# Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?

arXiv: https://arxiv.org/abs/2402.15467 · HTML: https://mlsanity.com/paper/2402.15467/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Feb 2024.

## Built on by (most cited first, 13 of 13)

- [Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers](https://mlsanity.com/paper/2502.09053/) (2025)
- [Towards Transparent and Incentive-Compatible Collaboration in Decentralized LLM Multi-Agent Systems: A Blockchain-Driven Approach](https://mlsanity.com/paper/2509.16736/) (2025)
- [How to Strategize Human Content Creation in the Era of GenAI?](https://mlsanity.com/paper/2406.05187/) (2024)
- [Flattening Supply Chains: When do Technology Improvements lead to Disintermediation?](https://mlsanity.com/paper/2502.20783/) (2025)
- [Foundations of GenIR](https://mlsanity.com/paper/2501.02842/) (2025)
- [Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources](https://mlsanity.com/paper/2505.07688/) (2025)
- [Data Sharing with a Generative AI Competitor](https://mlsanity.com/paper/2505.12386/) (2025)
- [Entry Barriers in Content Markets](https://mlsanity.com/paper/2509.01953/) (2025)
- [Human-AI Collaboration Mechanism Study on AIGC Assisted Image Production for Special Coverage](https://mlsanity.com/paper/2512.13739/) (2025)
- [LLM Active Alignment: A Nash Equilibrium Perspective](https://mlsanity.com/paper/2602.06836/) (2026)
- [Market Games for Generative Models: Equilibria, Welfare, and Strategic Entry](https://mlsanity.com/paper/2602.17787/) (2026)
- [Content Creation with Spillovers: An Incentive Design Approach](https://mlsanity.com/paper/2603.14372/) (2026)
- [Guiding Worker Self-Selection in Crowdsourcing Contests: An LLM-Augmented Algorithmic Approach](https://mlsanity.com/paper/2609.07749/) (2026)

## Abstract (arXiv)

The advent of generative AI (GenAI) technology produces transformative impact on the content creation landscape, offering alternative approaches to produce diverse, high-quality content across media, thereby reshaping online ecosystems but also raising concerns about market over-saturation and the potential marginalization of human creativity. Our work introduces a competition model generalized from the Tullock contest to analyze the tension between human creators and GenAI. Our theory and simulations suggest that despite challenges, a stable equilibrium between human and AI-generated content is possible. Our work contributes to understanding the competitive dynamics in the content creation industry, offering insights into the future interplay between human creativity and technological advancements in GenAI.