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How to approximate users’ values while preserving privacy: experiences with using attitudes towards work tasks as proxies for personal value elicitation

Abstract

Software users have different sets of personal values, such as benevolence, self-direction, and tradition. Among other factors, these personal values influence users’ emotions, preferences, motivations, and ways of performing tasks—and hence, information needs. Studies of user acceptance indicate that personal traits like values and related soft issues are important for the user’s approval of software. If a user’s dominant personal value were known, software could automatically show an interface variant which offers information and functionality that best matches his or her dominant value. A user’s dominant personal value is the one that most strongly influences his or her attitudes and behaviors. However, existing methods for measuring a user’s values are work intensive and/or interfere with the user’s privacy needs. If interface tailoring for very large groups of users is planned, value approximation has to be achieved on a large scale to assign individualized software to all users of the software. Our work focuses on approximating the dominant values of a user with less effort and less impact on privacy. Instead of probing for a user’s values directly, we explore the potential of approximating these values based on the user’s preferences for key tasks. Producing tailored versions of software is a separate topic not in the focus here. In this paper we rather describe a method to identify user values from task preferences and an empirical study of applying parts of this method. We are proposing the method in this paper for the first time except for a preliminary version orally presented at a workshop. The method consists of a research process and an application process. In the research process a researcher has to identify key tasks occurring in a context under investigation which have a relationship to personal values. These key tasks can be used in the application process to approximate the dominant values of new users in a similar context. In this empirical study we show that the research process of our method allows us to determine key tasks which approximate values in the shared context of nursing. The majority of the nurses were found to have one of the three following dominant values: benevolence, self-direction, or hedonism. Data confirmed common expectations: that nurses with the value of benevolence, when compared to all other nurses, had a higher preference for tasks which helped people immediately or improved their circumstances of the treatment. In relation to all other nurses, participants with self-direction disliked tasks which affected their personal freedom, and users with hedonism had a lower preference for tasks which involved physical work and preferred tasks which promised gratification. Our findings advance measurement of personal values in large user groups by asking questions with less privacy concern. However, the method requires substantial efforts during the initial research process to prepare such measurements. Future work includes replicating our method in other contexts and identifying value-dependent tasks for users with other values than the three values our empirical study mainly focused on.

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Acknowledgments

We would like to acknowledge the funding of the Deutsche Forschungsgemeinschaft (DFG), grants PA 1387/3-1 and WE 2467/7-1, and the help of the participating nurses, nurse managers, the Employee Committee, the Director of Nursing at the Heidelberg University, Doris Keidel-Müller and Steffi Schiemang.

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Correspondence to Sven H. Koch.

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Koch, S.H., Proynova, R., Paech, B. et al. How to approximate users’ values while preserving privacy: experiences with using attitudes towards work tasks as proxies for personal value elicitation. Ethics Inf Technol 15, 45–61 (2013). https://doi.org/10.1007/s10676-012-9309-7

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Keywords

  • Personal values
  • Value elicitation
  • Value approximation
  • Privacy
  • Software tailoring
  • Individualized interface
  • Value-sensitive design