The Effects of AI Assistance on Self-Promotion
Alexander K Koch,
Jenny Kragl,
Sijuan Ming and
Julia Nafziger
No 21262, CEPR Discussion Papers from Centre for Economic Policy Research
Abstract:
Persistent gender gaps in self-promotion contribute to unequal labor market outcomes. In this study, we investigate how AI-assisted writing tools shape self-promotion, and, as a secondary outcome, confidence and how these effects interact with gender. For this purpose, we conducted an online experiment in China in which participants wrote self-promotion texts, provided a numerical self-promotion score and stated their confidence about how they will perform in an upcoming math and logic test. We find suggestive evidence that AI assistance reduces numerical self-evaluations. Neither gender nor the interaction between gender and AI assistance is significantly related to self-promotion or confidence. We conduct a text analysis to investigate the mechanisms behind these results.
Keywords: Confidence; Gender gaps (search for similar items in EconPapers)
JEL-codes: C90 D03 D83 J16 M12 (search for similar items in EconPapers)
Date: 2026-03
References: Add references at CitEc
Citations:
Downloads: (external link)
https://cepr.org/publications/DP21262 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:21262
Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP21262
Access Statistics for this paper
More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK.
Bibliographic data for series maintained by CEPR ().