AI and other advanced technologies on JSTOR: What we’re learning from early usage, real-world applications, and user feedback
We are actively learning from usage, real-world applications, and user feedback in a limited beta environment to build out capabilities thoughtfully, intentionally, incrementally, and most importantly–based on evidence. This blog post delves into the rationale, construction, and current functionality of JSTOR’s beta generative AI tool, as well as the key themes and insights that have emerged from our analysis of its usage.