SOP-1053-01-AI_Ethical-Risk-Assessment-and-Mitigation
Title: Ethical Risk Assessment & Mitigation
Effective Date: 2025-01-30
Previous Version: None
Reason for Update: New SOP for AI compliance and ethics
Owner: Chief Ethics & Compliance Officer (CECO)
Signature/Date:
Signature on File / 2025-01-30
Objective
This Standard Operating Procedure (SOP) defines the methodology and responsibilities for conducting Ethical Risk Assessments and formulating Mitigation Plans for AI-related projects throughout the AI-SDLC lifecycle. It establishes guidelines to ensure that potential ethical, privacy, and safety concerns are identified, assessed, and appropriately mitigated before and after model deployment.
Scope
This SOP applies to all AI system or feature releases managed under the AI-SDLC, especially those requiring compliance with internal corporate policies, external regulatory constraints, or that directly involve personal data processing and autonomy. It is mandatory for all functional teams—including Development, Quality Assurance, Operations, and Product/Project Management—whenever an AI model or AI-driven solution is planned, developed, tested, and deployed.
Applicable To
- AI-IRB Liaison
- AI Ethics Committee
- Product Management
- Development Team
- Quality Assurance Team
- Operations Team
- Legal & Compliance
- Data Protection Officer (DPO)
Sections
- Roles and Responsibilities
- Definitions
- Procedure Activities
- Metrics and Reporting
- Forms and Records
- References
- Revision History
1. Roles and Responsibilities
| Role | Responsibility |
|---|---|
| Product Management | Initiates ethical risk evaluation during product ideation; ensures sufficient resources for risk analysis. |
| Development Team | Documents technical aspects, user stories, and any potential ethical impact or risk triggers from the solution. |
| AI Ethics Committee | Performs thorough review of ethical risk; sets risk thresholds and approves or escalates mitigation strategies. |
| AI-IRB Liaison | Coordinates with AI-IRB to ensure compliance with applicable ethical guidelines. |
| Quality Assurance | Verifies the ethical risk assessment steps are completed as part of the AI-SDLC gating processes. |
| Operations Team | Implements environment controls and ensures mitigation tactics are enforced in production. |
| Legal & Compliance | Reviews regulatory and legal obligations. Advises on data protection, liability, and other compliance concerns. |
| Data Protection Officer (DPO) | Conducts privacy impact assessments; ensures alignment with data-protection laws (GDPR, etc.). |
2. Definitions
- Ethical Risk Assessment: A structured process to identify moral, social, privacy, safety, or fairness concerns in an AI solution.
- Mitigation Plan: A formal document describing actions to reduce or eliminate identified risks, including responsibilities, deadlines, and required resources.
- AI-IRB: Internal Review Board for AI-related research or product releases, focusing on potential societal and ethical impacts.
- Risk Threshold: The maximum acceptable level or severity of ethical risk that can be tolerated before mitigation is mandatory.
- Authorized AI Agent: A validated AI system or subsystem identified within the Mind Matrix as having the authority to execute specific SDLC or operational tasks.
3. Procedure Activities
3.1. Risk Identification
- Product Management notifies AI Ethics Committee, AI-IRB Liaison, and DPO at project initiation (Gate 12).
- Development Team provides technical documentation, including a data-flow diagram, potential bias sources, recursive self-improvement subroutines, and any known ethically sensitive features.
- AI Ethics Committee uses domain experts, guidelines from prior SOPs, and frameworks like the Ethical AI Checklist to identify potential risk areas (e.g., bias, discrimination, privacy breach).
3.2. Risk Analysis and Prioritization
- AI Ethics Committee convenes to classify each risk factor by:
- Probability: Likelihood of negative outcome
- Impact: Consequence severity on users, society, or environment
- If AI-IRB involvement is required, AI-IRB Liaison handles additional reviews or external consultations.
- DPO evaluates privacy-specific risks (data usage, data residency, retention).
3.3. Mitigation Plan Development
- AI Ethics Committee drafts the Mitigation Plan:
- Defines recommended controls (technical, procedural, contractual).
- Assigns owners and timelines.
- Aligns with the overall project schedule.
- Development Team validates feasibility of recommended changes (e.g., additional logging, bias correction methods).
- Product Management ensures allocated budget/time for implementing mitigation tasks.
3.4. Approval and Execution
- Legal & Compliance and Operations review the Mitigation Plan to ensure regulatory compliance and feasibility in production.
- AI Ethics Committee finalizes the plan and obtains sign-off from Project Sponsor or designated authority if the risk rating is high.
- The Development Team and Operations implement the mitigations (e.g., injecting fairness constraints, using privacy-preserving technologies).
- Quality Assurance adds mitigation verification checks, integrating Exochain Peer Reviews for fairness and security validation, as part of final acceptance gating prior to release.
