MAP-1.5—Organizational risk tolerances are determined and documented.
>Control Description
>About
Risk tolerance reflects the level and type of risk the organization is willing to accept while conducting its mission and carrying out its strategy.
Organizations can follow existing regulations and guidelines for risk criteria, tolerance and response established by organizational, domain, discipline, sector, or professional requirements. Some sectors or industries may have established definitions of harm or may have established documentation, reporting, and disclosure requirements.
Within sectors, risk management may depend on existing guidelines for specific applications and use case settings. Where established guidelines do not exist, organizations will want to define reasonable risk tolerance in consideration of different sources of risk (e.g., financial, operational, safety and wellbeing, business, reputational, and model risks) and different levels of risk (e.g., from negligible to critical).
Risk tolerances inform and support decisions about whether to continue with development or deployment - termed “go/no-go”. Go/no-go decisions related to AI system risks can take stakeholder feedback into account, but remain independent from stakeholders’ vested financial or reputational interests.
If mapping risk is prohibitively difficult, a "no-go" decision may be considered for the specific system.
>Suggested Actions
- Utilize existing regulations and guidelines for risk criteria, tolerance and response established by organizational, domain, discipline, sector, or professional requirements.
- Establish risk tolerance levels for AI systems and allocate the appropriate oversight resources to each level.
- Establish risk criteria in consideration of different sources of risk, (e.g., financial, operational, safety and wellbeing, business, reputational, and model risks) and different levels of risk (e.g., from negligible to critical).
- Identify maximum allowable risk tolerance above which the system will not be deployed, or will need to be prematurely decommissioned, within the contextual or application setting.
- Articulate and analyze tradeoffs across trustworthiness characteristics as relevant to proposed context of use. When tradeoffs arise, document them and plan for traceable actions (e.g.: impact mitigation, removal of system from development or use) to inform management decisions.
- Review uses of AI systems for “off-label” purposes, especially in settings that organizations have deemed as high-risk. Document decisions, risk-related trade-offs, and system limitations.
>Documentation Guidance
Organizations can document the following
- Which existing regulations and guidelines apply, and the entity has followed, in the development of system risk tolerances?
- What criteria and assumptions has the entity utilized when developing system risk tolerances?
- How has the entity identified maximum allowable risk tolerance?
- What conditions and purposes are considered “off-label” for system use?
AI Transparency Resources
>References
Board of Governors of the Federal Reserve System. SR 11-7: Guidance on Model Risk Management. (April 4, 2011).
The Office of the Comptroller of the Currency. Enterprise Risk Appetite Statement. (Nov. 20, 2019).
Brenda Boultwood, How to Develop an Enterprise Risk-Rating Approach (Aug. 26, 2021). Global Association of Risk Professionals (garp.org). Accessed Jan. 4, 2023.
Virginia Eubanks, 1972-, Automating Inequality: How High-tech Tools Profile, Police, and Punish the Poor. New York, NY, St. Martin's Press, 2018.
GAO-17-63: Enterprise Risk Management: Selected Agencies’ Experiences Illustrate Good Practices in Managing Risk. See Table 3.
>Topics
>Cross-Framework Mappings
Ask AI
Configure your API key to use AI features.