AI Briefing#bias
The latest AI and developer news about #bias, with the original source and a short summary.
The latest AI and developer news about #bias, with the original source and a short summary.
A preprint testing 20 arguments across four models finds that attributing arguments to experts in unrelated fields reduces perceived credibility compared to having no source.
A study has found that Abliteration, the removal of censorship in LLMs, shifts a model's response attitude toward being more optimistic and confident.
This piece defines AI safety based on the principles of algorithmic fairness and presents the types of risks companies face along with response strategies.
ChatGPT is useful, but important decisions require human review and source verification.
Hallucination, bias, jailbreaking, and sycophancy in generative AI are threatening safety and trust.
OpenAI analyzed whether ChatGPT shows gender or racial bias based on users' names, and found that cases reflecting harmful stereotypes were under 1%.
Introduces Hugging Face's tools and guidance for identifying and mitigating bias throughout the entire machine learning development process.