EHT team tested for some biases, but did not test for the most significant bias.
Because they try to make an image of a black hole, their strongest bias is to see a black hole in anything.
So they should have tested if their final implementation of "imaging method" does NOT see black hole when incoming sparse data does not contain the black hole.
Unfortunately, there is no such test in the presentation.
EHT team tested that "imaging method" that was trained for recognizing a disk (without a hole) - is still able to recognize black hole. See it at [31:55]
But they did not test the reverse: train an imaging method for recognizing black hole, but then feed sparse disk data to that imaging method. Would it be able to see disk or still would see a black hole?
How about trying to feed sparse data of 2 bright stars. Would this imaging method that was trained to recognize black holes -- still be able to see these 2 stars?
Unfortunately, there was no testing like that ... or worse -- they did such testing, but then discarded the results, because it does not impress the public and financial sponsors.
They spent a lot of effort ensuring that their imaging methods were objective and free of human bias.