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Computer Ethics the Internet's Rapid Term Paper

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Computer Ethics The Internet's Rapid Term Paper

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Clearly from this case and others there is a critical need for the development of safeguards on consumer data captured over the Internet, both of the opt-in (where the customer approves the data being captured) and the non-opt-in variety. An Explicit Requirement for Transparency and Ethical Use of Data

Consumers have become increasingly concerned that their data, however acquired, will eventually be sold without their knowledge, eventually leading to the potential for identity theft at the worst and continual junk e-mail and bulk mail at the least. Due to the pervasive lack of trust regarding the use of their data, consumers are increasingly calling for Corporate Social Responsibility (CSR) programs that will protect their rights and data despite any pre-existing claims made by the companies who captured it through benign surveillance techniques (Pirsch, Gupta, Grau. pp. 126, 127).

Facebook, one of the emerging companies that is defining social networking, has gone through its own ethical crisis already on the issue of transforming how customer data is acquired and fueling the debate of where benign surveillance ends and spying on customers begins (Tsai, p. 17). The Beacon fiasco sends a cautionary message to those companies who have data acquired through benign surveillance. Facebooks' decision to launch their Beacon initiative that tracked all activity of their users including sites they visited off of Facebook generated a user- and industry-led backlash resulting in a major fiasco for the company in late 2007 and early 2008. Not informing their customers that the data was being tracked and then presented to their friends in the context of guided selling sessions online not only violated the privacy of each user, they also ended up creating situations online between friends that strained relationships. One example of a man purchasing an engagement ring for his fiancee online to surprise her during the holidays of 2007 turned into a disaster as she was shown an advertisement of rings when she accessed her fiancees' page. The result was a spoiled wedding proposal. There were many more examples of how Facebook's complete lack of ethical forethought and execution caused pain for thousands of its users. Ethically, Facebook had the responsibility to inform all their subscribers, several times over to make sure they saw it, that a Beacon was being introduced and it would track their movements both on and off Facebook. Giving them the opportunity to opt-in or opt out would have also been the ethically correct decision to make. Instead, Facebook forged ahead and kept the program stealth until discovered by bloggers Charlene Li (Bernoff & Li, et.al) of Forrester. The beacon fiasco shows how delicate trust that is implicit in the use of data acquired through benign surveillance can quickly be violated. Social networking is the new means by which critical transparency is formed between companies collecting data and those that the data represents. Facebook considered one of the catalysts of social networking, ironically finds its future hanging in the balance of an online culture it helped create.

Benign Surveillance and Consumers Rights: Interpretations of the 4th Amendment

The U.S. has become a litigious society with the number of lawsuits over the use of data escalating rapidly. Often the 4th Amendment of the U.S. Constitution is used as a means of setting precedence in that nation in addition to defining ethical practices of using data obtained through benign surveillance in other nations where American-based companies operate. While the 4th Amendment of the U.S. Constitution gives the government the right to search for evidence, there is no legal precedence for marketers capturing data using any means including through benign surveillance, specifically those items regarding the tracking of online search behavior. Online marketers install cookies, or small text files that record what websites are visited by PC users and what they click on. The ability of online marketers to interpret then build patterns of online advertisements that pop up on users' screens has reached such proportions that one of the most popular downloads on the entire Internet is a Pop-Ad Blocker that roots out and destroys the programs that read cookies and send information back to advertisers. Lavasoft (www.lavasoft.de) hassince become one of the most popular downloads for other privacy software applications for Internet users. The use of these Pop-Up Blockers have been ruled constitutional by the U.S. Supreme Count, preserving the right to privacy of citizens from being monitored through benign surveillance when they don't trust the organization during the monitoring. The bottom line of all this is that the 4th Amendment will be strengthened over time to ward off security threats including terrorism, yet the "snooping" of marketers to get online surfing information will become even more rigorously punished.

Opt-Out Options Needed from Data Collected Through Benign Surveillance

The backlash and lack of trust in capturing data through benign surveillance all types is leading to a series of strategies on the part of consumers globally to protect their identities and also create a greater level of security for themselves online as well. Table 1, Data Elements Captured Through Benign Surveillance provides a comprehensive...

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The interpolation of specific fields and values, if not immediately provided by the online consumer or customer can often be interpolated and filled in by using other values in the data warehouses and data marts that also have powerful data analytics and statistical analysis applications associated with them.
Table 1: Data Elements Captured Through Benign Surveillance

Type of Personal Data

Description of the Data Elements

Demographic Data

Online purchases of products and services through personalized Web sites based on user profiles; software providers: Broadvision, Personify, NetPerceptions. This data is also for sales from InfoUSA.

User Knowledge

Expertise-dependent personalization; product and technical descriptions: Sales Assistant

User Skills and Capabilities

Help Systems that capitalize on the need for tracking user click streams including the problems that are being solved, specifically focusing on severity and type of problems.

User Interests and Preferences

Recommender systems that capture and store user preferences including car up-sell and cross-sell systems; domain of telephony devices

User Goals and Plans

Personalized support for users with targeted browsing behavior, plan recognition. This area also includes work completed by Google on their Latent Semantic Indexing Model.

