We used machine learning force fields to sample diffusive properties of Li 3 N above and below the superionic transition. From the calculated values of the heat capacity at constant volume, we identify the superionic transition temperature of Li 3 N to be T s ≈ 625 K. The normal and superionic regimes are found to fit two distinct Arrhenius relationships for self-diffusion coefficients and defect concentrations. The activation energies for selfdiffusion and Li vacancy formation decrease by a similar factor across the superionic phase transition, which suggests that the superionic transition may be mediated by a change in defect formation process. We suggest that defect-defect interactions may be responsible for lowering the formation energy at a critical defect concentration reached at T s .