The content authorship-generation continuum: A framework for classifying AI-mediated content

Generative artificial intelligence increasingly creates content at runtime across digital platforms, yet no systematic framework exists for classifying these systems based on content authorship (human versus AI) and generation timing (pre-deployment versus runtime). Platforms, developers, and policymakers lack shared terminology for governance and accountability. We propose the Content Authorship-Generation continuum, a domain-agnostic framework classifying digital experiences into five stages from full human authorship to full AI generation and curation. Organised around editorial control and creative agency principles, the continuum reveals authorship distinctions with direct implications for moderation, design, and transparency. This conceptual framework enables stage-appropriate moderation strategies, design patterns, and accountability models, demonstrating utility through analysis of practical implications for developers, platforms, policymakers, and users.