Recommended Structure
Format: Live online (Zoom or equivalent)
Length: One week (three touchpoints)
Capacity: Up to 25 attendees
Online Tools Provided:
Session 1 — Intro + Q&A (≈60 min)
Establish shared concepts and an evaluation framework
Session 2 — Office Hour / Open Lab (≈60 min)
Bring local concerns, community scenarios, and tool questions for guided discussion
Session 3 — Follow-up Discussion + Reflections (≈60 min)
Translate the framework into practical decision-making and staff talking points
This offering equips staff to respond to common community concerns about AI: who benefits, who is harmed, and what libraries should do about it. We explore algorithmic bias through concrete examples, discuss access and cost barriers, and review environmental considerations at a high level. Participants learn a usable equity framework for evaluating AI tools and services in a library context, including accessibility, language, disability, age, and socioeconomic factors.
Who it's for
- Public-facing staff responding to community questions about AI impacts
- Managers and project leads evaluating new tools or vendors
- Anyone responsible for equity, access, and inclusion considerations
What you'll learn
- How to explain algorithmic bias using clear, real-world examples
- How access and cost barriers show up in AI tools and services
- A high-level view of environmental considerations and trade-offs
- A practical equity framework for evaluating AI in library contexts
- Key dimensions to assess: accessibility, language, disability, age, and socioeconomic factors
Leave with
- A usable equity lens for evaluating AI tools and services
- Clear language for addressing bias, access, and impact questions
- A shared approach for discussing trade-offs transparently and ethically