How Nonprofits Can Build an Algorithm Review Board for AI Governance
As nonprofits adopt AI tools, establishing formal governance structures becomes essential. An Algorithm Review Board (ARB) provides systematic oversight, ensures ethical implementation, and protects the communities you serve while building stakeholder trust.
As AI becomes integral to nonprofit operations, organizations need structured governance to ensure technology serves their mission ethically and effectively. An Algorithm Review Board (ARB)—sometimes called an AI Ethics Committee or AI Governance Board—provides the oversight, accountability, and expertise needed to make responsible AI decisions.
Unlike ad-hoc AI decisions made by individual staff members, an ARB creates a formal process for evaluating AI tools, assessing risks, preventing bias, and ensuring alignment with organizational values. This systematic approach is especially important for nonprofits, which serve vulnerable populations and operate under heightened scrutiny from donors, beneficiaries, and regulators.
This guide walks you through establishing an Algorithm Review Board tailored to nonprofit needs, from initial setup through ongoing operations. Whether you're just beginning your AI journey or already using multiple AI tools, an ARB helps you scale responsibly and maintain trust with stakeholders.
Why Algorithm Review Boards Matter for Nonprofits
Nonprofits face unique challenges when implementing AI. An ARB addresses these challenges systematically, ensuring AI serves your mission rather than creating new problems.
Risk Mitigation
AI systems can perpetuate bias, violate privacy, or make decisions that harm vulnerable populations. An ARB identifies these risks before deployment, protecting your organization and the communities you serve.
Mission Alignment
Every AI tool should advance your mission. An ARB ensures AI decisions align with organizational values and don't compromise the trust and relationships essential to nonprofit success.
Stakeholder Trust
Donors, beneficiaries, and partners need confidence that you're using AI responsibly. A formal ARB demonstrates commitment to ethical AI and provides transparency that builds trust.
Compliance & Accountability
As AI regulations evolve, nonprofits need documented processes for AI governance. An ARB creates accountability structures and helps ensure compliance with privacy laws, grant requirements, and ethical standards.
The Cost of Unchecked AI
Without proper governance, nonprofits risk:
- Bias in donor segmentation or program participant selection that excludes marginalized communities
- Privacy violations that breach donor or beneficiary trust
- AI-generated content that misrepresents your mission or creates legal issues
- Vendor relationships that compromise data security or ethical standards
What is an Algorithm Review Board?
An Algorithm Review Board is a cross-functional governance body responsible for reviewing, approving, and monitoring AI systems used by your organization. Think of it as your nonprofit's internal ethics committee for technology decisions.
The ARB's primary functions include:
Pre-Deployment Review
Evaluate proposed AI tools and use cases before implementation, assessing risks, benefits, and alignment with organizational values.
Bias & Fairness Assessment
Test AI systems for bias, discrimination, and fairness issues, especially when AI decisions affect program participants, donors, or communities.
Ongoing Monitoring
Regularly review AI system performance, outcomes, and impacts to ensure continued ethical operation and mission alignment.
Policy Development
Create and maintain AI governance policies, guidelines, and best practices that guide responsible AI use across your organization.
Incident Response
Investigate and respond to AI-related issues, bias complaints, or system failures, ensuring accountability and continuous improvement.
An ARB is distinct from an IT committee or technology advisory group. While those bodies focus on technical implementation, an ARB focuses on ethical, legal, and mission-aligned AI use. It bridges technical expertise with organizational values, ensuring AI serves your mission responsibly.
Building Your Algorithm Review Board
Creating an effective ARB requires thoughtful composition, clear structure, and defined processes. Here's how to build one that fits your nonprofit's size, capacity, and needs.
1. Determine Board Composition
Your ARB should include diverse perspectives that reflect both technical expertise and organizational values. For most nonprofits, a 5-7 person board works well.
Core Members (Required)
- Executive Sponsor: Senior leadership (ED, COO, or board member) who provides authority and resources
- Program Staff: Someone who understands your mission and beneficiary needs
- Data/IT Representative: Person familiar with your data systems and technical capabilities
- Legal/Compliance: Staff member or external advisor who understands privacy laws and regulations
Recommended Additional Members
- Community Representative: Beneficiary, volunteer, or community member who brings lived experience
- External AI Ethics Advisor: Consultant or academic with AI ethics expertise (can be part-time)
- Board Member: Trustee who can provide governance perspective and board-level accountability
Small Nonprofit Adaptation
If you have limited staff, your ARB can be smaller (3-4 people) with members serving multiple roles. You might also consider partnering with other nonprofits to share an external AI ethics advisor, or engaging a consultant on a project basis. The key is ensuring diverse perspectives, not having a large team.
