The Introduction of Social Networking and the Destruction of Privacy: Is online privacy obsolete?
The acquisition of information is synonymous with the gain of knowledge and power. With the creation and rise of social networking sites such as Facebook, Twitter and Instagram, online information has never been so easy to access. However, as the popularity of such platforms rises it becomes easier to live an online life and we often neglect that our most personal information is being shared with ‘strangers’ on the other side of a computer screen. The transparency of government organisations and corporate businesses in terms of data collection and collation via privacy-destroying technologies and data mining is essential to maintain ethical standards of company behaviour.
Online privacy often becomes neglected by web users, as social networking platforms make it easy to overshare our personal information. Tavani (2011), as cited in Al-Saggaf (2014), defines privacy as ‘the ability to restrict others access to and control the flow of one’s personal information, including the transfer and exchange of the information.’ However, modern day techniques and technologies are being used by public and private sector companies, governments and businesses to better themselves, putting our privacy and confidentiality at the bottom of their priority lists. It now seems as though privacy is impossible, as these technologies allow people sitting on the other side of a computer screen to monitor our every move. Businesses, governments and private corporations are using privacy-destroying technologies to help them improve their position in the market.
Privacy-destroying technologies are technological advances which make it easy to collect and collate information from individuals, sometimes even without their consent. Governments and businesses often use these technologies to collect information from online users. Facial recognition, surveillance, internet, vehicle and cell-phone tracking and sense-enhanced searches are all examples of privacy-destroying technologies (Froomkin, 2000). These ‘monitoring’ technologies are quite frequently associated with government use; however, they are being increasingly used in the private sector. Employers will often use them to monitor employee behaviour, and use internet searches to collect information about their cliental base and customers (Froomkin, 2000). These technologies work to their full effect when the individual they are ‘spying’ on is unaware that they are being watched and monitored.
Data mining shares similar foundations to privacy-destroying technologies, where both achieve optimum results when the user unknowingly becomes the participant, and they are unaware that their personal information is being collected. Data mining, by definition, is the process of extracting information from a large source of information (Saravanan, 2016). There are three types of data mining: content mining, structure mining and usage mining (Aldekhail, 2016). In terms of the use of data mining by governments and business and/or corporations, content mining and usage mining would be their main focuses. Content mining extracts helpful information from online sources and documents. Yogish, Raju & Manjunath (2011) describes the second type of data mining, content mining, as the process of extracting user access patters from server logs. Any type of information available on the internet can be subject to data mining techniques.
The World Wide Web is the largest source of data and information that exists, and when mining this information, the ethics of the online users must be considered. Ethics are the standards, values or ‘written rules’ that guide the behaviour business and government organisations when making and executing decisions. Data mining creates difficulties for individuals to control the release of their personal data online, and therefore raises ethical issues surrounding privacy, confidentiality and individuality (van Wel & Royakkers, 2004). The key ethical issue that relates to data mining is whether the individual is aware that their personal information is being collected and therefore are totally blind to how their information is being used.
Al-Saggaf (2014) explains that data mining techniques manage to forego the protection to private information, as the information that they are ‘mining’ is easily accessible and publicly available, as well as being non-confidential. While the collection of data might follow ethical standards, what the mined information is being used for does raise issues of consent, ethical standards and breach of individual privacy (Al-Saggaff, 2014). While data mining may be used for what seems harmless practices such as understanding customer and consumer behaviour, there are many questions associated with whether the individuals have consented to these data collection techniques.
The International Security, Trust and Privacy Alliance (2001) Framework Project, as cited in Dean, Payne & Landry (2016), states that ‘individuals have the right to decide how information about hem is shared, whom it is shared with and to what extent.’ The Kantian policy of data mining details a number of moral principles and questions that the miner must ask themselves before collecting the information. The data miner may ask themselves questions such as: ‘How would I want my personal information to be collected, stored online and shared with others? Does the collection of data benefit the subject or is the subject being used to benefit the organisation? (Dean, Payne & Landry, 2016).
