ITC516 | What are Ethical Dilemmas in Data Mining | Information Technology
To analyse the risk, enterprises should start an ethical debate of arguments for and against specific actions of data mining. The ethical debate is about evaluating what is adequate and what is not adequate for the organisation and others as well. Every person has distinct principles, values, convictions and beliefs. As a result, ethical debate forces an enterprise to take a stand and identifies what it believes to be good or bad. The outcomes must be employed and repeatedly interacted and applied.
Ethics implications in data mining
The core idea of data mining is linked with an analysis of large complex database and determines useful trends, patters and information in an un-organised data. It can be accomplished by software programs as well as machine learning algorithms. Data mining is being used by marketing, retail, healthcare, e-commerce as well as other business organisation. In a business sector such as e-commerce, marketing and retail, data mining is used for analysing the consumer behaviour for predicting trends, hence improving the profits and revenue of an organisation. In a healthcare sector, data mining is involved for recording patient information for decreasing cost and health associated processes. Insurance sector begins to use data mining for consumer data storage and analysis. Governmental agencies are renowned to use data mining for accessing and recording wide quantities of personal information for national security purpose.
Ethical implications for organisations using data mining are distinct from the legal implications. Performing theft is as illegal but even thinking to attempt a theft is known as unethical. Therefore, the concerns among the public are when organisations even try to use the shopping information or data to target them with more services; they address it unethical.
Due to rise in data mining applications to different sectors, there is equivalent expansion in concerns linked with ethics of mining consumer data for motives of profit. Data mining process by the organisation will not reduce in future; rather it is increased with more enterprises accessing the computer power.
Another cited issue with personal mining information in when data mined from an individual’s consumption behaviour is involved to market more services and products to that individual.
Another area of concern is that ethical usage of data mining applications in a health care industry. Patient information is desired by law to be collected only with consent by a patient, and this information is accessed by research organisation after multiple levels of security checks. Despite these regulations on paper and organisations implementing, several organizers undertake unethical mining of data without approval to discover new products which may extract higher revenue.
Generate a code of conduct
Fundamentally, information leaders must work collectively through legal and marketing departments; generate a code of conduct for big data analytics. This code of conduct must comprise a list of principles which describes what an organisation finds adequate and inadequate, a process summarising ethical balancing and checks while conducting analytics, legal implications and if the deliberated use of data relates how it is being involved. The higher is the analytical usage of data is removed from real objectives of measurement; the more is the chance that data is involved questionably. Invest in metadata which demonstrates the origin of data, the objective of data and limitations for the usage. Ethical guideline needs regular reinforcement and attention. An organisation you should ensure that every section of the business case, as well as proposal, are part of checklist while executing analytical activities or campaigns. Send reminders to the critical staff and solicit acknowledgement from people engaged about how principles are useful. Guidelines can be effective when they are on top of mind and applied.
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