2. Define Roles and Responsibilities
Clear roles prevent confusion and ensure accountability. Key positions include:
ARB Chair
Facilitates meetings, sets agendas, ensures follow-through on decisions, and serves as primary contact for AI-related questions. Should be someone with authority and organizational knowledge.
ARB Coordinator/Secretary
Manages documentation, tracks review requests, maintains records of decisions, and ensures ARB processes are followed. This can be a staff member who doesn't need deep AI expertise.
Technical Reviewer
Evaluates technical aspects of AI proposals: data requirements, system architecture, security, integration needs. May be your IT staff or an external technical consultant.
Ethics Reviewer
Assesses ethical implications, bias risks, fairness concerns, and mission alignment. Should understand your organization's values and the communities you serve.
3. Establish Review Processes
Define when and how AI proposals come to the ARB. Not every AI use case needs full board review—create a tiered system:
Low RiskTier 1: Expedited Review
Simple, low-impact AI tools
Examples: Grammar checkers, basic scheduling tools, simple content generation for internal use
Process: Staff member completes brief self-assessment form; ARB coordinator reviews and approves (or escalates if concerns)
Timeline: 1-2 business days
Medium RiskTier 2: Standard Review
AI tools that process personal data or affect stakeholders
Examples: Donor communication tools, volunteer management systems, program participant tracking
Process: Full ARB review with detailed proposal, risk assessment, and bias testing plan
Timeline: 1-2 weeks
High RiskTier 3: Comprehensive Review
AI systems making decisions about people or handling sensitive data
Examples: Program participant selection, resource allocation algorithms, automated eligibility determinations
Process: Full ARB review plus external expert consultation, community input, pilot testing, and board approval
Timeline: 4-8 weeks
ARB Review Framework
When reviewing AI proposals, your ARB should systematically evaluate multiple dimensions. Use this framework to ensure comprehensive assessment:
Mission Alignment
Does this AI tool advance your mission? Will it help you serve beneficiaries better, or is it primarily for organizational convenience?
- How does this AI use case connect to your strategic goals?
- What problem does it solve, and is AI the right solution?
- Are there non-AI alternatives that might be more appropriate?
Bias & Fairness
AI systems can perpetuate or amplify existing biases. Assess potential discrimination risks, especially for vulnerable populations.
- What training data will be used, and does it represent your community?
- How will you test for bias across different demographic groups?
- What safeguards prevent discriminatory outcomes?
- For more on bias prevention, see our guide on ethical AI implementation
Privacy & Data Security
Evaluate data handling, security measures, and compliance with privacy regulations.
- What personal data will be processed, and is it necessary?
- How is data encrypted, stored, and accessed?
- Does the vendor meet compliance requirements (GDPR, HIPAA, etc.)?
- Learn more in our comprehensive guide on data privacy and security
Transparency & Explainability
Can you explain how the AI makes decisions? Stakeholders need to understand AI use, especially when it affects them.
- How will you disclose AI use to stakeholders?
- Can the AI system explain its decisions?
- What human oversight mechanisms are in place?
Vendor Assessment
Evaluate the AI vendor's ethics, security practices, and alignment with your values.
- Does the vendor have ethical AI policies and practices?
- What security certifications do they hold?
- How do they handle bias testing and model transparency?
- See our detailed vendor selection guide for comprehensive evaluation criteria
Risk Assessment
Identify potential harms and mitigation strategies before deployment.
- What could go wrong, and who could be harmed?
- What's the worst-case scenario, and how likely is it?
- What safeguards and monitoring will prevent or detect problems?
- What's the plan if something goes wrong?
Implementation Steps
Ready to establish your ARB? Follow these steps to get started:
Get Leadership Buy-In
Present the ARB concept to your executive director and board, explaining why governance matters and how it protects your organization. Frame it as risk management and mission protection, not bureaucracy.
Assemble Your Board
Recruit ARB members based on the composition guidelines above. Start with a core group of 3-5 people; you can expand as needed. Ensure you have executive sponsorship and diverse perspectives.
Draft ARB Charter
Create a charter document that defines the ARB's purpose, scope, membership, decision-making authority, and processes. This formalizes the board and provides clarity for staff.
Develop Review Templates
Create standardized forms for AI proposals that capture the information needed for review: use case description, data requirements, risk assessment, vendor information, etc. This makes the process efficient and consistent.
Establish Meeting Cadence
Set regular meeting schedule (monthly or quarterly) and define how urgent reviews are handled. Create a process for staff to submit proposals and track review status.
Conduct Retroactive Review
Review existing AI tools already in use. This helps you understand current AI footprint, identify risks, and establish baseline governance. Prioritize high-risk systems first.
Train Staff
Educate staff about the ARB process, when to submit proposals, and why governance matters. Make it easy for people to engage with the ARB, not intimidating.
Start Reviewing
Begin with your first proposal. Use it as a learning opportunity to refine your process. Document decisions and learnings to improve future reviews.
