In this cyber age, data is considered as valuable as gold. Every big company is pursuing user data so that they can understand and serve their potential customers better than their competitors. In the old days, miners use to dig down deep in the earth to collect precious metals from mines. But now, the data mining experts gather meaningful information from cyberspace. Let’s see how this new (data) mining system works and assess the negative effects of data mining.
An overview of data mining
Data mining is a computational process by which an individual or company can extract meaningful information out of a big data set. There are various data mining tools available in the market, which enhances the data mining process rapidly. By using these tools, data mining experts can filter down required data quickly. Due to this, many experts also refer to this process as KDD (Knowledge Discovery from Data). Depending upon the size of a dataset, experts use different methods of data mining. Let us not get more deep into the methods and process of data mining.
Benefits of data mining
Data mining plays a crucial role in the cyber industry. It helps us understand user behavior, analyze complex medical data sets, develop artificial intelligence, etc. By using different methods of data mining, we can explore and use untapped valuable knowledge of big data sets. Many industry leaders like Google, Facebook, Amazon, and Tesla are already using data mining to improve their product and serve us better.
#1. Negative aspects of data mining
Every coin has two sides, and, naturally, anything good is also bad. When it comes to data mining, the method of usage of the data, the reason for mining, and other reasons can lead to a negative impact on the public. Data mining, as such, is not a harmful element but, the hand that wields it can alter its course. Here are some of the top issues of data mining.
#2. Privacy issue
Often, many companies use data mining to narrow down their potential customers and serve the targeted advertisement. They often exploit the user’s private information to gain personal benefits. How these miners could extract useful information is a big question here. This question also indicates that every information you provide on the internet is available for miners. For instance, if you order medicine for a medical condition in an online pharmacy, the information about the use of medicine can be extracted by the miners for pharmaceutical companies to provide advertisements for alternative or competitive products. Thus, no information that you can provide on the internet and expect it to be safe.
#3. Manipulation issues
What is the authenticity of the output of data mining? Well, it depends on the type of information you provide on the internet. Say, a person wants to create a hype about himself and posts information, which would imply that he owns a profitable business. Using manipulative information can make data miners mine incorrect data. This situation can be used by the said person to get financial access and other benefits. The same goes for political opinions. According to a study conducted by the Oxford Internet Institute, people from around nine countries use their social media platforms to propaganda false information. When data miners get hold of this information, they become facts, and this leads to fake news.
#4. Security issues
Data sets sold in the black market often create security issues for the public. This data can be used to blackmail, damage reputation, identity theft, and so on. In 2015, there as a breach in Washington, which leaked fingerprint data of millions of people. This breach is an acute threat, vowing to the fact that many banks can authorize transactions or change in passwords with just fingerprint matches. While hackers are trying to suck information, it would be more dangerous to mine out data from the cyberspace and sell it to hackers.
#5. Misuse of information and discrimination
Many fraudulent companies use data mining to target innocent people for various scams. They exploit the user’s personal information to generate passwords and steal money from their bank accounts. It is just the introduction of information misuse. According to a study, American Express has used data mining to discriminate its users. According to the mining report obtained by American Express, the customers who shopped in a certain shop tend to have poor debt payment history, and thus, the company reduced the credit rating for all those who shopped in that area. This kind of prediction and assumption is introducing discrimination beyond just skin color.
#6. Ethical issue
Just because a human-made algorithm predicts something, it does not assure its certainty. Governments taking financial or political decisions based on data mining can lead to catastrophic results in some cases. As mentioned before, discriminating people based on a few baseless information can lead to unpredictable decisions, which can cost money and brand value for many companies.
#7. Aggressive marketing
With data mining, spam and unsolicited advertisement will drown your devices. Target marketing is indeed very effective and profitable for both sides- user and seller. However, this can also be used to manipulate innocents into buying harmful products. For instance, with data mining, a company can extract the list of people with a disease with a social stigma like AIDS, infertility, and so on. With this list, the company can attract them with fake drugs or harmful supplements. Misused data in aggressive marketing can lead to nefarious results.
Even though there are some bad aspects are associated with data mining, it is not completely bad. If we utilize this process ethically, we can collect more meaningful information from the population’s behaviors. Data mining can revolutionize the research and development sector. We can develop new medicines or build artificial intelligence by utilizing information from the data mining process. Most of the negative effects of data mining operations are human-induced. We can also control and minimize these issues by implementing strong privacy policies and regulations. With governance over data mining and having a transparent process, the public could gain the best out of this technology.