Ethics in Data and Web Mining

Ethics in info and Web minelayingLiliam FaraonWhat is the importance of ethics in entropy tap?We live in a time when the pursuit of noesis is indispensable. From the transformations we have witnessed in the past years, we basis ac noesis that t separatelying assumes a growing importance and a requirement for any sector of humanity activity. Some authors say that 90% of each(prenominal) information in the humans has been generated over the last two years, and more and more devices volition be connected to the internet generating info that tidy sum be phthisisd by companies to predict embodiments of consumption and increase specific sales.The obligate 17 profit of Things Facts E reall(a)yone Should Read published by Forbes in October, 2015, brings us an idea of or so numbers and the potential market that is lendable to be exploit straight off there atomic number 18 more objects connected to the internet than commonwealthBy the year of 2020 around 250.000 vehicles entrust be connected to the internet, (saving time go past in traffic, fuel, improving the performance and protecting the environment and generating information)The global clothing device market has gr decl atomic number 18 223% only in 2015 specially by the launching of Fitbit and Apple WatchesInternet of Things will add $10 to $15 trillion to global GDP by 2036 only looking at all the facts some questions are raised, such as how the entropy we pay back is managed and stored? How is it perceived? How businesses are taking advantage from all the that information? And finally, how do we protect our own entropy and make sure is not cosmos social function without consent? Thats where web minelaying poses a threat to respectable values, such as singularity and secrecy.Improvements in IT and storage capacity has enabled companies to bump tools for data collection through numerous a(prenominal) channels. There are a variety of ways individuals generate data, such as ATM vi sits, bar-code readers, biometric devices, denotation and debit card transactions, loyalty clubs, medical records, on berth shopping, rentals, scanners, subscriptions, website browsing and use of many Smart devices available. As a result, there is an exponential growth of the core of data stored and available to be explored. This generation of data brought the need of pertly techniques and technologies that can analyse and convert all this information into useful chouseledge and Data digging becomes a real herculean resource. When all these data are merged and mined, they can infer a someones associations, credit information, health, income, semipolitical interests and tastes.Liu defines data mine as The bear upon of discovering useful patterns or knowledge from data sources The patterns must be valid, potentially useful and understandable. (Liu, 2011, p. 6).Data mining base on algorithms are truly automated and analytical tools and its use is rapidly increasing. By co mbining databases, information visualisation, machine learning, mathematical modelling, pattern recognition, statistics and more recently artificial intelligence, very large and complex datasets can be analysed and relationships, patterns, outliers and trends can be revealed.Figure 1 Data Mining Raw data itself is not useful at all, just now the information that can be extracted from the data is where the real value seats. We have ageless amounts of data being produced and stored, it makes sense companies and governments have the desire to analyse all this data to uncover patterns potentially useful hidden in there. Data Mining process is basically categorised into two classesDescriptive describes the oecumenical properties of information stored in a databasePredictive draws inferences from the data in post to make predictions.Witten emphasises Data Mining is to the highest degree solving problems by analysing data already present in databases (Witten, 2013, p. 4). Decision m akers desire the right answers for unspecific questions and obviously, the more data gathered the more questions raised. Which customers are likely to move in a positive way to a marketing endeavour? What products will have more success when launched? What is the best price upchuck for a new product? How do the competitors tend to react? The rejoinder for those questions cannot be reached based on feelings or intuition, they can be answered by analysing customers behaviour and profile using data mining tools.By amass and summarizing and making use of data mining companies and organisations can identify insights and arrive competitive advantage, recognize potential competitors, improve customer service relationship, tail customer expectations and needs. It also has important uses in social business and science, close to recently Government Agencies are using Data and Web mining applications to uncover criminal activities such as terrorist threats.There are many Data Mining t ools are available in the market nowadays, each one with its particularities, the most common are KNIME, NLTK, Orange, RapidMiner (formerly known as YALE), R-Programming and weka .Ethics must be a condition of the worldly concern, like logic. Ludwig Wittgenstein, 1889-1951. demon social media such as LinkedIn, Facebook and Twitter hold billions of users data, keeping these data protect and as a secret is a big concern. When an individual creates an account on any of those social media channels a insurance agreement is accepted, and it is basically data related.Data Mining analysts use wad in-person information collected by organisations all over the world through many different technologies and use them especially for prediction analysis, but practitioners must be very careful when analysing patterns, accredited kinds of discrimination are not only un respectable but also il effective, gender, religion, race and certain sensitive information is totally unacceptable, in the othe r hand, anonymizing data is very difficult, for example, over 85% of Americans can be identified from publicity available records using just three pieces of information zip code, birth time and sex (Witten, 2013, p.33).When a person shops for a product