In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI

A research paper published on ResearchGate examines third-party evaluation frameworks for identifying flaws in general-purpose AI systems beyond internal testing. Casey Ellis contributes analysis on robust disclosure mechanisms needed to ensure comprehensive vulnerability detection in large language models and similar AI technologies.