Dream machine -- the next creative economy

• URL: http://arxiv.org/abs/2606.26114v1
• Date: Thu, 21 May 2026 19:21:39 GMT
• Title: Dream machine -- the next creative economy
• Abstract summary: We examine the structural transformation of creative industries under generative artificial intelligence.<n>We trace the historical pattern of creative resistance to technological disruption.<n>We investigate how major studios, from Disney's $1 billion OpenAI investment to Netflix's AI-native animation unit, are positioning for an AI-augmented production pipeline.
• Score: 0.0
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: We examine the structural transformation of creative industries under generative artificial intelligence, drawing on 374 primary sources spanning policy documents, industry data, creator surveys, and platform analytics. Beginning with the December 2024 release of OpenAI's Sora video model as a watershed event, we trace the historical pattern of creative resistance to technological disruption, then develop an analytical framework -- the Human-AI Agency Continuum for mapping the spectrum of human and machine collaboration in creative work. We present evidence for the "slop ceiling," an audience-imposed quality threshold that constrains AI-generated content to approximately 1--3% of platform streams despite comprising 44% of uploads. Analysis of the UK Government's 2025 consultation on AI and copyright (over 11,500 responses, 88% opposing expanded AI training rights) reveals deep structural tensions between technology firms and creative workers. We investigate how major studios, from Disney's $1 billion OpenAI investment to Netflix's AI-native animation unit, are positioning for an AI-augmented production pipeline. The work covers coordination collapse in creative supply chains, the emergence of new professional roles such as prompt engineers and AI orchestrators, and proposes four principles for navigating the transition: transparency, consent, compensation, and human-centred design. Eight appendices provide quantitative analysis, a glossary, topical bibliography, and deep dives into shadow AI adoption, AI stigma, and algorithmic intent.

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