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We examine whether large language models (LLMs) exhibit race- and gender-based name discrimination in hiring decisions, similar to classic findings in the social sciences (Bertrand and Mullainathan, 2004).
Statistical methods for research workers
Ronald Aylmer Fisher. 1928 · 1928
Earlier work this paper cites.
CrowS-pairs: A challenge dataset for measuring social biases in masked language models
Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel R. Bowman. 2020 · 1967
Earlier work this paper cites.
Labor market discrimination against hispanic and black men
Cordelia W. Reimers. 1983 · 1983
Earlier work this paper cites.
The labor market status of hispanic men
Barry R. Chiswick. 1987 · 1987
Earlier work this paper cites.
Employer hiring practices: differential treatment of hispanic and anglo job seekers
Harry Cross. 1990 · 1990
Earlier work this paper cites.
An analysis of the correlates of discrimination facing young hispanic job-seekers
Genevieve M. Kenney and Douglas A. Wissoker. 1994 · 1994
Earlier work this paper cites.
Measuring individual differences in implicit cognition: the implicit association test
Anthony G Greenwald, Debbie E McGhee, and Jordan LK Schwartz. 1998 · 1998
Earlier work this paper cites.
An economic analysis of anti-hispanic discrimination in the american labor market: 1970s-1990s
Rebecca K. Woods. 2000 · 2000
Earlier work this paper cites.
Harvesting implicit group attitudes and beliefs from a demonstration web site
Brian A Nosek, Mahzarin R Banaji, and Anthony G Greenwald. 2002 · 2002
Earlier work this paper cites.
Using tf-idf to determine word relevance in document queries
Juan Ramos et al. 2003 · 2003
Earlier work this paper cites.
Are emily and greg more employable than lakisha and jamal? a field experiment on labor market discrimination
Marianne Bertrand and Sendhil Mullainathan. 2004 · 2004
Earlier work this paper cites.
Hispanics in the us labor market
Brian Duncan, V Joseph Hotz, and Stephen J Trejo. 2006 · 2006
Earlier work this paper cites.
The “name game”: Affective and hiring reactions to first names
John L Cotton, Bonnie S O’neill, and Andrea Griffin. 2008 · 2008
Earlier work this paper cites.
Barriers to reintegration: An audit study of the impact of race and offender status on employment opportunities for women
Sarah Wittig Galgano. 2009 · 2009
Earlier work this paper cites.
The new jim crow
Michelle Alexander. 2011 · 2011
Earlier work this paper cites.
Racial Disparity in Unemployment
Joseph A Ritter and Lowell J Taylor. 2011 · 2011
Earlier work this paper cites.
Networks of Opportunity: Gender, Race, and Job Leads
Steve McDonald, Nan Lin, and Dan Ao. 2014 · 2014
Earlier work this paper cites.
Racial discrimination in the labor market for recent college graduates: Evidence from a field experiment
John M. Nunley, Adam Pugh, Nicholas Romero, and R. Alan Seals. 2015 · 2015
Earlier work this paper cites.
From patrick to john f.: Ethnic names and occupational success in the last era of mass migration
Joshua R. Goldstein and Guy Stecklov. 2016 · 2016
Earlier work this paper cites.
The problem with bias: Allocative versus representational harms in machine learning
Solon Barocas, Kate Crawford, Aaron Shapiro, and Hanna Wallach. 2017 · 2017
Earlier work this paper cites.
Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan. 2017 · 2017
Cited alongside, same era.
The trouble with bias
Kate Crawford. 2017 · 2017
Cited alongside, same era.
Bridging the gender gap in confidence
Barbara A. Carlin, Betsy D. Gelb, Jamie K. Belinne, and Latha Ramchand. 2018 · 2018
Cited alongside, same era.
Gender bias in coreference resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018
Cited alongside, same era.
Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018 · 2018
Cited alongside, same era.
