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Shaping responsible AI in research: new Against the Grain article co-authored by JSTOR’s Beth LaPensee

Дата публикации: 16-01-2026 15:00:00

An article co-authored by Beth LaPensee, Principal Product Manager at JSTOR, has been published in the December issue of Against the Grain. Written with Anne Grant of Clemson University Libraries, the piece examines how libraries and nonprofit research platforms can work together to design and implement embedded AI tools that support ethical, transparent, and inquiry-driven research and instruction.
The post Shaping responsible AI in research: new <i>Against the Grain</i> article co-authored by JSTOR’s Beth LaPensee appeared first on About JSTOR.


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An article co-authored by Beth LaPensee, Director of Product Management, JSTOR, has been published in the December issue of Against the Grain. Titled “Embedded AI in Practice: How Libraries and Platforms Shape Research and Instruction Together,” the piece explores how libraries and nonprofit research platforms can collaboratively develop and integrate AI tools that support ethical, transparent, and inquiry-driven scholarship.

Co-authored with Anne Grant of Clemson University Libraries, the article draws on JSTOR’s experience developing its embedded AI research tool and Clemson’s role as an early instructional beta partner, offering a rare joint perspective from both platform and library practitioners. 

Key takeaways:

  • Responsible AI begins with transparency: JSTOR’s embedded AI tool anchors every response in full-text scholarly sources, with inline citations that allow users to trace insights directly back to the text.
  • Libraries and platforms as partners: Close collaboration between JSTOR and Clemson University Libraries shaped both tool design and classroom integration, demonstrating the value of co-creation in building AI literacy.
  • Supporting inquiry, not replacing it: Early use shows the tool helps students and researchers navigate dense texts, ask better questions, and engage more deeply—without outsourcing intellectual work.
  • Choice and institutional readiness matter: Institutions can decide whether and when to enable the tool, addressing ethical concerns around consent, trust, and local adoption.
  • New possibilities for discovery: Embedded AI opens paths for micro-discovery, semantic exploration, and more dynamic engagement with scholarly materials.

The article is available in full text to Against the Grain subscribers only.

Read more via the publisher.

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