AI coding assistants are generating substantial portions of code, fundamentally challenging traditional notions of authorship and ownership in software development. We conducted a within-subjects experiment examining three AI coding assistant autonomy conditions—High (AI generates complete code), Medium (AI provides substantial suggestions), and Low (AI offers minimal assistance). We found that AI autonomy systematically reshaped developers’ psychological relationships with code through distinct patterns across ownership dimensions. Possession decreased continuously with each increase in AI contribution. Identity remained similar under Low and Medium autonomy but decreased substantially under High autonomy. Responsibility decreased from Low to Medium and High autonomy, though developers maintained some sense of responsibility across all conditions. Attribution patterns revealed symmetric bidirectional shifts where ownership and responsibility attribution moved from predominantly Human-centered under Low autonomy through balanced uncertainty at Medium autonomy to predominantly AI-centered under High autonomy. Despite these internal psychological shifts, professional disclosure practices showed striking stability. While developers became less comfortable claiming ownership to technical reviewers as AI contribution increased, their willingness to describe creation processes transparently and accept accountability for production systems remained consistent across all conditions. These findings illuminate how AI autonomy fundamentally restructures the psychological landscape of human-AI co-creation while developers preserve core professional obligations for transparency and accountability.

Psychological ownership over virtual and physical spaces in augmented reality can lead to tensions between collaborators, yet, there is still a significant challenge in understanding how psychological ownership manifests in shared AR and what that might mean for the inclusion of collaborative interaction mechanisms. Through an experimental instruction task with a teleAR system, we interviewed 16 participant pairs on their perceptions of ownership of virtual and physical spaces and how they thought their perceptions impacted their interaction within those spaces. Our findings indicate (1) how AR introduces new ideas around behavioral norms in spaces that are layered and (2) that the nature of the task itself, in this case one of instruction where collaborators have different levels of knowledge and the local worker is reliant on the remote expert, significantly affects the perceptions of ownership and therefore behavior norms.

This study investigates how annotation control influences group processes in teleAR and examines the mediating role of psychological ownership. Through an experiment comparing three ego-centrically defined annotation control forms - We control (both annotate), I control (one annotates), and They control (partner annotates) - we found that ego-centric perceptions of annotation control significantly shaped collaborative dynamics. We control consistently showed advantages across all measured clusters of group processes, showing significant improvements over both I control and They control. Additionally, our analysis revealed that Collective Psychological Ownership (CPO) served as a crucial mediator between annotation control and group processes, particularly in comparisons between We control and They control. Further examination of the five psychological ownership dimensions revealed limited but notable mediation effects, with the Possession and Control dimensions showing positive indirect effects on Human development and Shared practices when comparing I control with They control. These findings show how annotation control forms influence distributed collaboration and highlight the importance of considering psychological ownership in improving group processes.

The introduction of Augmented Reality (AR) Head Mounted Displays (HMDs) in collaboration between remote and local workers, introduces new challenges given that camera views are now mobile. We introduce HoloMentor, an AR HMD-based collaborative system designed for remote instruction over live mobile views during physical tasks. Through Actionport, we provide a world-stabilized area where remote helpers can dynamically place a pointer and annotations on the physical environment. Through Actionpad, we provide an indirect input mechanism with an absolute position to the Actionport. We show how these innovations worked for participants engaged in a remote instructional task and how they supported effective and efficient communication. Finally, we provide the next steps for addressing AR on mobile views for remote instruction.