HUMAN–AI COLLABORATION IN CREATIVE CONTENT GENERATION
DOI:
https://doi.org/10.70917/ijcisim-2026-4347Keywords:
human–AI collaboration, generative AI, co-creativity, creative content, provenance, responsible AI, design workflowAbstract
Generative AI is transforming the conceptual development and design of text, images, music and video ideas and variations – both in terms of real time efficiency and cost. Not in the creative ability of humans, though, but of DED. The outcome of human's activity and what they feed into their personal life, the assessment of them, responsibility, the decision to communicate each other with the scale changes and transformations made by the machine. For a miniproj, the human centric approach is suggested and proposed for the content generation: co-creation and creativity. Our stages are: Framing of the brief, independent/humanased seed, articulation of alternatives, AI, getting it to mature, getting it approved then released to the learning outcomes. Clearly identifies who's responsible for each and every step, and all elements of the provenance ledger –the sources, what the consents are, the model(s), model version(s), prompts, candidates, the editor, and who's doing the reviewing of the edit and ledger disclosure persons. Please use the design in writing, visual communication, campaign ideas and for production of educational media. Issues of originality, relevance, voice, factuality and accessibility/efficiency now come into the picture when it comes to quality and release gates. Controlled prototype – same prototype compared to Human (or non-human) (or both) prototype and same set of Briefs and same experts used and blinded during evaluation. Only illustrative results (not necessarily experimental result) indicated to show the propose analysis. The least successful creative engagement is to have the partners develop a project or if following the ‘quick and post' route. It's a clear and incremental process in which each individual can maintain ownership of their own decisions about what to write and be ready to take responsibility for what they write, while the AI can offer them more avenues for exploration, faster iterations of revisions and test options.