{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/115868"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/115868","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Preference for gender stereotypicality in artificial intelligence","abstract":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01","abstract_html":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01","abstract_has_math":false,"creators":["Spielmann, Julia"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":["Stern, Chadly","Cohen, Dov","Fairbairn, Catharine","Todd, Nathtan","Miller, Andrea"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-08","date_published":"2022-08","updated_at":"2026-07-22T22:24:55Z","subjects":["gender stereotyping","artificial intelligence"],"languages":["en","eng"],"rights":["Copyright 2022 Julia Spielmann"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/115868","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Stern, Chadly","Cohen, Dov","Fairbairn, Catharine","Todd, Nathtan","Miller, Andrea"]},{"key":"dc:creator","label":"Author","values":["Spielmann, Julia"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-08","2022-06-15"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["gender stereotyping","artificial intelligence"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Julia Spielmann"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/115868"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01","The student, Julia Spielmann, accepted the attached license on 2022-06-14 at 10:26.","The student, Julia Spielmann, submitted this Dissertation for approval on 2022-06-14 at 10:36.","This Dissertation was approved for publication on 2022-06-15 at 08:19.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18075 on 2022-11-16 at 10:17:13","Do people prefer for voice-based artificial intelligence (AI) to align with gender stereotypes? Gender is a salient and ubiquitous organizing principle that provides a sense of structure and simplicity to society. Initial evidence suggests that non-human entities, such as weather patterns, numbers, robots, and even AI, are perceived within a human-gender context. However, no research to date has investigated whether people prefer gender stereotypicality in AI. AI provides a unique context to examine gender stereotyping that is removed from both social (e.g., gender discrimination laws that apply to humans) and non-social factors (e.g., biological influences on gender roles among humans). Across four studies using experimental designs, I examined whether people prefer voice-based AI that aligns with gender stereotypes. Across Studies 1 and 2, I found that people preferred gender stereotypicality (over counterstereotypicality and androgyny) in voice-based AI. In Studies 3 and 4, I found that people perceived AI as more credible when the gender of the AI voice was a stereotypical (versus counterstereotypical) match to the gender of the question, which in part explained people’s preference for stereotypicality. These studies contribute to understanding whether people prefer gender stereotypicality outside human gender relations, which holds implications for how AI might be used to both create and reinforce a gendered social reality."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Preference for gender stereotypicality in artificial intelligence"]}]}],"canonical_facts":{"dc:contributor":["Stern, Chadly","Cohen, Dov","Fairbairn, Catharine","Todd, Nathtan","Miller, Andrea"],"dc:creator":["Spielmann, Julia"],"dc:date":["2022-08","2022-06-15"],"dc:description":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01","The student, Julia Spielmann, accepted the attached license on 2022-06-14 at 10:26.","The student, Julia Spielmann, submitted this Dissertation for approval on 2022-06-14 at 10:36.","This Dissertation was approved for publication on 2022-06-15 at 08:19.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18075 on 2022-11-16 at 10:17:13","Do people prefer for voice-based artificial intelligence (AI) to align with gender stereotypes? Gender is a salient and ubiquitous organizing principle that provides a sense of structure and simplicity to society. Initial evidence suggests that non-human entities, such as weather patterns, numbers, robots, and even AI, are perceived within a human-gender context. However, no research to date has investigated whether people prefer gender stereotypicality in AI. AI provides a unique context to examine gender stereotyping that is removed from both social (e.g., gender discrimination laws that apply to humans) and non-social factors (e.g., biological influences on gender roles among humans). Across four studies using experimental designs, I examined whether people prefer voice-based AI that aligns with gender stereotypes. Across Studies 1 and 2, I found that people preferred gender stereotypicality (over counterstereotypicality and androgyny) in voice-based AI. In Studies 3 and 4, I found that people perceived AI as more credible when the gender of the AI voice was a stereotypical (versus counterstereotypical) match to the gender of the question, which in part explained people’s preference for stereotypicality. These studies contribute to understanding whether people prefer gender stereotypicality outside human gender relations, which holds implications for how AI might be used to both create and reinforce a gendered social reality."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/115868"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Julia Spielmann"],"dc:subject":["gender stereotyping","artificial intelligence"],"dc:title":["Preference for gender stereotypicality in artificial intelligence"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Psychology"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:55Z"}