Responsible Disclosure
The practice of reporting AI vulnerabilities, biases, or safety issues to the appropriate parties before making them public, giving developers time to fix issues before they can be exploited.
Why It Matters
Responsible disclosure protects users while still ensuring transparency. It balances the public's right to know with the need to fix problems before they are exploited.
Example
A researcher who discovers a jailbreak technique for a major LLM privately notifying the AI company, giving them 90 days to patch it before publishing the findings.
Think of it like...
Like finding a security flaw in a building and telling the owner before posting it online — giving them a chance to fix it before others can exploit it.
Related Terms
AI Safety
The research field focused on ensuring AI systems operate reliably, predictably, and without causing unintended harm. It spans from technical robustness to long-term existential risk concerns.
Red Teaming
The practice of systematically testing AI systems by attempting to find failures, vulnerabilities, and harmful behaviors before deployment. Red teamers actively try to break the system.
AI Governance
The frameworks, policies, processes, and organizational structures that guide the responsible development, deployment, and monitoring of AI systems within organizations and across society.