Description:
Web personalization has demonstrated to be advantageous for both online customers and vendors. However, its benefits are counteracted by privacy concerns. Personalized systems need to take these concerns into account, as well as privacy laws and industry self-regulations that may be in effect. We present two research endeavors in this framework of 'privacy-enhanced personalization': Effective disclosure of privacy practices. Current 'privacy policies' are ineffective in allaying privacy concerns. They are written in a lengthy and legalistic manner, and in effect, hardly ever read by Internet shoppers. We tested a different, HCI-oriented approach, namely web design templates in which every entry field for personal data is accompanied by a clear and concise explanation of how the retailer will deal with the respective piece of data, and what benefits customers can expect from sharing this personal information. We compared users of an online book retail website that used a traditional privacy disclosure with users of the same website after it was redesigned based on our templates. Subjects in the second group not only rated its privacy practices significantly higher, answered 8% more questions and gave 20% more answers, but also rated the perceived benefit resulting from data disclosure significantly higher and bought books 33% more often. Privacy concerns, privacy laws and self-regulation not only affect the personal data that can be collected, but also frequently-employed personalization methods. Our research aims at maximizing the personalization benefits, while at the same time satisfying the privacy constraints that prevail during a user session. We describe a pilot experiment with an existing user modeling server and a software-architecture based development environment.
Speaker(s):
Dr. Alfred Kobsa, professor, Donald Bren School of Information and Computer Sciences, University of California, Irvine
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