6 Expert-Backed Claims on AI Risk Management
Following a workshop focused on risk management frameworks and risk thresholds for frontier AI, which brought together top experts in AI risk management and key policymakers, we present a set of expert-driven claims that emerged from the discussions. Below, you’ll find the claims that resulted from the conversations, along with the specific experts who endorse each one.
Claim 1
Frontier AI risk management frameworks should include elements of commonly used risk management standards and frameworks (e.g., in NIST AI RMF, and ISO/IEC 23894 & 42001), such as the following:
- Defining risk tolerances
- Performing risk assessmentsome text
- Identification of risks
- Analysis of identified risks
- Comparing risks to risk tolerance
- Implementing risk mitigation or other controls
- Monitoring risks
Endorsed by:
Siméon Campos (SaferAI), Henry Papadatos (SaferAI), Heather Frase, PhD, Bill Anderson-Samways (IAPS), Malcolm Murray
Claim 2
Risk analysis should include, though not be restricted to, a semi-quantitative or quantitative estimate of risk (i.e. severity and likelihood).
Endorsed by:
Siméon Campos (SaferAI), Henry Papadatos (SaferAI), Heather Frase, PhD, Bill Anderson-Samways (IAPS)
Claim 3
Risk identification should be done continuously throughout the training run and deployment, in a tight integration between red-teaming, monitoring and standard risk identification methods (e.g. Fishbone analysis, scenario analysis etc.) applied upon worrying findings.
Endorsed by:
Siméon Campos (SaferAI), Henry Papadatos (SaferAI), Heather Frase, PhD, Bill Anderson-Samways (IAPS), Malcolm Murray
Claim 4
In absence of government-set risk tolerance, frontier AI developers should define their risk tolerance in a quantitative or semi-quantitative way. Any substantial differences in tolerance to other industries should be clearly explained.
Endorsed by:
Siméon Campos (SaferAI), Henry Papadatos (SaferAI), Malcolm Murray.
Claim 5
Risk tolerance should be operationalized as a joint set of capabilities thresholds and mitigations objectives, with in-depth rationales for how those relate to the global risk thresholds.
Endorsed by:
Siméon Campos (SaferAI) , Henry Papadatos (SaferAI), Bill Anderson-Samways (IAPS), Malcolm Murray.
Claim 6
Risk assessments should be validated by independent third-party auditors or oversight organizations to ensure objectivity, rigor, and adherence to industry standards and best practices.
Endorsed by:
Siméon Campos (SaferAI), Henry Papadatos (SaferAI), Heather Frase, PhD, Bill Anderson-Samways (IAPS), Malcolm Murray.