However, with data mining it is difficult to declare what patterns or trends the mined data will reveal, and therefore it is hard to specify what information is being collected and what it is being used for in advance (van Wel & Royakkers, 2004). Due to this, it becomes difficult for the individual to be able to give their consent, as their personal information may not be what the data miners were aiming to find. It could be said, that data mining is indeed positive, as it can be used to predict future spending habits of customers, and businesses will be able to match and help their customers in a better way. Data mining could indeed be viewed as a positive technique in obtaining useful information for business operation, but on the flipside, the collection of personal information that is shared on social media by individuals could lead to dissemination of false or misleading personal data.
The most popular and successful social networking site Facebook has created a simple, efficient way of collecting basic personal information from its users, and most would not even know what they are participating in. What seems like basic and normal start up questions, could in fact be the way that Facebook filters personal news feed, or markets products specifically matched to you and the advertisements that appear on the side bar. Al-Saggaff (2014) reveals that the questions asked to produce a personal profile, such as gender, age, location, interests, education and work history, in addition with a profile picture can be used simultaneously to violate an individual’s privacy. By doing this, social networking platforms encourage users to share their personal information, and by answering all the personal questions, users often find it easier to modify their personal profiles, however are more likely than not to be unaware that they are allowing third-party applications to access their profile (Al-Saggaff, 2014).
With all this in mind, online privacy is not obsolete, however measures need to be taken by both individuals and organisations to ensure that ethics are kept at the centre of decision making and if so, individuals will continue to maintain their right to privacy. As it has been found, it is difficult for governmental organisations and businesses to remain transparent in their use of privacy-destroying technologies and data mining techniques, as they are unsure what information is going to be revealed. However, good practice would be to put a code of ethical standards in place to ensure that personal information of their customers, consumers, or in terms of the government their supporters, is not incorrectly shared, used or disseminated. Individuals should also make a conscious effort to protect their personal information, by not sharing information they don’t wish for others to know online, and by thinking before acting or sharing.
Overall, data mining is used by companies for the greater good, such as investigating customer spending habits. However, data mining that collects and collates information from social media platforms, such as their personal details about gender, location, photos and contact information are the ones that are raising privacy concerns. If practices like this continue, without the integration of a code of ethics, an individual’s privacy and confidentiality is being breached and could lead to online privacy becoming obsolete. The main concern with data mining is that individuals are often unaware that their personal data is being collected. Consequently, online privacy is not obsolete, however if unethical data mining continues, we are well on our way to no longer being able to maintain our online privacy.
Froomkin, M 2000, ‘The Death of Privacy?’ Stanford Law Review, vol. 52, no. 5, pp. 1461-1543, viewed 19 September 2016, via JSTOR database
Dean, M, Payne, D & Landry, B 2016, ‘Data mining: an ethical baseline for online privacy policies,’ Journal of Enterprise Information Management, vol. 29, no. 4, pp. 482-504, viewed 19 September 2016, via Emerald Insight database
Al-Saggaf, Y 2014, ‘Data Mining and Privacy of Social Network Sites’ Users: Implications of the Data Mining Problem,’ Science, English and Ethics, vol. 21, pp. 941-966, viewed 20 September 2016, via Springer Link database
Aldekhail, M 2016, ‘Application and Significance of Web Usage Mining in the 21st Century: A Literature Review,’ International Journal of Computer Theory and Engineering, vol. 8, no. 1, pp. 41-47, viewed 19 September 2016, via ProQuest database
Yogish, H, Raju, G & Manjunath T 2011, ‘The Descriptive Study of Knowledge Discovery from Web Usage Mining,’ International Journal of Computer Science Issues, vol. 8, no. 5, pp. 225-230, viewed 20 September 2016, via International Journal of Computer Science Issues database
Van Wel, L & Royakkers, L 2004, ‘Ethical issues in web data mining,’ Ethics and Information Technology, vol. 6, pp. 129-140, viewed 20 September 2016, via Springer Link database
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