What are the privacy issues with data mining? Do you think they are substantiated?
Typically, data mining refers to a process that is mainly utilized by a firm in the conversion of raw data into useful information. Consequently, this process is performed by the use of software; many benefits come with employing this technology. The principal challenge associated with data mining is privacy. In the information era, the swift transfer of personal data has indicated a rise in identity theft. Again, this privacy issue has become a key concern when discussing data mining. Moreover, the data mining process makes it possible for firms to gain the data required to operate a business, nonetheless, it also gives the firm a substantial amount of personal data.
Further, the personal data that firms have access to can be easily sold to other people such as the third party without any knowledge. Data mining can be easily abused as it includes everything ranging from healthcare records, shopping habits, public records such as court and property records, and lastly, online practices. This data is then utilized in different fields including machine learning, database systems, intelligence gathering, and statistics.
The information that we give out on applications, for instance, government offices and banks are most likely placed in a database. The government has utilized data mining in the fight against any form of terrorism. This personal information again can fall into the hands of any person and be abused. Every person expects that his or her personal information is kept safely to avoid falling in the wrong hands. Therefore, consumers should be given the right to make choices on whether they want their personal information placed in a database. However, there is a higher likelihood that most will object this due to privacy concerns. Consequently, the government informs that it is vital that enough notice is given for data mining, who will be granted access, and how that data will be secured. Also, it includes whether the data will be updated in the future or not. This becomes a privacy concern since when data brokers store the information they have gathered, they are significantly running the risk that cyber attackers will breach the database. Ultimately, this becomes a fundamental cybersecurity concern when it relates to the storage of personal information.
The other example of privacy concern with the data mining process is the receipt of payment information by health professionals. The main role of data collection by a health professional has to be precisely comprehended by the consumer and also identified at the time of collection. However, data mining is a secondary process for future use. Therefore, it needs a precise consent of the patient, and since data mining is mainly based on the withdrawal of concealed patterns from a database. The system conducting the data mining process not know what relationships will emerge from the analysis of payment data. Hence, identifying a principal purpose at the beginning of the data mining process and then setting restrictions on one’s use of the data to that purpose, can be very challenging mainly for health professionals who are supposed to protect their patient’s information from data mining.