Measuring Proof Burden in Public Bounty Listings: A RentAHuman Case Study
3.20T1 sourcearXiv cs.HC
Source record
Published by arXiv cs.HC (T1 source). The original is at https://arxiv.org/abs/2608.18547.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryResearchers manually audited 981 listings on RentAHuman, a 2026 marketplace where AI agents hire humans, to measure 'proof burden'—requirements beyond task completion such as identity, location, or physical-world proof. 56.2% of 779 bounty/task listings scored 4 or 5 on a 0-5 Proof Burden Scale, spanning 154 distinct feature combinations.
Why it mattersDocuments an emerging AI-agent-to-human labor market with a coded taxonomy of what requesters actually demand, plus a baseline dataset of 981 listings. Useful reference for tracking agent labor patterns.
Cited by
No citations on record.
