The core idea of data mining is about analyzing large complex databases and identifying useful patterns, trends, and information in the unorganized data. This is accomplished by software programs and machine learning algorithms. Data mining has been successfully used by retail, marketing, e-commerce, healthcare, and other business organizations. In the business sector like marketing, e-commerce, and retail data mining are used to analyze customer behavior to predict trends thereby enhancing a company's revenue or profits. In the healthcare sector, data mining is used for storing patient data, for reducing costs and other health-related processes. The insurance sector has begun using data mining for customer data storage and analysis. Governmental agencies are well-known to use data mining for accessing and storing large quantities of individual information for the purposes of national security.
Ethical implications for businesses using data mining are different from legal implications. Performing a theft is defined as illegal, but even thinking of trying to attempt a theft is termed unethical. Hence, the concerns among public is that when companies even attempt to use their shopping information or other data to target them back with more products, they consider it unethical. But despite this, ethics surrounding data mining is a gray area. The entire technology cannot be considered good or bad since it has many useful advantages for the public good too.
With the rise of data mining applications to various sectors, there is an equivalent rise in concerns about the ethics of mining customer data for the motive of profit. The process of mining data by companies is not going to reduce in the future; rather it is going to increase with more organizations accessing computer power.
One of the most often cited issue with mining personal data is when the information mined from an individual's consumption behavior is used to market more products and services to that individual. Here companies appear to focus on the philosophy that if more data is mined then sales of products will automatically increase. While this may be true to some extent, it can severely conflict with customers. Some examples of such conflicts are listed below:
- A teenage girl searches a company's website that sells baby products. And the data mining application of the company immediately tracks the customer information and sends baby products addressed to the teenage girl. This can cause embarrassment to the girl and her family. A prime example is the 2012 Target store incident.
- A person who has lost his/her legs might simply have browsed online for shoes out of curiosity or a desire to see shoes. If a company were to send him/her information about shoes, he/she might be pained at receiving it.
Another area of concern is the ethical use of data mining applications in the healthcare industry. Patient information is required by law to be gathered only with complete consent by the patient. And such information can be accessed or used by research companies only after many levels of security checks. Despite the regulations on paper and the agencies implementing, some organizers perform unethical mining of data without any consent or approval in order to discover a new product that might fetch high revenue.
The solution to the varied forms of ethical concerns of data mining by businesses is for companies to maintain transparency in mining data and being accountable for any breaches of privacy. They must be proactive in implementing the above two aspects in order to ameliorate customers that their personal data is not being misused and that the data is secure.