I also disagree with the conclusion, but for a different reason. I think it's unlikely that the word embeddings were just lower quality. That should result in noise, not bias.

I that there is a real statistical pattern in the training data that names associated with certain ethnicities are more likely to appear close to words with negative sentiment. I just don't think this necessarily means that the news is racist. I think more analysis is needed to see where this pattern comes from.

However, if it is true that the news is biased and racist in a quantifiable way, that would be a bigger problem than biased word vectors. I would genuinely be interested in seeing that type of analysis.