• Seattle Skeptics on AI
Seattle Skeptics on AI

Tag: bias evaluation

Measuring Bias and Fairness in Large Language Models: Standardized Protocols Explained
Measuring Bias and Fairness in Large Language Models: Standardized Protocols Explained

Tamara Weed, Jan, 15 2026

Standardized protocols for measuring bias in large language models use audit tests, embedding analysis, and text evaluation to detect unfair patterns. Learn how these tools work, which ones are most effective, and how to start using them today.

Categories:

Science & Research

Tags:

LLM bias fairness in AI bias evaluation AI auditing language model fairness

Recent post

  • Prompt Sensitivity in Large Language Models: Why Small Word Changes Change Everything
  • Prompt Sensitivity in Large Language Models: Why Small Word Changes Change Everything
  • Generative AI in Business Operations: High-Impact Use Cases and Real Implementation Patterns
  • Generative AI in Business Operations: High-Impact Use Cases and Real Implementation Patterns
  • Practical Applications of Generative AI Across Industries and Business Functions in 2025
  • Practical Applications of Generative AI Across Industries and Business Functions in 2025
  • Parameter Counts in Large Language Models: Why Size and Scale Matter for Capability
  • Parameter Counts in Large Language Models: Why Size and Scale Matter for Capability
  • Anti-Pattern Prompts: What Not to Ask LLMs in Vibe Coding
  • Anti-Pattern Prompts: What Not to Ask LLMs in Vibe Coding

Categories

  • Science & Research

Archives

  • January 2026
  • December 2025
  • November 2025
  • October 2025
  • September 2025
  • August 2025
  • July 2025

Tags

vibe coding generative AI large language models AI coding tools prompt engineering AI compliance AI governance LLM security AI coding transformer models AI code security AI implementation GitHub Copilot Parapsychological Association psi research paranormal studies psychic phenomena parapsychology no-code apps knowledge worker productivity

© 2026. All rights reserved.