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PRODID:-//University of Iceland//AI Centre//EN
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UID:85ce4d9a-f770-4784-9b51-6edc2e5ceb9f@ai.hi.is
DTSTAMP:20260923T173439Z
DTSTART:20260929T090000Z
DTEND:20260929T100000Z
SUMMARY:Who wrote the abstract? Analysis of AI use in theses from Skemman
DESCRIPTION:Since ChatGPT was released in late 2022\, niversities have been
  asking what effect such tools have on thesis writing. Most of the evidenc
 e\, however\, comes from surveys or from detection tools built for English
 . This talk presents a study of the abstracts of final theses in Skemman\,
  Iceland's open thesis repository. The data cover 22\,240 theses from 2019
  to 2026\, with roughly 19\,000 abstracts in Icelandic and 11\,000 in Engl
 ish. General-purpose detection tools have not been developed specifically 
 for Icelandic\, so we trained our own detection models. They are based on 
 Icelandic and multilingual language models that learn to distinguish betwe
 en abstracts written before the ChatGPT era and nearly 2\,000 abstracts co
 mposed by 36 language models from the text of the theses themselves. Thres
 holds were set so that only 1% of the pre-ChatGPT abstracts are flagged. A
 t those thresholds\, the proportion of flagged Icelandic abstracts rises f
 rom 2.4% in 2023 to 42.2% so far in 2026. For English\, it rises from 7.6%
  to 62.1%. The rise appears across institutions and degree levels\, and sc
 hools differ considerably. The commercial detector Pangram catches almost 
 all generated English abstracts at its default setting\, but only 12% of t
 he Icelandic ones\, which can be remedied by modifying the flagging thresh
 old. The results point to a real shift in how students write. They say lit
 tle about individual students since they are not a proof of AI usage.\n\nh
 ttps://ai.hi.is/is/events/colloquium-in-statistics-and-ai-23/
LOCATION:Íslensk erfðagreining\, Tjarnarsalur
URL:https://ai.hi.is/is/events/colloquium-in-statistics-and-ai-23/
STATUS:CONFIRMED
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