Overblokning

Overblokning is a term used in discussions of digital content filtering to describe situations where blocking exceeds the intent of a policy. It occurs when automated systems restrict access to legitimate content because of broad rules or misinterpretation.

The phenomenon appears in settings such as school or workplace internet filters, parental controls, search engines' safety features, and automated content moderation on social media.

Causes include overly broad category definitions, keyword-based or rule-based filters that catch unrelated terms, errors in image or video recognition, contextual misinterpretation, language ambiguity, bias in training data, and poorly tuned thresholds.

Effects can include reduced access to information, disruption of learning, user frustration, erosion of trust in filtering tools, and concerns about censorship or discrimination when certain groups are disproportionately affected.

Mitigation approaches involve refining policies to be more granular, adding contextual signals, using whitelists or opt-out mechanisms, combining automated tagging with human review, conducting regular audits, and increasing transparency about blocked content.

Finding the right balance between safety and openness is challenging because content and contexts change. Continuous evaluation and user feedback are essential to reduce overblokning while preserving protective aims.