text: •**Breadth, Diversity, and Mitigating Bias:**Books can serve a critical role in ensuring AI 
  models are inclusive of a broad range of topics and categories that may be under- 
  represented in other content. For all that the Internet has generated an explosion in 
  human creativity and information sharing, it generally represents only a few decades 
  of information and a small portion of the world’s creative population. A books 
  dataset, by comparison, is capable of representing centuries of human knowledge. As 
  a result such a dataset can help ensure AI systems behavior is based on centuries of 
  historical information from modern books. It can help ensure broad geographic and 
  linguistic diversity. What’s more, the greater breadth and diversity of high-quality 
  content help mitigate challenges around bias and misinformation. Using a more 
  diverse pool of training data can help support the production of a model and outputs 
  of the model that are more representative of that diversity. Books can be useful in 
  evaluation datasets to test existing models for memorization capabilities, which can 
  help prevent unintended reproduction of existing works. Of course, this is all 
  contingent on actual composition of the corpus; in order to have the beneﬁts 
  described, the books would need to be curated and included with characteristics like 
  time, geographic and linguistic diversity. 