Exactly. Without models being truly open source, (training data, training procedures, alignment etc.), there is no way for auditors to assess, for example, whether a model was trained on data exhibiting certain forms of selection bias (anything from training data or alignment being overly biased towards Western culture, controversial political or moral viewpoints, particular religions, gender stereotypes, even racism) which might lead to dangerous outcomes later on, whether by contamination of derived models or during inference.

> if OSI defines black boxes as "open source", they open a loophole that will be exploited to harm people without being held accountable

The OSI’s definition matches the legal definition in the EU and California (and common use). If the OSI says open data only, it will just be ignored. (If people are upset about the current use, they can make the free vs. open distinction we do in software to keep the pedantic definition contained.)