Ongoing ARB Operations
An ARB isn't a one-time setup—it requires ongoing attention to remain effective. Here's how to maintain and evolve your governance:
Regular Monitoring
Periodically review approved AI systems to ensure they continue operating ethically and effectively:
- • Quarterly performance reviews for high-risk systems
- • Annual comprehensive audits of all AI tools
- • Monitor for bias, accuracy, and mission alignment
- • Track outcomes and impacts on beneficiaries
Policy Updates
Keep governance policies current as AI technology and regulations evolve:
- • Update review frameworks based on learnings
- • Revise risk tiers as you gain experience
- • Incorporate new regulations and best practices
- • Document decisions and create institutional knowledge
Staff Education
Continuously build AI literacy and ethical awareness across your organization:
- • Regular training on AI ethics and governance
- • Share ARB decisions and learnings with staff
- • Create resources and guidelines for responsible AI use
- • Encourage questions and feedback about AI systems
Transparency & Reporting
Maintain transparency about your AI governance with stakeholders:
- • Report ARB activities to board and leadership
- • Share governance approach with donors and funders
- • Disclose AI use to beneficiaries when appropriate
- • Document governance practices for grant applications
Common Challenges and Solutions
Establishing an ARB isn't always smooth. Here are common challenges nonprofits face and how to address them:
Challenge: "We don't have AI expertise"
Solution: You don't need deep technical expertise to start. Focus on mission alignment, ethics, and risk assessment—these are nonprofit strengths. Consider engaging an external AI ethics consultant for technical questions, or partner with other nonprofits to share expertise.
Challenge: "ARB will slow us down"
Solution: Use tiered review processes so low-risk tools get fast-tracked. Most approvals should be quick—the ARB prevents problems, not progress. Document common approvals to create templates that speed future reviews.
Challenge: "Staff will bypass the ARB"
Solution: Make the ARB process easy, not burdensome. Provide clear templates, quick turnaround for low-risk items, and support staff through the process. Executive sponsorship ensures ARB decisions are respected.
Challenge: "We're too small for formal governance"
Solution: Start simple. A 3-person ARB that meets quarterly is better than no governance. Use lightweight processes and templates. You can always expand as you grow.
Integrating ARB with Other Governance
Your ARB should connect with existing governance structures. Here's how it fits:
Board of Directors
The ARB reports to the board on AI governance activities, high-risk decisions, and policy changes. Include a board member on the ARB to ensure alignment and accountability.
Executive Leadership
Executive sponsorship is essential. The ARB should have clear authority to approve or reject AI proposals, with escalation to leadership for major decisions.
IT/Technology Committees
Coordinate with IT governance to ensure technical feasibility and security. The ARB focuses on ethics and mission; IT focuses on implementation and security.
Program & Mission Teams
Program staff should be represented on the ARB to ensure beneficiary perspectives are considered. The ARB should consult with program teams when evaluating use cases that affect service delivery.
Your ARB complements existing governance by adding AI-specific expertise and processes. It doesn't replace other committees—it ensures AI decisions receive appropriate ethical and mission-focused oversight. For more on building comprehensive AI readiness, see our AI readiness checklist.
Conclusion: Governance as Foundation
An Algorithm Review Board provides the structured governance nonprofits need to use AI responsibly. It's not about creating bureaucracy—it's about protecting your mission, your stakeholders, and the communities you serve while enabling confident AI adoption.
Start small, learn as you go, and evolve your ARB to fit your organization's needs. The most important step is beginning: establishing formal oversight, even in a lightweight form, demonstrates commitment to responsible AI and builds the foundation for ethical technology use.
As AI becomes more central to nonprofit operations, governance becomes more critical. An ARB helps you scale AI use confidently, knowing that each tool has been evaluated for ethics, bias, privacy, and mission alignment. This systematic approach protects your organization's reputation, maintains stakeholder trust, and ensures technology serves your mission rather than creating new problems.
For nonprofits committed to responsible AI, an Algorithm Review Board isn't optional—it's essential. It's the difference between ad-hoc AI adoption and strategic, ethical technology use that advances your mission while protecting the people you serve.
Related Resources
Ethical AI Implementation
Comprehensive guide to using AI ethically and transparently
Data Privacy & Security
Essential practices for protecting data when deploying AI
Vendor Selection
How to evaluate AI vendors for ethics and security
AI Readiness Checklist
Build comprehensive AI readiness including governance
Responsible AI Services
Learn about our responsible AI consulting services
Ready to Build Your Algorithm Review Board?
One Hundred Nights helps nonprofits establish AI governance structures that protect your mission while enabling confident technology adoption. We'll help you design an ARB that fits your organization, develop review processes, and build the capacity for ongoing ethical AI oversight.