Selective Actions

Adaptation based on link-selection including image selection and personalization including the development of on-site personas and the development of programs to deliver customized content.

Temporal Viewing Behavior

Adaptation based on viewing time including streaming objects; temporal navigation behavior

Ratings

Adaptation based on object ratings; product suggestions including the customization of product and web page content specifically for the development of a highly differentiated and unique user experience.

Purchases and Purchase-related actions

Suggestions of similar goods after product selection: Amazon.com; other purchase-related actions: registering, transferring products into virtual shopping cart, quizzes

Other (dis-) confirmatory actions

Adaptation based on other user actions, e.g. saving, printing documents, bookmarking a Web page and the tracking of this content is the main area of focus in this area of study.

Usage Frequency

Adaptation based on usage frequency; specific research is being completed on the icon toolbar and analysis of web page visits.

Situation-action correlations

Interface agents; routing mails and the analysis of meeting requests send through e-mail and across networks are also susceptible to being analyzed and captured without the sender or receivers' knowledge.

Action Sequences

Recommendations based on frequently used action sequences, e.g. past actions, action sequences of other users captured and analyzed in the context of each user account.

Software Environment

Adaptation based on users' browser versions and platforms, availability of plug-ins, Java and JavaScript versions also used for capturing user-specific data without their knowledge.

Hardware Environment

Adaptation based on users' bandwidth, processor speed, display devices (e.g. resolution), input devices; all configuration data is captured and evaluated as part of a users' profile.

Locale

Adaptation based on users' current location (e.g. country code), characteristics of usage locale; capture of local-specific variables to track and evaluate the use of a given sites' functionality and features, and the creation of consumer profiles specifically for this purpose.

There are an abundance of data types, elements and forms that can be captured benign surveillance data collection strategies and techniques, the future of data collections strategies will be increasingly defined by opt-out requirements on the part of consumers. Consumers will over time demand opt-out for every specific data attribute as breaches defined and voluntary mass surveillance strategies that need customer adoption to be ethical (as was the case with Facebook's Beacon project) require this option for consumers. In conclusion, the ethics of data acquire through benign surveillance is going to go through a revolutionary change, partially driven by the impact of social networking demanding higher levels of transparency, and also for greater controls over the data when used in development projects. From an application and service development standpoint, the need is even greater for compliance to ethical standards and processes to protect the confidentiality of the mass of personal data captured through voluntary mass surveillance.

References

Anders Albrechtslund 2007. Ethics and technology design. Ethics and Information Technology 9, no. 1 (March 1): 63. http://www.proquest.com (Accessed April 12, 2008).

Josh Bernoff, Charlene Li. 2008. Harnessing the Power of the Oh-So-Social Web. MIT Sloan Management Review 49, no. 3 (April 1): 36-42.…

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References

Anders Albrechtslund 2007. Ethics and technology design. Ethics and Information Technology 9, no. 1 (March 1): 63. http://www.proquest.com (Accessed April 12, 2008).

Josh Bernoff, Charlene Li. 2008. Harnessing the Power of the Oh-So-Social Web. MIT Sloan Management Review 49, no. 3 (April 1): 36-42. http://www.proquest.com (Accessed April 12, 2008).

Terrell Ward Bynum 2006. Flourishing Ethics. Ethics and Information Technology 8, no. 4 (November 1): 157-173. http://www.proquest.com (Accessed April 20, 2008).

