Van Niekerk, Daniel;
Peréz-Ortiz, María;
Shawe-Taylor, John;
Orlic, Davor;
Drobnjak, ivana;
Kay, Jackie;
Siegel, Noah;
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(2024)
Challenging Systematic Prejudices: An Investigation into Bias Against Women and Girls.
UNESCO, IRCAI: Paris, France.
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Abstract
The International Research Centre on Artificial Intelligence (IRCAI), under the auspices of UNESCO, in collaboration with UNESCO HQ, has released a comprehensive report titled “Challenging Systematic Prejudices: An Investigation into Gender Bias in Large Language Models”. This groundbreaking study sheds light on the persistent issue of gender bias within artificial intelligence, emphasizing the importance of implementing normative frameworks to mitigate these risks and ensure fairness in AI systems globally. We are excited to announce this new in-depth report in a partnership with a number of authors, set for release on International Women’s Day on March 8, 2024.
| Type: | Report |
|---|---|
| Title: | Challenging Systematic Prejudices: An Investigation into Bias Against Women and Girls |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://ircai.org/project/challenging-systematic-p... |
| Language: | English |
| Additional information: | This study is available in Open Access under the Attribution-ShareAlike 3.0 IGO (CC-BY-SA 3.0 IGO) license (https://creativecommons.org/licenses/by-sa/3.0/igo/). By using the content of this study, the users accept to be bound by the terms of use of the UNESCO Open Access Repository (https://www.unesco.org/en/openaccess/cc-sa). |
| Keywords: | Artificial Intelligence, Gender, Bias |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10188772 |
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