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Data

Crowd Workers Widely Use LLMs for Text Production

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First page
Crowd Workers Widely Use LLMs for Text Production
The curator’s take

Empirical evidence that 33-46% of MTurk crowd workers used LLMs on text tasks.

Key points
01

LLM-generated contamination: Estimates that a third to almost half of crowd-worker text production involved LLMs - a massive data quality issue.

02

Benchmark contamination risk: Implications for NLP datasets produced via crowdsourcing, potentially invalidating many "human baseline" numbers.

03

Methodology: Uses statistical analysis comparing completion times, stylistic features, and output consistency to estimate LLM usage.

04

Community wake-up: Sparked widespread discussion about the future of human-generated data and the need for AI-usage detection.

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