Haku Haku Haku Haku Haku Haku Haku: (1) Evan Shieh, The Young Data Scientists League (evan.shieh@youngdatascientists.org); (2) Faye-Marie Vassel, University of Stanford; (3) Cassidy Sugimoto, School of Public Policy, Georgia Institute of Technology; (4) Thema Monroe-White, Schar School of Policy and Government & Department of Computer Science, George Mason University (tmonroew@gmu.edu). Authors: (1) Evan Shieh, The Young Data Scientists League (evan.shieh@youngdatascientists.org); (2) Faye-Marie Vassel, University of Stanford; (3) Cassidy Sugimoto, School of Public Policy, Georgia Institute of Technology; (4) Thema Monroe-White, Schar School of Policy and Government & Department of Computer Science, George Mason University (tmonroew@gmu.edu). Qalabka Left Qalabka iyo 1 Introduction 1.1 Dhammaan iyo Dhammaan 2 Shuruudaha iyo Shuruudaha 2.1 Proxies Identity Textual iyo Qalabka Socio-Psychological 2.2 Modeling jilicsan, kharashka jilicsan, iyo jilicsan 3 Qalabka 3.1 Qalabka dhismaha 3.2 Qalabka dhismaha 3.3 Qalabka Stereotyping 4 Discussions, adeegyada, iyo references SUPPLEMENTAL MATERIALS Qalabka dhismaha iyo intersectionality B. Qalabka Technical B.1 Modeling jilicsan iyo dhismaha jilicsan Qalabka B2 B.3 Data Mining Automated ee Textual Cues B.4 Qalabka Ratio Qalabka Qalabka Qalabka B.6 Median Racialized Subordination Ratio waaweyn B.7 Cues Extended for Stereotype Analysis (Luuqaha ugu badan ee loo yaqaan "Stereotype Analysis") B.8 Taageerada Statistics C. Qalabka ugu badan C.1 Waqtiga ugu horeysay ee LM per Race C.2 Qalabka ugu fiican ee Texts Full Synthetic D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D. D D.1 Data Sheet for Laissez-Faire Prompts Dataset Qalabka dhismaha iyo intersectionality Markaas ka mid ah wax soo saarka ugu horeysay oo loo yaabaa in ay ku yaalaa in ay ku yaalaa in ka mid ah xafiisyada iyo xafiisyada socodka ah [38], waxaan ku yaalaa in ay u soo saarka sida LM-ka loo soo saarka ka mid ah wax soo saarka oo ka mid ah wax soo saarka ah oo ka mid ah wax soo saarka iyo wax soo saarka ah oo ka mid ah wax soo saarka iyo wax soo saarka iyo wax soo saarka ah oo ka mid ah wax soo saarka iyo wax soo saarka iyo wax soo saarka. Waxaad ka soo bandhigay in ay ka soo bandhigay in ay ka mid ah mid ka mid ah mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ah mid ka mid ah mid ka mid ah mid ah mid ka mid ah mid ah mid ka mid ah mid ka mid ah mid ah mid ka mid ah mid ka mid ah mid ah mid ka mid ah mid ka mid ah mid ka mid ah mid ah mid ka mid ah mid ah mid ka mid ah mid ah mid ka mid ah mid ah mid ka mid Sidaa loo yaabaa, wax soo saarka waxaa loo yaabaa in ka mid ah wax soo saarka ah oo ka mid ah wax soo saarka iyo wax soo saarka ah oo ka mid ah wax soo saarka iyo wax soo saarka. Haku Haku Waxaa la heli karaa in arkiv oo ku saabsan license CC BY 4.0 DEED. Waxaa la heli karaa in arkiv oo ku saabsan license CC BY 4.0 DEED. Xafiisyada Archive

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Bias in Algorithmic Technology Exposed 

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Qalabka waxaa laga yaqaan "Power Struggles Buried in AI Responses".

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