To summarize, I think these are our options:

1. Change the behavior of np.anyarray() to check for an __anyarray__() protocol. Change np.matrix.__anyarray__() to return a base numpy array (this is a minor backwards compatibility break, but probably for the best). Start issuing a FutureWarning for any MaskedArray operations that violate Liskov and add a skipna argument that in the future will default to skipna=False.

2. Introduce a new coercion function, e.g., np.duckarray(). This is the easiest option because we don't need to cleanup NumPy's existing ndarray subclasses.

My vote is still for 1. I don’t have an issue for PyData/Sparse depending on recent-ish NumPy versions — It’ll need a lot of the recent protocols anyway, although I could be convinced otherwise if major package devs (scikits, SciPy, Dask) were to weigh in and say they’ll jump on it (which seems unlikely given SciPy’s policy to support old NumPy versions).