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Process methods standardize the analysis and design process, and increase the coverage of the design space by considering as many questions and issues as possible upfront. The proponents of modeling frameworks attempt to proceed one step further, by systematizing factual knowledge about privacy in general structures that can be used for many types of applications. However, experimental evidence and our review of the literature suggest that the privacy design space may be too broad to be systematized in one single framework or model. If different methods address different parts of the design space, one option for attempting to increase analytic and design thoroughness would be to combine methods.

While this is indeed possible, we believe that a combined method would be even more difficult to validate and would not be adopted easily. An alternative to creating a large unified analysis process would be to document a modular toolbox of privacy heuristics that can be used upon need with a clear understanding of their limitations and contributions. This privacy toolbox should clearly indicate for what applications and social settings certain approaches are more effective, and what the designer can expect from them. We will return to this subject in Section 4.3.

4 Trends and Challenges in Privacy HCI Research

In the previous sections, we provided an overview of the research landscape of HCI as it relates to privacy. As a conclusion to this article, we outline several trends that are changing the privacy landscape, as well as major research challenges in the field. While the research subfields reviewed in Section 3 tackle a specific aspect of privacy in HCI, we focus here on five “grand challenges” that span several subfields:

Developing more effective and efficient ways for end-users to manage their privacy.

Gaining a deeper understanding of people’s attitudes and behaviors towards privacy

Developing a “Privacy Toolbox”

Improving organizational management of personal data

Converging privacy research with technological adoption models

Below, we outline each of these trends, indicate where we see current research headed, and what are the challenges facing researchers and practitioners.

4.1 Better Ways of Helping End-Users Manage Their Personal Privacy

It is becoming increasingly difficult to manage personal privacy as information and communication technologies become pervasive. Personal information is fragmented across a number of devices, applications, web sites, and organizations, each with different user interfaces, notifications, and management policies. We argue that we need new approaches for alleviating the burden of managing user’s personal privacy.

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