A naukri.com initiative
Arxiv
1w
109
Image Credit: Arxiv
On the Effectiveness and Generalization of Race Representations for Debiasing High-Stakes Decisions
- Understanding and mitigating biases in large language models (LLMs) is crucial for their use in high-stakes decision-making.
- The study introduces two decision tasks, Admissions and Hiring, to assess racial bias in LLMs.
- The experiment shows that Gemma 2B Instruct and LLaMA 3.2 3B Instruct have strong biases in favor of certain racial groups.
- While prompt engineering fails to promote fairness, debiasing interventions based on identifying 'race subspaces' within the model activations show promise in reducing biases.
Read Full Article
6 Likes
For uninterrupted reading, download the app