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AI Research Assistants

Trick or Treat? Emerging AI research tools are disrupting information discovery.

Sign up for the beta

JSTOR invites you to explore an interactive research tool in beta. Developed in collaboration with our community, this tool employs generative AI and other technologies to empower people to deepen and expand their research with JSTOR’s trusted corpus.

JSTOR stewards content from thousands of publishers, libraries, and museums. We do not sell any items available in JSTOR to large language model (LLM) providers. Limited content sent to selected LLM providers to support user queries is stored temporarily by LLMs (if at all) and not used to train models. For more details, please see our FAQ.

Sign up for the beta

Do you have questions, comments, or concerns? We want to hear from you! Please email support@jstor.org to share your feedback.

Current Functionality

JSTOR’s generative AI tool is designed to provide users with a range of powerful functionalities for interacting with the full text of a single item, including:

  1. Custom summaries: The tool can provide a summary directly related to the user’s search query, as well as a general summary of the document, allowing users to quickly grasp the content and relevance of academic texts.
  2. Recommended topics: The tool can recommend related topics based on the document’s content, enabling users to explore additional research paths and deepen their understanding of the subject matter.
  3. Related content: The tool can display documents that are conceptually similar to the current text being viewed, helping users to find additional relevant resources quickly and efficiently.
  4. Question and answer (Q&A): Users can ask specific questions about the document, and the tool generates answers using the document’s content to ensure accuracy and relevance. This feature is particularly useful for users seeking detailed information on specific aspects of a document, including topics and concepts.

JSTOR Beta in action