Ethical Considerations & The Human-in-the-Loop
Protect your mission. Learn how to navigate AI bias, data privacy, and ethical deployment in this essential workshop for nonprofit leaders.
Innovation without integrity is a risk your nonprofit cannot afford.
Artificial Intelligence offers incredible power to scale your impact, but it also introduces new risks. From algorithmic bias that can harm vulnerable communities to data privacy breaches that erode donor trust, the "dark side" of AI is real.
But fear shouldn't stop you from innovating. It just means you need a framework.
Join Yacouba Traoré for a critical 2-hour workshop on AI Ethics & The Human-in-the-Loop. We move beyond philosophical debates to provide practical checklists and protocols for using AI safely in the Canadian nonprofit sector.
What You Will Learn:
- The "Black Box" Problem: Understanding how AI models make decisions and why they hallucinate.
- Bias & Equity: How to spot algorithmic bias in tools used for hiring, service delivery, and impact measurement.
- Data Sovereignty (PIPEDA): The difference between "Public" models (where your data trains the AI) and "Private" models (where your data stays yours).
- The Human-in-the-Loop: A framework for ensuring human oversight in every automated workflow.
The "Safety Shield" Bonus: All attendees will receive our exclusive "AI Vendor Vetting Checklist"—a PDF tool you can use to interrogate software salespeople and ensure any tool you buy aligns with your values.
Who Should Attend:
- Executive Directors concerned about reputation risk.
- Program Managers working with vulnerable client data.
- Marketing/Fundraising staff using AI for content.
- IT & Operations leads.
Cost: $100 CAD
Protect your mission. Learn how to navigate AI bias, data privacy, and ethical deployment in this essential workshop for nonprofit leaders.
Innovation without integrity is a risk your nonprofit cannot afford.
Artificial Intelligence offers incredible power to scale your impact, but it also introduces new risks. From algorithmic bias that can harm vulnerable communities to data privacy breaches that erode donor trust, the "dark side" of AI is real.
But fear shouldn't stop you from innovating. It just means you need a framework.
Join Yacouba Traoré for a critical 2-hour workshop on AI Ethics & The Human-in-the-Loop. We move beyond philosophical debates to provide practical checklists and protocols for using AI safely in the Canadian nonprofit sector.
What You Will Learn:
- The "Black Box" Problem: Understanding how AI models make decisions and why they hallucinate.
- Bias & Equity: How to spot algorithmic bias in tools used for hiring, service delivery, and impact measurement.
- Data Sovereignty (PIPEDA): The difference between "Public" models (where your data trains the AI) and "Private" models (where your data stays yours).
- The Human-in-the-Loop: A framework for ensuring human oversight in every automated workflow.
The "Safety Shield" Bonus: All attendees will receive our exclusive "AI Vendor Vetting Checklist"—a PDF tool you can use to interrogate software salespeople and ensure any tool you buy aligns with your values.
Who Should Attend:
- Executive Directors concerned about reputation risk.
- Program Managers working with vulnerable client data.
- Marketing/Fundraising staff using AI for content.
- IT & Operations leads.
Cost: $100 CAD
Good to Know (Highlights)
- 🛡️ Risk-Focused: We prioritize safety and compliance.
- 🇨🇦 Canadian Context: tailored to Canadian privacy laws and nonprofit standards.
- 🎥 Recording: All registrants receive the full recording and the Vetting Checklist.
Good to know
Highlights
- 2 hours
- Online
Refund Policy
Location
Online event
Agenda
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The Ethical Landscape
The "Speed vs. Safety" trade-off. Real-world examples of AI failures in the social sector (and how to avoid them).
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Data Privacy & Sovereignty
Public vs. Private: Understanding how LLMs (Large Language Models) use your data. Anonymization 101: Practical techniques to strip PII (Personally Identifiable Information) before prompting. The "Free Tool" Trap: Why free tools often cost you your data privacy.
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