Not Quite 'Ask a Librarian': AI on the Nature, Value, and Future of LIS
This study provides an incremental demonstration of AI language models for generating ideas in LIS, relevant to researchers and practitioners in the field.
The authors used GPT-3 to answer questions about library and information science (LIS), generating responses that varied from clichés to insightful perspectives, demonstrating the model's current capabilities in this domain.
AI language models trained on Web data generate prose that reflects human knowledge and public sentiments, but can also contain novel insights and predictions. We asked the world's best language model, GPT-3, fifteen difficult questions about the nature, value, and future of library and information science (LIS), topics that receive perennial attention from LIS scholars. We present highlights from its 45 different responses, which range from platitudes and caricatures to interesting perspectives and worrisome visions of the future, thus providing an LIS-tailored demonstration of the current performance of AI language models. We also reflect on the viability of using AI to forecast or generate research ideas in this way today. Finally, we have shared the full response log online for readers to consider and evaluate for themselves.