Robustness
AIGP glossary · Last reviewed: · By Victor Humenhuk (AIGP certified)
Robustness - Performance maintained under stress: noisy, unexpected, adversarial or shifting inputs.
In the AIGP body of knowledge, Robustness comes up under Module 8: AI Governance Vocabulary.
Robustness in context
- Know all five (mnemonic: Inclusive Humans Trust Robust Accountability) and that [[Robustness (OECD)]] is achieved by ==traceability== plus a ==risk management approach== - two methods, not one. (The five OECD AI Principles)
- Major AI laws converge on eight obligations for high-risk AI: risk management, data governance, technical documentation, record-keeping, transparency, human oversight, accuracy/robustness/cybersecurity, and impact/conformity assessment. (The eight requirements for high-risk AI)
- Testing is continuous, risk-tailored and documented - test for ==accuracy, robustness, reliability, privacy, interpretability, safety, security and bias==. (Testing and Validation)
Where Robustness is covered in the AIGP study notes
Related terms
- Fairness
- Safety
- Reliability
- Fail-safe plans
- Model card
- System card
- Watermarking
- Automated decision-making (ADM)
- Open-source software
Test yourself on Robustness
Recognising a definition is not the same as applying it in an exam scenario. Work through the free AIGP practice questions, or read the full AIGP study guide - every study note is free.