3.5. Post-Deployment Evaluation
- Quality Assurance and Operations monitor risk indicators in the live environment.
- AI-IRB Liaison consults with AI Ethics Committee if any newly discovered risk emerges that may exceed the risk threshold.
- All stakeholders perform a formal review at the next Post Implementation or scheduled checkpoint to see if additional mitigations are required.
4. Metrics and Reporting
| Metric | Definition | Reporting Frequency |
|---|---|---|
| Number of Identified Ethical Risks | Total count of discovered ethical risks per project | Gate 6 and Gate 2 |
| Time to Mitigate | Elapsed days between risk acceptance and closure | Monthly |
| Unresolved Risk Count | Any open or high-severity risk items not yet mitigated | Weekly (Scrum metric) |
| Compliance Incidents | # of potential compliance or ethical incidents post-deployment | As needed |
5. Forms and Records
- Ethical Risk Identification Form: Captures the nature, probability, and impact rating.
- Mitigation Plan Template: Documents recommended solutions, responsibilities, and deadlines.
- Post-Deployment Ethical Incident Record: Used to log newly discovered or escalated risks after go-live.
6. References
- SOP-1000-01-AI (AI-SDLC Overview)
- SOP-1003-01-AI (Configuration Management for AI Projects)
- Global Data Protection Regulation (GDPR)
- IEEE Ethically Aligned Design
- AI-IRB Committee Guidelines (internal corporate policy)
7. Revision History
| Version | Date | Changes | Approved By |
|---|---|---|---|
| 1.0 | 2025-01-30 | Initial issue (new AI ethical risk SOP) | Chief Ethics & Compliance Officer |
End of SOP 1053-01-AI
@startuml
title SOP-1053-01-AI: Ethical Risk Assessment & Mitigation
skinparam participantMargin 20
skinparam participantPadding 10
skinparam boxPadding 10
participant “Product Management” as PM
participant “Development Team” as DEV
participant “AI Ethics Committee” as AIETHICS
participant “AI-IRB Liaison” as AIIRB
participant “Data Protection Officer” as DPO
participant “Legal & Compliance” as LEGAL
participant “Operations Team” as OPS
participant “Quality Assurance” as QA
participant “Project Sponsor” as SPONSOR
PM -> AIETHICS: Notify of new AI project\nInitiate risk evaluation
AIETHICS -> DEV: Request technical docs, user stories\nand potential ethical concerns
DEV -> AIETHICS: Provide design specs,\nbias sources, and data-flow diagram
AIETHICS -> DPO: Forward docs for privacy review
DPO -> AIETHICS: Evaluate privacy risk\n(impact, compliance)
AIETHICS -> AIIRB: If external IRB needed,\ninitiate formal review
note over AIETHICS,AIIRB: Potential external or specialized IRB steps
AIIRB -> AIETHICS: Provide additional\nrequirements or constraints
AIETHICS -> AIETHICS: Identify and classify\nethical risk factors
AIETHICS -> LEGAL: Review legal/regulatory\nimplications
LEGAL -> AIETHICS: Provide compliance advice
AIETHICS -> AIETHICS: Develop Mitigation Plan\n(technical & procedural controls)
AIETHICS -> DEV: Consult feasibility of\nproposed solutions
DEV -> AIETHICS: Confirm feasibility,\nresource needs, timeline
AIETHICS -> PM: Present Mitigation Plan\nfor resource allocation
PM -> OPS: Ensure budget/time is assigned\nfor mitigation tasks
OPS -> PM: Confirm operational readiness
AIETHICS -> LEGAL: Final check for\nregulatory compliance
LEGAL -> AIETHICS: Approve or recommend changes
alt High Risk
AIETHICS -> SPONSOR: Request sign-off on high-risk mitigations
SPONSOR -> AIETHICS: Sign-off granted
else Acceptable
note over AIETHICS: No sponsor sign-off needed
end
DEV -> QA: Implement & test mitigation steps
QA -> QA: Verify mitigation as part of\nacceptance gating
OPS -> OPS: Deploy final solution with\nethical safeguards
OPS -> QA: Provide risk monitoring data\npost-deployment
QA -> AIETHICS: Evaluate new or\nescalated risks
AIETHICS -> AIIRB: Escalate if new risk\nexceeds threshold
AIETHICS -> AIETHICS: Update or refine\nMitigation Plan as needed
@enduml
Short textual explanation:
This diagram shows how Product Management notifies the AI Ethics Committee of a new AI project. The committee obtains technical details from Development, coordinates privacy checks with the DPO, and possibly involves the AI-IRB Liaison. Ethical risks are identified, then the committee proposes mitigations. Legal & Compliance reviews for regulatory alignment, and the Project Sponsor may need to sign off if the risk is high. Development and Operations implement changes, while Quality Assurance verifies them. Finally, post-deployment monitoring handles any newly discovered risks.