There is a categorical difference between "a [specifically designed] image that can be construed as a duck or a rabbit" and "a human can regularly mis-categorize random pictures of ducks as rabbits if a weird filter is overlayed". The first is well-known and fun and trite -- the second is unheard of and probably impossible for humans, yet provably possible for trained computers.
I'd imagine GP was referring to "humans perceive straight lines to be curved when certain shapes are overlayed", or "humans perceive shapes of the same color to be different colors when filters are applied" sorts of optical illusions.
There are plenty of those, and I personally I think they're probably analogous to how adversarial filters fool AI classifiers.
It's really easy to cause humans to misclassify all kinds of images as containing faces ;). Humans also regularly misclassify random noise as words. You can even suggest which words we hear by telling us what the noise is supposed to be.
The point outlined is that we don't know enough about how we identify objects to discard a simple adversarial attack; probably not a filter-based but maybe something else.