Terrell Ward Bynum 2001. Computer ethics: Its birth and its future. Ethics and Information Technology 3, no. 2 (January 1): 109. http://www.proquest.com (Accessed April 14, 2008).
Anthony Danna, Oscar H. Gandy Jr. 2002. All that glitters is not gold: Digging beneath the surface of data mining. Journal of Business Ethics 1-40, no. 4 (November 1): 373-386. http://www.proquest.com Accessed April 10, 2008).
Richard De George 2006. Information technology, globalization and ethics. Ethics and Information Technology 8, no. 1 (March 1): 29-40. http://www.proquest.com (Accessed April 9, 2008).
William L. Dougan 2005. Social, Ethical and Policy Implication of Information Technology. Review of title_of_work_reviewed_in_italics, clarifying_information. Journal of Information Privacy & Security 1, no. 4 (October 1): 60-62. http://www.proquest.com. (Accessed April 2, 2008).
Selwyn Ellis, David Griffith. 2001. The evaluation of it ethical scenarios using a multidimensional scale. Database for Advances in Information Systems, January 1, 75-84. http://www.proquest.com. (Accessed March 28, 2008).
Charles Ess 2006. Ethical pluralism and global information ethics. Ethics and Information Technology 8, no. 4 (November 1): 215-226. http://www.proquest.com (Accessed March 31, 2008).
Luciano Floridi 2006. Four challenges for a theory of informational privacy. Ethics and Information Technology 8, no. 3 (July 1): 109-119. http://www.proquest.com (Accessed March 15, 2008).
Luciano Floridi, J.W. Sanders. 2001. Artificial evil and the foundation of computer ethics. Ethics and Information Technology 3, no. 1 (January 1): 55. http://www.proquest.com (Accessed April 13, 2008).
Krystyna G. rniak-Kocikowska 2007. From computer ethics to the ethics of global ICT society. Library hi-tech 25, no. 1 (January 1): 47-57. http://www.proquest.com (Accessed April 18, 2008).
Kenneth Einar Himma 2003. The relationship between the uniqueness of computer ethics and its independence as a discipline in applied ethics. Ethics and Information Technology 5, no. 4 (December 1): 225-237. http://www.proquest.com (Accessed April 11, 2008).
Rhea Ingram, Steven J. Skinner, Valerie a. Taylor. 2005. 'Consumers' Evaluation of Unethical Marketing Behaviors: The Role of Customer Commitment'. Journal of Business Ethics 62, no. 3 (December 1): 237-252. http://www.proquest.com. (Accessed April 9, 2008).
Justine Johnstone 2007. Technology as empowerment: a capability approach to computer ethics. Ethics and Information Technology 9, no. 1 (March 1): 73. http://www.proquest.com (Accessed April 12, 2008).
Russell Lacey, Julie Z. Sneath. 2006. Customer loyalty programs: are they fair to consumers? The Journal of Consumer Marketing 23, no. 7 (November 10): 458- 464. http://www.proquest.com (Accessed April 16, 2008).
Jeremy Moss 2002. 'Power and the digital divide'. Ethics and Information Technology 4, no. 2 (January 1): 159. http://www.proquest.com (Accessed April 16, 2008).
T. Nuyen 2004. Lyotard's postmodern ethics and information technology. Ethics and Information Technology 6, no. 3 (October 1): 185-191. http://www.proquest.com (Accessed April 19, 2008).
Donna K. Peeples 2002. Instilling consumer confidence in e-commerce. S.A.M. Advanced Management Journal 67, no. 4 (October 1): 26-31. http://www.proquest.com (Accessed April 21, 2008).
Michael Pemberton 1998. "Through a glass darkly": Ethics and information technology. ARMA Records Management Quarterly 32, no. 1 (January 1): 76-84+. http://www.proquest.com. (Accessed April 17, 2008).
Dane K. Peterson 2002. Computer ethics: The influence of guidelines and universal moral beliefs. Information Technology & People 15, no. 4 (January 1): 346-361. http://www.proquest.com (Accessed April 13, 2008).
Alan R. Peslak 2007. A REVIEW of the IMPACT of ACM CODE of CONDUCT on INFORMATION TECHNOLOGY MORAL JUDGMENT and INTENT. The Journal of Computer Information Systems 47, no. 3 (April 1): 1-10. http://www.proquest.com (Accessed April 10, 2008).
Sanjeev Phukan 2005. Using Information Technology Ethically: New Dimensions in the Age of the Internet. The Business Review, Cambridge 4, no. 1 (July 1): 234-239. http://www.proquest.com (Accessed April 9, 2008).
Julie Pirsch, Shruti Gupta, Stacy Landreth Grau. 2007. A Framework for Understanding Corporate Social Responsibility Programs as a Continuum: An Exploratory Study. Journal of Business Ethics 70, no. 2 (January 1): 125-140. http://www.proquest.com (Accessed April 19, 2008).
Johnny Hartz Soraker 2006. The role of pragmatic arguments in computer ethics. Ethics and Information Technology 8, no. 3 (July 1): 121-130. http://www.proquest.com (Accessed April 14, 2008).
Herman T. Tavani 2002. The uniqueness debate in computer ethics: What exactly is at issue, and why does it matter? Ethics and Information Technology 4, no. 1 (January 1): 37. http://www.proquest.com. (Accessed April 11, 2008).
Herman T. Tavani 1999. KDD, data mining, and the challenge for normative privacy. Ethics and Information Technology 1, no. 4 (January 1): 265-273. http://www.proquest.com (Accessed April 18, 2008).
Timm Triplett 2002. Bernard Gert's Morality and its application to computer ethics. Review of title_of_work_reviewed_in_italics, clarifying_information. Ethics and Information Technology 4, no. 1 (January 1): 79. http://www.proquest.com. (Accessed April 17, 2008).
Jessica Tsai 2008. Facebook's About-Face. Customer Relationship Management, January 1, 17-18. http://www.proquest.com (Accessed April 12, 2008).
Anton Vedder 1999. KDD: The challenge to individualism. Ethics and Information Technology 1, no. 4 (January 1): 275-281. http://www.proquest.com (Accessed April 15, 2008).
John Weckert 2001. Computer ethics: Future directions. Ethics and Information Technology 3, no. 2 (January 1): 93. http://www.proquest.com (Accessed April 16, 2008).
Lita van Wel, Lamber Royakkers. 2004. Ethical issues in web data mining. Ethics and Information Technology 6, no. 2 (July 1): 129-140. http://www.proquest.com (Accessed April 18, 2008).

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