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When AI moderates online content: Effects of human collaboration and interactive transparency on user trust

  • Michigan State University
  • Pennsylvania State University

Research output: Contribution to journalArticlepeer-review

Abstract

Given the scale of user-generated content online, the use of artificial intelligence (AI) to flag problematic posts is inevitable, but users do not trust such automated moderation of content. We explore if (a) involving human moderators in the curation process and (b) affording "interactive transparency,"wherein users participate in curation, can promote appropriate reliance on AI. We test this through a 3 (Source: AI, Human, Both) × 3 (Transparency: No Transparency, Transparency-Only, Interactive Transparency) × 2 (Classification Decision: Flagged, Not Flagged) between-subjects online experiment (N = 676) involving classification of hate speech and suicidal ideation. We discovered that users trust AI for the moderation of content just as much as humans, but it depends on the heuristic that is triggered when they are told AI is the source of moderation. We also found that allowing users to provide feedback to the algorithm enhances trust by increasing user agency.

Original languageEnglish
Article numberzmac010
JournalJournal of Computer-Mediated Communication
Volume27
Issue number4
DOIs
StatePublished - 1 Jul 2022
Externally publishedYes

Keywords

  • Content classification
  • Haii-Time model
  • Human-AI collaboration
  • Interactivity
  • Source cues

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