  The illusion of consensus occurs when people believe there is consensus
across multiple sources, but the sources are the same and thus there is no
"true" consensus. We explore this phenomenon in the context of an AI-based
intelligent agent designed to augment metacognition on social media.
Misinformation, especially on platforms like Twitter, is a global problem for
which there is currently no good solution. As an explainable AI (XAI) system,
the agent provides explanations for its decisions on the misinformed nature of
social media content. In this late-breaking study, we explored the roles of
trust (attitude) and reliance (behaviour) as key elements of XAI user
experience (UX) and whether these influenced the illusion of consensus.
Findings show no effect of trust, but an effect of reliance on consensus-based
explanations. This work may guide the design of anti-misinformation systems
that use XAI, especially the user-centred design of explanations.
