Matthias Hoppe

Fiona Draxler, Anna Werner, Florian Lehmann et al.

Human-AI interaction in text production increases complexity in authorship. In two empirical studies (n1 = 30 & n2 = 96), we investigate authorship and ownership in human-AI collaboration for personalized language generation. We show an AI Ghostwriter Effect: Users do not consider themselves the owners and authors of AI-generated text but refrain from publicly declaring AI authorship. Personalization of AI-generated texts did not impact the AI Ghostwriter Effect, and higher levels of participants' influence on texts increased their sense of ownership. Participants were more likely to attribute ownership to supposedly human ghostwriters than AI ghostwriters, resulting in a higher ownership-authorship discrepancy for human ghostwriters. Rationalizations for authorship in AI ghostwriters and human ghostwriters were similar. We discuss how our findings relate to psychological ownership and human-AI interaction to lay the foundations for adapting authorship frameworks and user interfaces in AI in text-generation tasks.

Xiaru Meng, Yulan Ju, Yan He et al.

Live cultural experiences like concerts generate shared physiological arousal among audience members, a collective resonance that contributes to their emotional power. Recreating such experiences in virtual reality therefore requires not just audiovisual fidelity, but reproduction of this physiological dimension. Yet current VR evaluation methods rely on post-hoc self-reports that interrupt immersion and cannot capture moment-to-moment arousal dynamics. We propose cross-temporal physiological synchrony as an unobtrusive methodology for evaluating VR cultural recreations: measuring how closely a VR participant's arousal patterns align with those of the original live audience. In a two-phase study, we recorded electrodermal activity from 40 live concert attendees, then created three VR recreations with varying abstraction levels (realistic 360-degree video, mixed video-plus-visualization, and fully abstract physiological representations) and measured synchrony with 22 laboratory participants using Dynamic Time Warping. Contrary to assumptions favoring realism, abstract visualizations achieved the strongest synchrony with live audiences. During musical climaxes, the abstract condition maintained correlation while realistic video showed none. These findings suggest that abstract physiological representations may be more effective than realistic footage for evoking authentic collective engagement in VR cultural recreations.

Radiah Rivu, Ville Mäkelä, Sarah Prange et al.

We investigate the opportunities and challenges of running virtual reality (VR) studies remotely. Today, many consumers own head-mounted displays (HMDs), allowing them to participate in scientific studies from their homes using their own equipment. Researchers can benefit from this approach by being able to reach a more diverse study population and to conduct research at times when it is difficult to get people into the lab (cf. the COVID pandemic). We first conducted an online survey (N=227), assessing HMD owners' demographics, their VR setups, and their attitudes towards remote participation. We then identified different approaches to running remote studies and conducted two case studies for an in-depth understanding. We synthesize our findings into a framework for remote VR studies, discuss the strengths and weaknesses of the different approaches, and derive best practices. Our work is valuable for HCI researchers conducting VR studies outside labs.

Matthias Hoppe, Yannick Weiß, Marinus Burger et al.

More and more off-the-shelf drones provide frameworks that enable the programming of flight paths. These frameworks provide vendor-dependent programming and communication interfaces that are intended for flight path definitions. However, they are often limited to outdoor and GPS-based use only. A key disadvantage of such a solution is that they are complicated to use and require readjustments when changing the drone model. This is time-consuming since it requires redefining the flight path for the new framework. This workshop paper proposes additional features for DronOS, a community-driven framework that enables model-independent automatisation and programming of drones. We enhanced DronOS to include additional functions to account for the specific design constraints in human-drone-interaction. This paper provides a starting point for discussing the requirements involved in designing a drone system with other researchers within the human-drone interaction community. We envision DronOS as a community-driven framework that can be applied to generic drone models, hence enabling the automatisation for any commercially available drone. Our goal is to build DronOS as a software tool that can be easily used by researchers and practitioners to prototype novel drone-based systems.