AI SESSIONS

Getting Real Results with AI: Objective-Centered Strategies for Librarians and Educators
A Library 2.0 / Learning Revolution Workshop with Reed Hepler

OVERVIEW

One of the biggest frustrations for librarians and educators integrating AI is the tendency to use these tools simply because they are available — resulting in wasted time, superficial outputs, and results that don’t actually advance real professional or learning goals. This workshop teaches the discipline of objective-centered AI use: starting every interaction with a clear purpose and ensuring AI truly serves human objectives rather than the other way around.

Understanding the distinction between objective-centered and tool-centered approaches carries profound implications for professional work quality, efficiency, and ethical practice. When librarians and faculty begin with objectives—supporting a specific patron need, achieving a particular learning outcome, completing a defined research task—they position themselves to evaluate whether AI collaboration genuinely advances that goal or merely produces impressive-looking content that misses the mark. This workshop provides practical frameworks for defining objectives with sufficient specificity to guide AI interactions productively, including the COSTAR framework (Context, Objective, Style, Tone, Audience, Response) and decision matrices for evaluating AI feasibility. Participants will learn to recognize when their objectives require human expertise that AI cannot replicate, when AI collaboration can enhance efficiency without compromising quality, and when the effort required to guide AI toward an objective exceeds the effort of completing the task through traditional methods. The workshop models the principle that AI tools should serve human objectives rather than humans serving AI capabilities.

By the conclusion of this workshop, participants will possess a systematic approach to objective-centered AI collaboration that they can apply across all professional contexts. Attendees will leave with objective definition templates, AI feasibility assessment tools, conversation steering techniques that maintain focus on goals rather than AI suggestions, and strategies for teaching students to approach AI use with clear purposes rather than vague hopes for assistance.

Participants will understand how to evaluate whether AI-generated outputs actually fulfill their stated objectives or merely approximate them in ways that require more correction than starting from scratch would have demanded. Most importantly, participants will recognize that objective-centered practice represents the foundation of all other AI literacy competencies—without clear objectives, verification becomes impossible, ethical evaluation lacks criteria, and collaboration devolves into passive consumption of whatever the AI produces. This workshop ensures that participants leave equipped to use AI deliberately and purposefully rather than experimentally and reactively.

LEARNING OBJECTIVES: Participants will be able to

• Articulate specific, measurable objectives for professional tasks before engaging with AI tools, using frameworks that clarify purpose, audience, context, and success criteria
• Evaluate AI feasibility for defined objectives by assessing whether AI collaboration will enhance efficiency and quality compared to traditional methods or alternative approaches
• Apply conversation steering techniques that maintain focus on stated objectives throughout AI interactions, resisting AI-generated tangents or suggestions that drift from the original purpose
• Assess AI outputs against stated objectives using criteria that distinguish between genuine objective fulfillment and superficial approximation requiring substantial revision

The recording and presentation slides will be available to all who register. 

DATE: Tuesday, July 14th, 2026, 2:00 - 3:30 pm US - Eastern Time