Result-Centered Rights Framework Revealing Limits… Discussion of ''Process, Intent, and Responsibility''-Centered Copyright Rises
We have long understood creation as a uniquely human domain, granting "copyright" as rights to the resulting works. But generative AI''s emergence is fundamentally shaking this premise — AI functions no longer as a simple tool but as a co-creator participating in the creative process. Academic framework: Professor Hyundaewon (Dean, Sogang University Graduate School of Virtual Convergence) defines AI in "AI-X" as "AI-Human Co-Creation (AHCC) — a collaborator and creative partner co-creating the virtual convergence world." This is not simple concept definition but a declaration that creative subjects and structures are moving from individual-centered to collaborative networks. The "aggregation" challenge: traditional copyright has held that simply combining information without creative transformation is not protectable — mere compilation without original structure/interpretation isn''t a work of authorship. Yet generative AI already performs structurally similar processes: learning vast data, reconstructing it, reflecting user prompts for context and perspective, and producing optimized results. The key question: is "creativity" uniquely human, or does it emerge through specific structural processes that AI can perform? AHCC framework implications: creation shifts from individual creator''s sole act to collaborative structure where humans and AI interact; traditional author-reader vertical structure transforms into horizontal co-creation network where humans and AI participate; viewing creation as "process" rather than "result." Copyright redesign needed: current copyright optimized for human individual creators cannot accommodate AI involvement — new frameworks needed covering: who receives copyright for AI-assisted works; when human direction of AI constitutes authorship; how AI developers'' contributions relate to output copyright; and what rights exist when AI is trained on copyrighted works to generate similar outputs.
