{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T19:29:36Z","timestamp":1773170976549,"version":"3.50.1"},"reference-count":0,"publisher":"Project MUSE","issue":"4","license":[{"start":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T00:00:00Z","timestamp":1756252800000},"content-version":"vor","delay-in-days":118,"URL":"https:\/\/www.crossref.org\/license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["lib"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:p xml:lang=\"en\"> Abstract: The library and information science (LIS) ecosystem encompasses an interconnected network of stakeholders that includes students, faculty, administrators, scholars, practicing library and information professionals, and the communities that they serve. Threats or opportunities that occur in any part of the ecosystem may impact its whole. This includes generative artificial intelligence (AI), which presents new challenges, threats, and opportunities for interacting with and evaluating information. Because it is still developing, we do not yet know the outcome of this technological shift, though we are able to assess how its early developments have impacted LIS stakeholders and how they might best respond. One significant area of concern about generative AI's impact on the LIS ecosystem is the problem of AI-generated scholarship and its effect on the legitimacy of evidence-based science. In this critical essay, we explore the history of fraudulent scientific scholarship and how AI accelerates the problem, the specific threats that LIS stakeholders may face as a result of generative AI, and the opportunities that AI presents to the LIS ecosystem. We end with a call for LIS stakeholders to rethink how the changing values of academic scholarship in light of generative AI might impact their prevailing practices.<\/jats:p>","DOI":"10.1353\/lib.2025.a968527","type":"journal-article","created":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T09:22:46Z","timestamp":1756286566000},"page":"538-552","source":"Crossref","is-referenced-by-count":2,"title":["The Impact of Generative AI on the LIS Ecosystem: Threats and Opportunities"],"prefix":"10.1353","volume":"73","author":[{"given":"Amanda S.","family":"Hovious","sequence":"first","affiliation":[]},{"given":"Andrew J. M.","family":"Smith","sequence":"additional","affiliation":[]}],"member":"147","container-title":["Library Trends"],"original-title":[],"language":"en","deposited":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T09:22:48Z","timestamp":1756286568000},"score":1,"resource":{"primary":{"URL":"https:\/\/muse.jhu.edu\/article\/968527"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":0,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,5]]}},"URL":"https:\/\/doi.org\/10.1353\/lib.2025.a968527","relation":{},"ISSN":["1559-0682"],"issn-type":[{"value":"1559-0682","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5]]}}}