Public Negotiation of AI-Mediated Cognition in Reddit Discourse

We examine how acceptable AI assistance is related to continuing human responsibility in public discussion. Our analysis covers 208,252 comments from selected Reddit communities using nonexclusive lexical indicators, BERTopic on a fixed 50,000-comment subset, contextual interpretation, engagement measures and monthly distributions. AI-assisted learning and broader educational discussion formed the largest non-outlier clusters. Illustrative arguments made assistance conditional on retained understanding, source checking and accountable professional judgment; other selected topics supplied educational, institutional or human capacity context. The six largest primary clusters recurred across 13 observed months, while frequency, scores and extended comments captured different forms of prominence. A coverage-oriented 120-case label fit assessment yielded coder agreement of 50/60 for indicators and 60/60 for topics, including one shared topic label rejection. Nine sensitivity reconstructions produced 14–35 non-outlier topics, with variation in cluster boundaries and the separation of smaller themes. The study contributes to social informatics by showing how cognitive responsibility is articulated through relations among AI assistance, human competence, verification and institutional expectations within a purposively sampled platform environment.