Epistemic Blinding: An Inference-Time Protocol for Auditing Prior Contamination in LLM-Assisted Analysis

1. 1Identify the need for epistemic blinding in LLM-assisted analysis
2. 2Develop an agentic system that uses LLMs to reason across multiple datasets
3. 3Implement epistemic blinding as an inference-time protocol to audit prior contamination
4. 4Analyze the outputs to distinguish between data-driven inference and memorized priors

AI engineers and researchers working with large language models (LLMs) can benefit from epistemic blinding to improve the transparency and reliability of their models, while data scientists and analysts can use this protocol to audit and refine their LLM-assisted analysis

💡 Epistemic blinding can help distinguish between data-driven inference and memorized priors in LLM outputs

🔍 Epistemic blinding: a new protocol to audit prior contamination in LLM-assisted analysis #LLMs #AI