Prevalence and Prevention of Large Language Model Use in Crowd Work

2025/02/18 by Veniamin Veselovsky, Manoel Horta Ribeiro, Philip J. Cozzolino +4 · 22 citations
Computer Science · Engineering · Social Sciences · #Computer science #Engineering #Knowledge Management and Sharing #Mobile Crowdsensing and Crowdsourcing #Social Media and Politics #Work (physics)

paper · doi:10.1145/3685527

published in Communications of the ACM 68(3), 42-47 (Association for Computing Machinery)

openalex publication_date 2025/02/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/26

Abstract

Crowd workers often use LLMs, but this can have a homogenizing effect on their output. How can we—and should we—prevent LLM use in crowd work?

Cited by

• Generative AI Meets Open-Ended Survey Responses: Research Participant Use of AI and Homogenization
• New Evidence and Design Considerations for Repeated Measure Experiments in Survey Research
• How Human is AI? Examining the Impact of Emotional Prompts on Artificial and Human and Responsiveness
• Recognising, Anticipating, and Mitigating LLM Pollution of Online Behavioural Research
• When Large Language Models are More PersuasiveThan Incentivized Humans, and Why
• CrowdLLM: Building LLM-Based Digital Populations Augmented with Generative Models
• Text as Behavior
• Detecting the Use of Generative AI in Crowdsourced Surveys: Implications for Data Integrity
• Recognising and mitigating LLM Pollution in online behavioural research
• Lessons from complex systems science for AI governance
• Helping or Homogenizing? GenAI as a Design Partner to Pre-Service SLPs for Just-in-Time Programming of AAC
• Redefining Research Crowdsourcing: Incorporating Human Feedback with LLM-Powered Digital Twins
• Transparency in Healthcare AI: Testing European Regulatory Provisions against Users' Transparency Needs
• Laypeople's Attitudes Towards Fair, Affirmative, and Discriminatory Decision-Making Algorithms
• A Penny for Your Prompts: Experiments Detecting and Mitigating LLM Usage by Survey Respondents

Related

• Prevalence and prevention of large language model use in crowd work
• Wisdom from Diversity: Bias Mitigation Through Hybrid Human-LLM Crowds
• How desirable is alignment between LLMs and linguistically diverse human users?
• Human-LLM Coevolution: Evidence from Academic Writing
• Eight Things to Know about Large Language Models