Privacy and Trust in Agent-Supported Distributed Learning

Privacy and Trust in Agent-Supported Distributed Learning

Larry Korba (National Research Council Canada, Canada), George Yee (National Research Council Canada, Canada), Yuefei Xu (National Research Council Canada, Canada), Song Ronggong (National Research Council Canada, Canada), Andrew S. Patrick (National Research Council Canada, Canada) and Khalil El-Khatib (National Research Council Canada, Canada)
DOI: 10.4018/978-1-59140-500-9.ch003
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The objective of this chapter is to explore the challenges, issues, and solutions associated with satisfying requirements for privacy and trust in agent-supported distributed learning (ADL). Accordingly, the first section will present the background, context, and challenges. The second section will delve into the requirements for privacy and trust as seen in legislation and standards. The third section will look at available technologies for satisfying these requirements. The fourth section will discuss an often-ignored area—that of building trustworthy user interfaces for distributed-learning systems. Finally, the chapter will end with conclusions and suggestions for further research.

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