mlsanityData to 7 Oct 2026

Governance of Generative AI in Creative Work: Consent, Credit, Compensation, and Beyond

arXiv 2501.11457 ↗First posted 20 Jan 2025cs.HCcited by 13

Not on the map. Why?

Abstract (arXiv)

Since the emergence of generative AI, creative workers have spoken up about the career-based harms they have experienced arising from this new technology. A common theme in these accounts of harm is that generative AI models are trained on workers' creative output without their consent and without giving credit or compensation to the original creators. This paper reports findings from 20 interviews with creative workers in three domains: visual art and design, writing, and programming. We investigate the gaps between current AI governance strategies, what creative workers want out of generative AI governance, and the nuanced role of creative workers' consent, compensation and credit for training AI models on their work. Finally, we make recommendations for how generative AI can be governed and how operators of generative AI systems might more ethically train models on creative output in the future.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jan 2025.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 6; 2026: 7.

13 papers.

Sort:

By area:

  1. 2025Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol (MCP) Ecosystemcited by 17
  2. 2026Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Bookscited by 9
  3. 2025Attribution-by-design: Ensuring Inference-Time Provenance in Generative Music Systemscited by 3
  4. 2026"Unlimited Realm of Exploration and Experimentation": Methods and Motivations of AI-Generated Sexual Content Creatorscited by 3
  5. 2025Signals of Provenance: Practices & Challenges of Navigating Indicators in AI-Generated Media for Sighted and Blind Individualscited by 2
  6. 2025The AI Memory Gap: Users Misremember What They Created With AI or Withoutcited by 2
  7. 2025How Do Data Owners Say No? A Case Study of Data Consent Mechanisms in Web-Scraped Vision-Language AI Training Datasetscited by 2
  8. 2026Investigating Writing Professionals' Relationships with Generative AI: How Combined Perceptions of Rivalry and Collaboration Shape Work Practices and Outcomescited by 2
  9. 2025PRAC3 (Privacy, Reputation, Accountability, Consent, Credit, Compensation): Long Tailed Risks of Voice Actors in AI Data-Economycited by 0
  10. 2026"Better Ask for Forgiveness than Permission": Practices and Policies of AI Disclosure in Freelance Workcited by 0
  11. 2026Yes, But Not Always. Generative AI Needs Nuanced Opt-incited by 0
  12. 2026Can AI be a moral victim? The role of moral patiency and ownership perceptions in ethical judgments of using AI-generated contentcited by 0
1 more
  1. 2026Upskilling with Generative AI: Practices and Challenges for Freelance Knowledge Workerscited by 0