Algorithmic Moderation

Algorithmic moderation refers to the use of automated systems, including machine learning models and rule-based filters, to identify, flag, rank, or remove content on digital platforms without direct human review of each decision. It enables platforms to process content at massive scale that would be impossible with human review alone, but introduces risks of systematic errors and biases. Research consistently finds that automated moderation systems perform inconsistently across languages, dialects, and cultural contexts, and are more likely to incorrectly flag content from marginalized communities — including disability advocacy, chronic illness peer support, LGBTQ+ expression, and discussions of race — as violating community guidelines. For digital accessibility, algorithmic moderation is particularly concerning because AI-based classifiers may not be trained on disability-specific content, leading to the over-removal of legitimate disability-related posts and suppression of communities that rely on these platforms for peer support and advocacy.