I'm Fully Who I Am - Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation
Offered By: Association for Computing Machinery (ACM) via YouTube
Course Description
Overview
Explore a 15-minute conference talk that addresses the critical issue of measuring biases in open language generation, with a focus on centering transgender and non-binary voices. Delve into the research presented by authors Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zack Jaggers, Kai-Wei Chang, Aram Galstyan, Richard Zemel, and Rahul Gupta at the Association for Computing Machinery (ACM). Gain insights into the importance of inclusive representation in language models and the methodologies employed to identify and mitigate biases against transgender and non-binary individuals in AI-generated content.
Syllabus
"I'm fully who I am'': Towards Centering Transgender and Non-Binary Voices to Measure Biases in…
Taught by
ACM FAccT Conference
Related Courses
Translation Tutorial - Thinking Through and Writing About Research Ethics Beyond "Broader Impact"Association for Computing Machinery (ACM) via YouTube Translation Tutorial - Data Externalities
Association for Computing Machinery (ACM) via YouTube Translation Tutorial - Causal Fairness Analysis
Association for Computing Machinery (ACM) via YouTube Implications Tutorial - Using Harms and Benefits to Ground Practical AI Fairness Assessments
Association for Computing Machinery (ACM) via YouTube Responsible AI in Industry - Lessons Learned in Practice
Association for Computing Machinery (ACM) via YouTube