have the ability to use social media data mining to track certain groups of people. Technology they possess allows them to search through hashtags that are associated with specific crimes. Although critics have raised concerns that race, religion, and ethnicity play too large a role in the methodology of policing through data mining, the strengths of the practice cannot be ignored. The safety of whole communities is being improved because of data mining. After the September eleventh terrorist attacks, many government organizations began to use data mining to track suspicious people. Per a “2006 report to Congress,” The Department of Homeland Security has stated that they use data mining to track terrorists (Rubinstein et al. 5).
A researcher and software engineer has the viewpoint that “A trend can only reflect facts held in the current database – it cannot claim to make character judgments about an individual from the relevant interest group” (Martis 7). This is a notable idea because although he acknowledges the benefits of data mining, the author is pointing out that the conclusions that are made based on data are oftentimes inaccurate. Data mining does a fine job of compiling data and attempting to put all of the pieces of a person together, but there are always going to be parts that are missing. The fact that data mining has numerous detriments, however, does not deter the author from writing that “the power and applicability of such technologies is too great to ignore” (Martis 8). Even though this source appreciates the value of data mining while pointing out the weaknesses of the practice, it is interesting to think about how possibly misinterpreted data could be used to perpetuate stereotypes in both the law enforcement and medical communities.
The monumental issue of data mining is worthy of society’s full attention and scrutiny. The faults and strengths of data mining in regards to the health and safety of the public need to be analyzed deeply in order to establish a positive relationship. It is obvious that data mining and similar technologies will not be disappearing any time soon, and figuring out ways to safely use Internet data mining while making advances is crucial for the future success of America.
Internet Data Mining 