I Realized I Couldn't Trust AI With My Research

What happened

The author developed Research Council, an AI research tool that investigates technical questions by retrieving and verifying evidence from a curated knowledge base. The tool uses four parallel agents to examine evidence, verify claims, and deliver verdicts based on the reliability of the data. The system is designed to address the challenge of comparing different AI memory architectures and ensuring that conclusions are supported by reliable evidence.

Why it matters

Research Council is significant for AI developers and researchers because it provides a structured way to evaluate the validity of claims in AI research. This is crucial for building trust in AI systems, especially when they are used for memory-related tasks. The tool also emphasizes the importance of transparency and evidence-based reasoning in AI development, which is essential for creating reliable and trustworthy systems.

• Research Council is a tool that helps verify the validity of AI research claims by using a curated knowledge base and multiple agents.
• The system emphasizes the importance of evidence-based reasoning in AI development to avoid drawing unsupported conclusions.
• The tool ensures that claims are verified against the original sources, preventing the spread of unverified information.
• The approach highlights the need for transparency and structured evaluation in AI research.
• The system is efficient and can be used on free-tier AI models, making it accessible for researchers.

The bigger picture

Research Council has the potential to improve the reliability and transparency of AI research by ensuring that conclusions are based on verified evidence. This can lead to more trustworthy AI systems, especially in applications like memory assistance for individuals with dementia. The tool also encourages a more rigorous approach to evaluating AI architectures and their performance.

Research Council is a significant contribution to AI research, offering a structured and transparent way to evaluate claims and ensure that conclusions are supported by reliable evidence. The tool addresses the challenge of comparing different AI memory architectures and emphasizes the importance of evidence-based reasoning in building trustworthy AI systems.

Technical details

• Research Council uses a Sanity Knowledge Base to store and organize research papers and their metadata.
• The system employs four parallel agents: Researcher A, Researcher B, Contradiction Hunter, and Evidence Auditor.
• The tool verifies claims by cross-checking them against the original sources using deterministic code.
• The system delivers verdicts such as 'SUPPORTED', 'CONTRADICTED', or 'INSUFFICIENT EVIDENCE'.
• The tool is designed to run efficiently on Gemini's free tier, using only five model calls.

FAQ