Ownership is designed, not given: Human–AI fit and work sustainability in platform work
Diksha Kashyap, Mrinalini PandeyBackground
Human–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.
Objective
This study examines how human–AI value alignment and task complementarity influence psychological ownership and worker outcomes, and whether algorithmic transparency conditions these relationships.
Methods
Two 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.
Results
Human–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.
Conclusions
Psychological 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.