The increasing role of machine learning in the construction of cultural heritage and humanities datasets necessitates critical examination of the myriad biases introduced by machines, algorithms, and the humans who build and deploy them. From image classification to OCR, the effects of decisions ostensibly made by machines compound through the…[Read more]