Computational methods can help the humanities by making massive cultural heritage collections more explorable and analyzable. Machine learning and statistical methods provide an opportunity to view collections from alien, defamiliarized perspectives that can call into question the boundaries between established categories. But the converse is also true: the humanities have much to offer machine learning. The use of computational methods within humanities scholarship often tests and expands the affordances of these methods. The complexities and idiosyncrasies of humanities collections can improve our understanding of what models learn and how we might direct what they learn….
A Symbiotic Future For Machine Learning and the Humanities (feat. Laure Thompson)
