Join us on May 22, 2024 at the HITS conference for a working discussion during lunch of the myriad facets of an AI Governance model and how to institute one.
We’ll start with an introduction on building governance model similar to a PMO function and understanding the stakeholder implications. With brainstorming aids at the tables, we ask four questions with in 5 minute breakout sessions and take 5 minutes to recap them:
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- What do think an AI Governance program objectives should be (business outcome)?
- Caution on creating LLM’s
- Project approval
- Risk mitigation plans
- oversight
- What goals should the program consider when evaluating projects? What are the criteria against which you measure an AI project for “worthiness”?
- Standard Portfolio Management criteria
- Fairness, transparency, etc.
- Who are your major stakeholders whose point of view should be considered?
- More than BU & HR
- What risks or issues might you have to mitigate as part of the AI Governance program?
- Data estate
- Data gaps (unrepresented communities in historical data)
- A caution that “just because I can, doesn’t mean I should”
- What do think an AI Governance program objectives should be (business outcome)?
We’ll wrap up with a recap of the discussion takeaways and provide a QR code for this page.
Resources: