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UID:pretalx-sips2025-budapest-XHEHBP@pretalx.com
DTSTART;TZID=CET:20250625T145200
DTEND;TZID=CET:20250625T150000
DESCRIPTION:Artificial intelligence systems\, particularly in social media\
 , are under increasing scrutiny (Reviglio & Agosti\, 2020). TikTok’s rec
 ommendation system\, renowned for its high degree of personalization\, exe
 mplifies this trend (Bhandari & Bimo\, 2022). This lightning talk will pre
 sent insights from an ongoing field experiment pre-registered involving 70
 0 TikTok users. Participants were divided into two groups: a control group
  using TikTok as normal\, and an experimental group that disabled personal
 ization in their news feed for two weeks. Pre- and post-experiment measure
 s include mental health\, political polarization\, and problematic TikTok 
 use. By sharing our design\, early findings\, and challenges\, we seek fee
 dback from the scientific community to refine our approach. This talk also
  aims to spark discussion on innovative ways psychological researchers can
  study Human–AI Interaction\, particularly in the context of highly adap
 tive systems like TikTok.
DTSTAMP:20260514T180910Z
LOCATION:Second floor 214
SUMMARY:LT15: Lessons Learned from a Field Experiment on TikTok's Artificia
 l Intelligence Systems and User Outcomes - Alexandra Masciantonio\, Nino G
 ugushvili
URL:https://pretalx.com/sips2025-budapest/talk/XHEHBP/
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