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How Should AI Systems Talk to Users when Collecting their Personal Information? Efects of Role Framing and Self-Referencing on Human-AI InteractionMengqi Liao · 2021AI systems collect our personal information in order to provide per­ sonalized services, raising privacy concerns and making users leery. As a result, systems have begun emphasizing overt over covert collection of information by directly asking users. This poses an important question for ethical interaction design, which is ded­ icated to improving user experience while promoting informed decision-making: Should the interface tout the benefts of infor­ mation disclosure and frame itself as a help-provider? Or, should it appear as a help-seeker? We decided to fnd out by creating a mockup of a news recommendation system called Mindz and conducting an online user study (N=293) with the following four variations: AI system as help seeker vs. help provider vs. both vs. neither. Data showed that even though all participants received the same recommendations, power users tended to trust a help-seeking Mindz more whereas non-power users favored one that is both help-seeker and help-provider. CCS CONCEPTS • Human-centered computing → Human computer interaction (HCI); Empirical studies in HCI.

UX of AI & PersonalizationResearch Papers

“This App Would Like to Use Your Current Location to Better Serve You”: Importance of User Assent and System Transparency in Personalized Mobile ServicesTsai-Wei Chen · 2018Modern mobile apps aim to provide personalized services without appearing intrusive. A common strategy is to let the user initiate the service request (e.g., “click here to receive coupons for your favorite products”), a practice known as “overt personalization.” Another strategy is to assuage users’ privacy concerns by being transparent about how their data would be collected, utilized and stored. To test these two strategies, we conducted a 2 (Personalization: Overt vs. Covert) x 2 (Transparency: High vs. Low) factorial experiment, with a fifth control condition. Participants (N=302) interacted with GreenByMe, a prototype of an eco-friendly mobile application. Data show that overt personalization affects perceived control. Significant three-way interactions between power usage, perceived overt personalization and perceived information transparency was seen on perceived ease of use, trust in the app, user engagement and behavioral intention to use the app in the future. In addition, results reveal that perceived information transparency also promotes trust, which is negatively linked with privacy concerns and positively correlated with user engagement and product involvement. Author Keywords Location-Aware Computing; Contextual Computing; Usability Study; User Experience Design; Privacy ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous.

UX of AI & PersonalizationResearch Papers