The whole paper doesn't go beyond surface-level analysis. The main point is that language models reflect the same biases as its training data. Very little of it is technical. Most of it is about examples of how language models aren't as politically correct as the authors want it to be (e.g. calling female doctors "female doctors" when it's not relevant to the context). It's a legitimate concern, but anyone who remembered Microsoft Tay would know that.