IMHO she is saying it’s reasonable to believe that social and systemic issues have an impact on creating ML models (as the teams designing, building, and deploying said models are members of society) in ways in addition to the data sets.

I don’t know what the right answer is but plenty of institutions come up with ways they attempt to deal with systemic biases. For example, blind auditions for positions in orchestras (you only hear the person auditioning, you can’t see them). Used to not be a thing. Now it is.

Point being that when people are motivated they are able to come up with stuff.