Blog Assignment 4

        The article, Privacy-Enhanced Personalization, written by Alfred Kobsa, explains how both web users and vendors value personalized content, but how certain issues make it difficult to please both parties. There are many perceived privacy threats to users, including unsolicited marketing, price discrimination, unauthorized access to accounts, and government surveillance. Around the turn of the century, it was decided that in order for there to be a balance between privacy and personalization, there would have to be some sort of trade-off between them; with an increase of personalization, there would require a decrease of privacy and vice versa. But now the interdisciplinary field of privacy-enhanced personalization strives for the best possible personalization within privacy boundaries.
        One privacy theory states that privacy-related behaviors result from a cost-benefit analysis, where potential risks of disclosing personal information are weighed against potential benefits. Different factors, such as age, education, and income, have been shown to affect the degree of this privacy concern. As far as disclosing information goes, users will provide certain information (demographics, lifestyle, hobbies, etc.) without hesitation, but will not willingly give other information, such as credit card details, social security numbers, and financial or contact information. Web users believe they should have the right to know how their personal information is being used and be able to have a certain amount of control over it; this is why trust is very important between user and website. Five elements result in a website having trust: 1) positive past experience, 2) design and operation of website, 3) reputation of website operator, 4) presence of a privacy statement, and 5) presence of a privacy seal.
        Many privacy laws and guidelines have been created to deal with this privacy issue online. Users have embraced pseudonymous user models as well as principles of fair information practices. Another approach is personalizing systems so that users’ data is located on the client side instead of the server side. Other techniques have been proposed to help protect the privacy of users of collaborative-filtering based recommender systems. Although no “silver bullet” exists at this time regarding this issue of privacy, many small enhancements are now available to test out on users.
        This article is very perplexing. I had never thought very deeply about online privacy before reading this. I now know that it is difficult on both the user and the vendor to find a middle ground on privacy issues. Hopefully there will be a solution to this problem in the near future so that both users and vendors can benefit from it. My question, which we briefly touched on in class, is whether the age of online users has an impact on how much information they are willing to give away. I would be interested to see if teenagers, nowadays, will give information more readily than, say, college-aged people.