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Ethical AI for charities and membership organisations: A governance guide

by Hart Square June 10, 2025
Charity
Education
Healthcare
Membership
AI

Understanding ethical AI challenges

Key ethical considerations

1.Transparency and trust A Twilio survey revealed a significant perception gap:

  • 83% of organisations believe they are transparent about AI use
  • Only 38% of end-users perceive this transparency²

As Alan Perestrello from Hart Square notes in the AI Governance and Ethical Considerations Webinar (November 2024): “There is a gap that the sector needs to acknowledge and address. Organisations are likely doing significant work on internal processes and governance, but this may not be clear to stakeholders.”

2. Bias and fairness AI systems can inadvertently perpetuate or create new forms of bias:

Alex Skinner of Pixl8 Group highlighted the importance of understanding AI’s limitations in the AI Tools and Best Practices Webinar (January 2025): “When we see lots of examples around content generation and writing, it makes us feel that AI couldn’t possibly handle rules-based tasks. But actually, that’s where some of the best applications lie.”

Practical steps:

  • Examine training data for potential discriminatory patterns
  • Regularly audit AI decision-making processes
  • Ensure diverse representation in AI development and oversight

3. Data privacy and security

Protecting member and donor information is paramount:

  • Implement robust data governance frameworks
  • Ensure compliance with GDPR and sector-specific regulations
  • Develop clear protocols for data usage and protection

Developing an AI governance framework

Essential components

1.Establish an AI oversight committee

  • Create a cross-functional team
  • Include representatives from:
  • Leadership
  • Technology
  • Operations
  • Ethical compliance
  • Frontline services

2.Create a comprehensive AI policy

Key policy elements:

  • Clear objectives and scope
  • Ethical principles
  • Risk management strategies
  • Usage guidelines
  • Compliance mechanisms

Practical implementation approach

Carolyn Brown from the BMA shared her organisation’s approach in the AI Strategy Webinar (September 2024): “We developed an AI charter owned by the executive, spelling out our responsibility for the safe use of AI, looking to understand both the risks and opportunities.”

Risk management strategies

Identifying and mitigating risks

1.Operational risks

  • System reliability
  • Performance consistency
  • Potential errors in AI-generated outputs

2. Reputational risks

  • Loss of stakeholder trust
  • Potential negative publicity
  • Misalignment with organisational values

3. Cultural risks

  • Staff resistance to change
  • Concerns about job displacement
  • Lack of AI literacy

Building AI literacy and culture

Change management approach

Gous Uddin from Curve Digital recommends in the AI Governance and Ethical Considerations Webinar (November 2024): “Form a self-organised AI interest group with a diverse mix of people. The key is that it’s not a top-down approach – create a safe space for members to experiment, be open, and become change agents.”

Practical steps:

  • Provide comprehensive AI training
  • Create learning communities
  • Encourage experimentation
  • Develop clear communication strategies

Balancing innovation and ethical considerations

Alignment with organisational mission

Alex Skinner offers valuable insight in the AI Tools and Best Practices Webinar (January 2025): “It’s about understanding the art of the possible. We need to look beyond the initial hype and understand how AI can genuinely help us solve real organisational challenges.”

Evaluation criteria:

  • Does this AI initiative directly support our mission?
  • Can we measure its positive impact?
  • Does it enhance our ability to serve members or beneficiaries?

Measuring ethical AI performance

Governance metrics

  • Transparency scores
  • Bias detection rates
  • Staff and stakeholder trust indicators
  • Mission alignment assessments

Practical next steps

  1. Conduct an ethical AI readiness assessment
  2. Develop your AI governance charter
  3. Create an AI literacy programme
  4. Implement pilot projects with clear ethical guidelines

Get support

Connect with experts

Citations

  1. Charity Digital Skills Report 2024
  2. Twilio Non-Profit Digital Communications Survey 2024

Disclaimer: AI technologies evolve rapidly. This guide represents best practices as of March 2025.

Part of Hart Square’s AI Resource Series for Non-Profit Organisations