# "Generate" the Future of Work through AI: Empirical Evidence from Online Labor Markets

arXiv: https://arxiv.org/abs/2308.05201 · HTML: https://mlsanity.com/paper/2308.05201/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 54 references that are in the map.
- First posted on arXiv 9 Aug 2023.

## Builds on (most cited first, 8 of 8)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [Toolformer: Language Models Can Teach Themselves to Use Tools](https://mlsanity.com/paper/2302.04761/) (2023)
- [Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback](https://mlsanity.com/paper/2204.05862/) (2022)
- [Self-Instruct: Aligning Language Models with Self-Generated Instructions](https://mlsanity.com/paper/2212.10560/) (2022)
- [Augmented Language Models: a Survey](https://mlsanity.com/paper/2302.07842/) (2023)
- [GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models](https://mlsanity.com/paper/2303.10130/) (2023)
- [The Future of ChatGPT-enabled Labor Market: A Preliminary Study in China](https://mlsanity.com/paper/2304.09823/) (2023)

## Built on by (most cited first, 7 of 7)

- [Position: Key Claims in LLM Research Have a Long Tail of Footnotes](https://mlsanity.com/paper/2308.07120/) (2023)
- [Generative AI and Copyright: A Dynamic Perspective](https://mlsanity.com/paper/2402.17801/) (2024)
- [A Scoping Review of ChatGPT Research in Accounting and Finance](https://mlsanity.com/paper/2412.05731/) (2024)
- [Crafting Knowledge: Exploring the Creative Mechanisms of Chat-Based Search Engines](https://mlsanity.com/paper/2402.19421/) (2024)
- [AI and Jobs: Has the Inflection Point Arrived? Evidence from an Online Labor Platform](https://mlsanity.com/paper/2312.04180/) (2023)
- [Generative AI Impact on Labor Market: Analyzing ChatGPT's Demand in Job Advertisements](https://mlsanity.com/paper/2412.07042/) (2024)
- [When AI Agents Compete for Jobs: Strategic Capabilities and Economic Dynamics of AI Labour Markets](https://mlsanity.com/paper/2512.04988/) (2025)

## Abstract (arXiv)

Large Language Model (LLM)-based generative AI systems are general-purpose tools capable of augmenting or even automating a wide range of job functions, positioning them to reshape labor market dynamics. However, predicting their precise impact a priori is challenging, given AI's simultaneous effects on both demand and supply, as well as the strategic responses of market participants. Leveraging an extensive dataset from a leading online labor platform, we document a pronounced displacement effect and an overall contraction in submarkets where required skills closely align with core LLM functionalities. Although demand and supply both decline, the reduction in supply is comparatively smaller, thereby intensifying competition among freelancers. Notably, further analysis shows that this heightened competition is especially pronounced in programming-intensive submarkets. This pattern is attributed to skill-transition effects: by lowering the human-capital barrier to programming, ChatGPT enables incumbent freelancers to enter programming tasks. Moreover, these transitions are not homogeneous, with high-skilled freelancers contributing disproportionately to the shift. Our findings illuminate the multifaceted impacts of general-purpose AI on labor markets, highlighting not only the displacement of certain occupations but also the inducement of skill transitions within the labor supply. These insights offer practical implications for policymakers, platform operators, and workers.