online, the company has plan of attack to customers address, credit card, name, phone number and other information in their database. But how does the company encrypts the information and protects it from misuse or security breach is and estimable and legal issue. Some proceedss are also raised Is it estimable and legal to use the users information for publicity purposes? How can users protect their right of hiding? Where does the right of a company meets the ethics when sharing its data with some other company to comprehend and understand customers and increase profit by sell this information to third party companies is a very important matter and it must be carefully discussed. There is a thin line between of a persons priva cy and companys right to use it. When a person provides own(prenominal) information, he or she needs to know how and what it will be used and a few steps must be taken to guarantee confidentiality and integrity.The use of data particularly data about people for data mining has serious ethical implications and practitioners of data mining techniques must act responsibly by making themselves aware of the ethical issues that butt against their particular application. (Witten, 2013, p. 33).There is a growing concern regarding to the use of common soldier and sensitive information and the ethical issues of Data Mining must be analysed and understood both from the business and the personal point of view. From a personal point of view, by Data Mining execution respecting consent, privacy and regulations customers big businessman appreciate the fact they are being target with more individualise offers based on circumstances and needs and in return they may be willing to provide mor e specific data about themselves. From a business point of view by respecting the privacy issues companies will save resources as they will be able to target very specific customers for certain products. It is obvious that as any other powerful technology there are negative consequences of Data Mining, some results can ineffective, misdirected or unregulated, but if used correctly it can be very resourceful.Some points are very important and organizations making use of data mining techniques should salute a thought about them when the use of personal data is plannedConnectivity and data sharingAll the users and people that give consent are connected through the internet and share dataSecurity is essentialOnce all the information traffics through databases, companies commove about the security and privacy, that way all the data will be encrypted, the web services will be hosted in a boniface with a certificate installed and authentication userThe importance of Privacy indemnityPr ivacy Policy is a legal statement and regulates the privacy insurance related to users personal data which is under companies responsibilityInfrastructureThe process will not function without an application to analyse, interpret, read and draw patterns from the dataAccount managementGathering and leveragingAccount Management has all the information gathered and leveraged, and elaborate can advertising campaigns. It plays an important situation in the profitability of the companyInformation could be released without the consent of the person, it becomes an ethical dilemma, because sometimes the users are unaware of the information gathered and that is being used by companies. It is very important to highlight that the person has the right to know how it will be used and should be able to have the chance to consent or not the collection and use. And also when a person becomes part of a group profile and used as a decision making basis, the individuality is threatened, people cannot be judged only as group members, but also as an individual, able to make its own decisions.It is likely that in the next few years an inspection of ethical issues and legal implications will be further required, legislation of digital privacy will be developed and laws will enter force, confidentiality and privacy conservation should be the main points of concern. Unauthorised extraction of data will be considered a crime and companies must be ready for that.Data Mining algorithms are very important and powerful tools for analysis and predictions, they are expect to become more and more significant in the future, decision based on data will change the way companies base their processes, of cartroad there are no 100% guarantee that they will succeed, but, are more likely to be successful than decisions based on feelings or gut. Once patterns are revealed profiles can be drown and stereotypes can be used for crime prevention, commercial proposes, marketing campaigns, policies develo pment and many others.interim Data Mining ethical issues need to be raised and sentience increased, as the world continues to develop, more and more data is likely to be collected and the Data Mining processes will become more sophisticated. passel will need to get a clearer idea of privacy and companies will have to become more transparent on its processes of collect, gather and use of data.Cook, Jack (2005). Ethics of data mining. Available athttp//scholarworks.rit.edu/cgi/viewcontent.cgi?article=1443context=articleEthics in Computing. Available at https//ethics.csc.ncsu.edu/privacy/mining/study.php Accessed 02 treat 2017.Fule, Peter. Detecting Privacy and honest Sensitivity in Data Mining Results. Available at http//crpit.com/confpapers/CRPITV26Fule.pdfLiu, Bing. (2011). Web Data Mining Exploring Hyperlinks, Contents, and Usage Data, customsMARR, Bernard.17 Internet Of Things Facts Everyone Should Read (2015). Available at http//www.forbes.com/sites/bernardmarr/2015/10/27/17 -mind-blowing-internet-of-things-facts-everyone-should-read/5e463ad01a7a Accessed 01 march 2017.Wahlstrom, Kirsten (2006). On the Ethical and Legal Implications of Data Mining. Available at https//csem.flinders.edu.au/ query/techreps/SIE06001.pdfWitten, Ian H (2013). Data Mining Practical Machine Learning Tools and Techniques, Morgan Kaufmann.Zhen, Ethical issues in Web Data Mining. Available athttp//blog.nus.edu.sg/group208/2012/11/25/ethical-issues-in-web-data-mining/ Accessed 01 March 2017.