Researchers, policymakers, and developers of artificial intelligence (AI) are actively collaborating to establish trustworthy AI standards that align with broader societal values, particularly in the context of large language models (LLMs). However, the critical discourse on bridging the vast knowledge gap between experts who shape and implement standards for LLMs and users whose values are at stake remains largely unaddressed. Taking a "bottom-up" perspective and using a mixed-method approach, we first conducted interviews (N = 12) to engage with users' perceptions of normative standards in the context of LLMs. We thereby identified 68 specific criteria that users' consider when evaluating whether their values are fulfilled. Second, we conducted an online survey (N = 379) to further investigate how users prioritize these standards and the identified criteria in conversational LLM-based applications. Our findings reveal opportunities for strategic communication measures, the importance of transparent governance mechanisms and the necessity of non-technical complements to technical solutions for bridging the knowledge gap. We discuss actionable steps to effectively communicate trustworthy AI standards.

Measuring the subjective experience of digital game players is essential to player experience research. Recently, the Player Experience Inventory (PXI) was developed, which assesses both functional and psychosocial consequences of digital gameplay. We present a pre-registered independent online study with a large sample to provide additional evidence of psychometric quality for the PXI. Responses from 1518 participants were collected, rating a recent or memorable experience playing a digital game using the PXI and related measures. While our results from standard psychometric reliability and validity analyses generally favored the PXI, we also identified challenges with the immersion construct. Further, we find a ten-factor model, or alternatively, an 11-factor should enjoyment be measured, to fit our collected data best. In sum, the PXI is a valuable tool to measure a variety of constructs central to player experience.

Virtual reality (VR) applications are increasingly permeating our lives. The immersion provided by VR enables novel interactions with data that would be impossible in conventional environments. Especially regarding multimedia data, VR could overcome existing limitations when browsing videos to find specific scenes. This paper introduces a virtual multimedia drawer, tailored to VR environments, to enable novel ways to interact with videos. A within-subjects design experiment (N=24) was conducted to evaluate the multimedia drawer on user experience, efficiency, and effectiveness. Results show that the multimedia drawer, while taking slightly longer to locate a particular scene within a video for certain types of tasks (i.e., sequence tasks), provides statistically significantly higher levels of enjoyment, novelty, and stimulation and is preferred over conventional timeline-based approaches. Implications of quantitative and qualitative results regarding the design and features of the multimedia drawer as a video browsing method in VR are critically discussed.