Just because AI can do something doesn’t mean it should, especially in social impact work.

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Core Points

• Key ethical considerations:
  • Bias - AI reflects the data it’s trained on.
  • Privacy - sensitive data must be protected.
  • Transparency - people should know when AI is involved.
• Best practices:
  • Data minimization - only share what’s necessary.
  • Human-in-the-loop - people make final decisions.
  • Clear escalation paths to real humans.
• Policy basics:
  • Define what AI can and cannot be used for.
  • Train staff on responsible usage.
  • Review tools regularly as they evolve.
• Long-term thinking:
  • AI should support equity, not reinforce existing gaps.

Example:

A nonprofit paused an AI chatbot rollout until consent and data handling standards were clearly defined.

Practical Takeaway

Responsible AI builds trust; irresponsible AI erodes it quickly.