. // Multilingual gender fairness in AI-generated texts
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ABG-139241
ADUM-75250 |
Thesis topic | |
| 2026-05-22 |
Université de Lorraine
NANCY - Grand Est - France
. // Multilingual gender fairness in AI-generated texts
., .
Language Awareness, Gender Stereotypes, Generative AI
Language Awareness, Gender Stereotypes, Generative AI
Topic description
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Despite major advances in GenAI, stereotyping and biases are ubiquitous in texts generated by AI technologies, which runs counter to a European society committed to gender equality. The doctoral contract will:
1) investigate texts generated by leading LLMs (e.g. OpenAI's ChatGPT, Google's Gemini, Mistral's Le Chat) in terms of gender fairness with a focus on languages other than EN (e.g. DA, FR, DE);
2) explore the impact of linguistic factors (i.e. linguistic bias), specifically the effects of grammatically un/gendered languages and the masculine default, on gendered representations using corpus linguistic methods;
3) reveal how AI tools echo and reinforce human bias as well as raise Critical Multilingual Language Awareness among users and developers of how LLMs index gender-related structures of power;
4) contribute to enhancing the dialogue between linguists and computer scientists to confront sexism in GenAI technologies with the Associated Partners.
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Début de la thèse : 01/11/2026
WEB : https://www.multilawa.eu
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Despite major advances in GenAI, stereotyping and biases are ubiquitous in texts generated by AI technologies, which runs counter to a European society committed to gender equality. The doctoral contract will:
1) investigate texts generated by leading LLMs (e.g. OpenAI's ChatGPT, Google's Gemini, Mistral's Le Chat) in terms of gender fairness with a focus on languages other than EN (e.g. DA, FR, DE);
2) explore the impact of linguistic factors (i.e. linguistic bias), specifically the effects of grammatically un/gendered languages and the masculine default, on gendered representations using corpus linguistic methods;
3) reveal how AI tools echo and reinforce human bias as well as raise Critical Multilingual Language Awareness among users and developers of how LLMs index gender-related structures of power;
4) contribute to enhancing the dialogue between linguists and computer scientists to confront sexism in GenAI technologies with the Associated Partners.
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Début de la thèse : 01/11/2026
WEB : https://www.multilawa.eu
Funding category
Funding further details
Programmes de l'Union Européenne de financement de la recherche (ERC, ERASMUS)
Presentation of host institution and host laboratory
Université de Lorraine
Institution awarding doctoral degree
Université de Lorraine
Graduate school
78 SLTC - SOCIETES, LANGAGES, TEMPS, CONNAISSANCES
Candidate's profile
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The Doctoral Candidate is expected to – have the potential to conduct research of excellent quality , as demonstrated by initial academic work such as the master's thesis, and – if applicable – presentations at conferences, awareness-raising activities or publications. – be interested in working in a multilingual, interdisciplinary and international research environment. – have excellent communication skills in German and English (at least B2). – be willing to undertake international research secondments and travels. See details: https://www.multilawa.eu/recruitment-for-applying/general-information/
The Doctoral Candidate is expected to – have the potential to conduct research of excellent quality , as demonstrated by initial academic work such as the master's thesis, and – if applicable – presentations at conferences, awareness-raising activities or publications. – be interested in working in a multilingual, interdisciplinary and international research environment. – have excellent communication skills in German and English (at least B2). – be willing to undertake international research secondments and travels. See details: https://www.multilawa.eu/recruitment-for-applying/general-information/
2026-07-08
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