Session chair: Federico Boschetti

Much work at the intersection of NLP and cultural analytics/computational social science is focused on creating new algorithmic measuring devices for constructs we see encoded in text (including agency, respect, and power, to name a few).  How does the paradigm shift of large language models change this? In this talk, I’ll discuss the role of LLMs (such as ChatGPT, GPT-4 and open alternatives) for research in cultural analytics, both raising issues about the use of closed models for scholarly inquiry and charting the opportunity that such models present.  The rise of large pre-trained language models has the potential to radically transform the space of cultural analytics by both reducing the need for large-scale training data for new tasks and lowering the technical barrier to entry, but need care in establishing the reliability of results.