all AI news
Non-discrimination Criteria for Generative Language Models
March 14, 2024, 4:48 a.m. | Sara Sterlie, Nina Weng, Aasa Feragen
cs.CL updates on arXiv.org arxiv.org
Abstract: Within recent years, generative AI, such as large language models, has undergone rapid development. As these models become increasingly available to the public, concerns arise about perpetuating and amplifying harmful biases in applications. Gender stereotypes can be harmful and limiting for the individuals they target, whether they consist of misrepresentation or discrimination. Recognizing gender bias as a pervasive societal construct, this paper studies how to uncover and quantify the presence of gender biases in generative …
abstract applications arxiv become biases concerns cs.ai cs.cl cs.hc development discrimination gender generative language language models large language large language models public stereotypes type
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
Founding AI Engineer, Agents
@ Occam AI | New York
AI Engineer Intern, Agents
@ Occam AI | US
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Alternance DATA/AI Engineer (H/F)
@ SQLI | Le Grand-Quevilly, France