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PRODID;X-RICAL-TZSOURCE=TZINFO:-//com.denhaven2/NONSGML ri_cal gem//EN
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VERSION:2.0
BEGIN:VEVENT
DTEND;VALUE=DATE-TIME:20260516T160500Z
DTSTART;VALUE=DATE-TIME:20260516T152000Z
DTSTAMP;VALUE=DATE-TIME:20260420T132933Z
UID:a6c57ccb-6ba1-4eed-87dc-9d5b0850c600@talks.stuts.de
DESCRIPTION:Collecting data from human participants is slow and costly. R
 ecruitment is difficult\, participants are often un- or underpaid\, and 
 results are affected by biases such as the Observer’s Paradox and the Ha
 wthorne Effect. In addition\, many sample groups are WEIRD (from Western
 \, educated\, industrialized\, rich\, and democratic societies). So can 
 Artificial Intelligence (AI) simulate human participants? To test this\,
  I generated a sample of 600 AI participants using the LLaMA 3.1 model (
 8B)\, approximating Germany’s population based on 2024 federal statistic
 s. Their questionnaire responses were compared to data from human partic
 ipants. No prior computational knowledge is required\, everyone interest
 ed in discussing the implications of AI in linguistic research is warmly
  invited! 
URL:programm.stuts79.de/events/1516.html
SUMMARY:Can AI-Generated Participants Replace Humans in Linguistic Resear
 ch?
ORGANIZER:stuts79
LOCATION:stuts79 - DOR 24 1.501
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