Possible correction: this does not appear to be an example of machine bias. It's also important to keep in mind that there can be other sources (such as brittleness) of bad ML outcomes than bias.

When I do an exact search for the Justification Sentence with Google, what best matches is a quote by Rajiv Gandhi. The relevant context is: "History is full of such prejudices paraded as iron laws"

His stance is clearly opposite to what the extracted text implies. This is a common problem with knowledge extraction and one I've run into often myself.

Extracting just a phrase, or utterances of a generative model cannot be trusted because the original meaning can be opposite to what is presented. Existing models fail to preserve nuance imparted by context, struggle with negation, lack deep understanding and an ability to truly reason.