It’s all in the name: Mitigating gender bias with name-based counterfactual data substitution
Rowan Hall Maudslay, Hila Gonen, Ryan Cotterell, and Simone Teufel. 2019 · 2019
SODAPOP: Open-ended discovery of social biases in social commonsense reasoning models
Haozhe An, Zongxia Li, Jieyu Zhao, and Rachel Rudinger. 2023 · 2023
Later among the works it cites.
Nichelle and nancy: The influence of demographic attributes and tokenization length on first name biases
Haozhe An and Rachel Rudinger. 2023 · 2023
Later among the works it cites.
Out of one, many: Using language models to simulate human samples
Lisa P Argyle, Ethan C Busby, Nancy Fulda, Joshua R Gubler, Christopher Rytting, and David Wingate. 2023 · 2023
Later among the works it cites.
Marked personas: Using natural language prompts to measure stereotypes in language models
Myra Cheng, Esin Durmus, and Dan Jurafsky. 2023 · 2023
Later among the works it cites.
Can ai language models replace human participants?
Danica Dillion, Niket Tandon, Yuling Gu, and Kurt Gray. 2023 · 2023
Later among the works it cites.
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Race and networks in the job search process
David S. Pedulla and Devah Pager. 2019 · 2019
Cited alongside, same era.
When the name matters: An experimental investigation of ethnic discrimination in the finnish labor market
Akhlaq Ahmad. 2020 · 2020
Cited alongside, same era.
Language (technology) is power: A critical survey of “bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach. 2020 · 2020
Cited alongside, same era.
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2020
Cited alongside, same era.
“you are grounded!”: Latent name artifacts in pre-trained language models
Vered Shwartz, Rachel Rudinger, and Oyvind Tafjord. 2020 · 2020
Cited alongside, same era.
The confidence gap predicts the gender pay gap among stem graduates
Adina D. Sterling, Marissa E. Thompson, Shiya Wang, Abisola Kusimo, Shannon Gilmartin, and Sheri Sheppard. 2020 · 2020
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Tamanna Hossain, Sunipa Dev, and Sameer Singh. 2023 · 2023
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Examining the causal impact of first names on language models: The case of social commonsense reasoning
Sullam Jeoung, Jana Diesner, and Halil Kilicoglu. 2023 · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
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OpenAI. 2023 · 2023
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Race and ethnicity data for first, middle, and surnames
Evan TR Rosenman, Santiago Olivella, and Kosuke Imai. 2023 · 2023
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A rose by any other name would not smell as sweet: Social bias in names mistranslation
Sandra Sandoval, Jieyu Zhao, Marine Carpuat, and Hal Daumé III. 2023 · 2023
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Evaluating and mitigating discrimination in language model decisions
Alex Tamkin, Amanda Askell, Liane Lovitt, Esin Durmus, Nicholas Joseph, Shauna Kravec, Karina Nguyen, Jared Kaplan, and Deep Ganguli. 2023 · 2023
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Akshaj Kumar Veldanda, Fabian Grob, Shailja Thakur, Hammond Pearce, Benjamin Tan, Ramesh Karri, and Siddharth Garg. 2023 · 2023
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“kelly is a warm person, joseph is a role model”: Gender biases in LLM-generated reference letters
Yixin Wan, George Pu, Jiao Sun, Aparna Garimella, Kai-Wei Chang, and Nanyun Peng. 2023 · 2023
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The silicone ceiling: Auditing gpt’s race and gender biases in hiring
Lena Armstrong, Abbey Liu, Stephen MacNeil, and Danaë Metaxa. 2024 · 2024
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Auditing the use of language models to guide hiring decisions
Johann D Gaebler, Sharad Goel, Aziz Huq, and Prasanna Tambe. 2024 · 2024
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What’s in a name? auditing large language models for race and gender bias
Amit Haim, Alejandro Salinas, and Julian Nyarko. 2024 · 2024
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Systemic Discrimination Among Large U.S. Employers
Patrick Kline, Evan K Rose, and Christopher R Walters. 2022 · 2036
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BBQ: A hand-built bias benchmark for question answering
Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Thompson, Phu Mon Htut, and Samuel Bowman. 2022 · 2086
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