Resizing an image can be seen as a subsampling operation, which could need an anti-alasing filter to prevent aliasing effects (if the image frequencies start to overlap due to the sampling).
This Wikipedia article 18 gives you a high-level overview for a couple of interpolation techniques.
I haven’t seen a lot of thought in the machine learning area regarding aliasing effects in images and would guess that for a lot of use cases the default of image processing libraries seems to work.