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

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

human-AI collaboration, content classification, source cues, interactivity, HAII-TIME model

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) betweensubjects online experiment (N ¼ 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

Maria D. Molina , S. Shyam Sundar

https://doi.org/10.1093/jcmc/zmac010

Oxford University Press

16 May 2022

Sri Wahyuni

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English

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Journal of Computer-Mediated Communication, 2022