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Sarah Theres Völkel, Ramona Schödel, Daniel Buschek, Clemens Stachl, Jiew-Quay Au, Bernd Bischl, Markus Bühner, Heinrich Hussmann
Opportunities and Challenges of Utilizing Personality Traits for Personalization in HCI: Towards a shared perspective from HCI and Psychology
To appear in Augstein, Mirjam, Herder, Eelco, and Wörndl, Wolfgang: Personalized Human Computer Interaction (2019). DeGruyter Oldenbourg (bib)

This chapter discusses main opportunities and challenges of assessing and utilizing personality traits in personalized interactive systems and services. This unique perspective arises from our long-term collaboration on research projects involving three groups from Human-Computer Interaction (HCI), Psychology, and Statistics. Currently, personalization in HCI is often based on past user behavior, preferences, and interaction context. We argue that personality traits provide a promising additional source of information for personalization, which goes beyond context- and device-specific behavior and preferences. We first give an overview of the well-established Big Five personality trait model from Psychology. We then present previous findings on the influence of personality in HCI associated with the benefits and challenges of personalization. These findings include the preference for interactive systems, filtering of information to increase personal relevance, communication behavior, and the impact on trust and acceptance. Moreover, we present first approaches of personality-based recommender systems. We then identify several opportunities and use cases for personality-aware personalization: (1) personal communication between users, (2) recommendations upon first use, (3) persuasive technology, (4) trust and comfort in autonomous vehicles, and (5) empathic intelligent systems. Furthermore, we highlight main challenges: First, we point out technological challenges of personality computing. To benefit from personality-awareness, systems need to automatically assess the userâs personality. To create empathic intelligent agents (e.g., voice assistants), a consistent personality has to be synthesized. Second, personality-aware personalization raises questions about user concerns and views, particularly privacy and data control. Another challenge is acceptance and trust in personality-aware systems due to the sensitivity of the data. Moreover, the importance of an accurate mental model for userâs trust in a system was recently underlined by the right for explanations in the EUâs General Data Protection Regulation. Such considerations seem particularly relevant for systems that assess and utilize personality. Finally, we examine methodological requirements such as the need for large sample sizes and appropriate measurements. We conclude with a summary of opportunities and challenges of personality-aware personalization and discuss future research questions.