Move Fast and Mend Things: Keeping Up with Evolving AI Harms Using Social Media Commentary

Researchers have introduced an LLM-assisted thematic analysis pipeline designed to dynamically detect, categorise, and track emerging AI harms from large-scale social media commentary. Analysing 5.7 million Reddit summaries between January 2025 and June 2026, the study generated a dataset of 575,000 harm-related posts and a 12-category, 47-subnode taxonomy that surfaces granular risks, such as distinct AI privacy violations, frequently omitted by top-down governance frameworks.

Standard AI threat models frequently fail to anticipate the full breadth of operational, psychological, and socio-technical harms experienced by users post-deployment. Incorporating bottom-up surveillance of public commentary allows organisations to identify unforeseen vulnerabilities before they manifest as critical failures or regulatory infractions. Transitioning to continuous, dynamic risk discovery is essential for maintaining institutional resilience in rapidly evolving technological environments.

Ex-ante threat modelling and ex-post incident tracking often miss socio-technical, psychological, and operational AI harms generated by rapid deployment.

Forward consideration, not a verified fact.