Ownership is designed, not given: Human-AI fit and work sustainability in platform work

BackgroundHuman-AI collaboration is increasingly shaping platform-based work, yet workers may struggle to develop a sense of ownership over work produced under algorithmic management. Psychological ownership may provide an important mechanism for understanding sustainable human-AI work.ObjectiveThis study examines how human-AI value alignment and task complementarity influence psychological ownership and worker outcomes, and whether algorithmic transparency conditions these relationships.MethodsTwo empirical studies were conducted with platform-based gig workers, comprising 217 participants in Study 1 and 209 in Study 2. Study 1 examined psychological ownership as a mediator of the relationships between human-AI design features, eudaimonic well-being, and occupational resilience. Study 2 examined algorithmic transparency as a moderator and tested moderated mediation using bootstrapped PROCESS analyses.ResultsHuman-AI value alignment and task complementarity positively predicted psychological ownership, which, in turn, was associated with greater eudaimonic well-being and occupational resilience. Psychological ownership significantly mediated these relationships. Algorithmic transparency strengthened the effects of both design features on ownership and their indirect effects on well-being and resilience.ConclusionsPsychological ownership is a central mechanism through which human-AI job design contributes to sustainable work. Algorithmic transparency functions as an enabling condition that allows workers to verify alignment, contribution, and agency.