The surge of AI in the legal community gives the law librarian the chance to step up and make ourselves known. This opening panel will discuss the skills that law librarians can hone to become the leaders within the AI space and how the legal profession is changing. Unsure how to lead in this area? The panel will discuss upskilling paths and share experiences in certification and continued education.

MODERATOR:

• Rebecca Fordon, Assistant Professor of Practice and the Assistant Director of Innovation, Research & Instruction, the Ohio State University Moritz Law Library

SPEAKERS:

• Cas Laskowski, Head of Research, Data & Instruction, University of Arizona College of Law Library
• Diana Koppang, Director of Knowledge Management, Neal, Gerber & Eisenberg LLP

AALL BODY OF KNOWLEDGE DOMAINS: Professionalism + Leadership At Every Level

All AALL webinars include live captioning services.

The opinions shared during this program represent the views of the speakers and do not necessarily reflect those of the American Association of Law Libraries (AALL). Recording, capturing, or using AI tools to duplicate, transcribe, or otherwise reproduce an AALL program in any form is strictly prohibited without prior written consent from AALL. This includes, but is not limited to audio, video, or any other content shared. By attending an AALL program or accessing an AALL recording, you agree to adhere to this policy.

This session will feature two presentations centered around Trends in Teaching AI in the University Setting: 

• AI-Integration in First Semester Legal Research & Writing
• Educational program to be announced

AI-Integration in First Semester Legal Research & Writing

This session presents a practical, classroom-tested approach to integrating generative AI into first-year Lawyering Skills instruction. Drawing on implementation at an academic law library and legal research program, the presentation demonstrates how AI can be embedded within core competencies (case analysis, legal reasoning, and research) rather than treated as a standalone topic. Through structured assignments, students critically evaluate AI-generated legal work, identify hallucinated authorities, compare human and AI drafting, and develop verification habits essential to professional practice. The session emphasizes real-world challenges, including overreliance, accuracy, and ethical obligations, while offering concrete exercises and workflows that legal information professionals can adapt in their own instructional settings. This talk highlights lessons learned, student outcomes, and strategies for fostering AI literacy grounded in judgment, accountability, and rigorous legal research.

TARGET AUDIENCE:

Academic Law Librarians, Court Librarians, Firm/Private Law Librarians, Government Law Librarians, Legal Research & Writing Instructors (Non-librarians), Knowledge Management & Innovation Professionals, and Newer Legal Information Professionals/Early Career Librarians.

TAKEAWAYS:

1. Evaluate AI-generated legal content critically by identifying hallucinated citations, misapplied authority, and gaps in reasoning, using structured verification techniques applicable to real research workflows.
2. Integrate AI tools into legal research and writing instruction in ways that reinforce—rather than replace—core competencies such as case analysis, rule synthesis, and predictive reasoning.
3. Apply ethical and professional standards to AI use by developing practices that promote transparency, accuracy, and accountability in line with legal research norms and professional responsibility rules.

SPEAKERS:

• Frank Young, Reference Librarian & Instructor, University of Illinois Chicago School of Law

AALL BODY OF KNOWLEDGE DOMAINS: Professionalism + Leadership At Every Level, Research + Analysis, Teaching + Training, 

All AALL webinars include live captioning services.

The opinions shared during this program represent the views of the speakers and do not necessarily reflect those of the American Association of Law Libraries (AALL). Recording, capturing, or using AI tools to duplicate, transcribe, or otherwise reproduce an AALL program in any form is strictly prohibited without prior written consent from AALL. This includes, but is not limited to audio, video, or any other content shared. By attending an AALL program or accessing an AALL recording, you agree to adhere to this policy.

Be a part of the conversation! The virtual coffee chat will begin with the full group to provide an overview of problem solving with AI, then attendees will be able to choose which breakout session discussion to join, centered around the academic, government, and law firm library types. The moderated breakouts will ask questions targeted to your library experience, and all attendees are invited to contribute. The breakout discussion will be captured via a notetaker and anonymized takeaway summaries shared as part of the event recordings bundle.

AALL BODY OF KNOWLEDGE DOMAINS: Professionalism + Leadership At Every Level, Research + Analysis, Information Management, Teaching + Training, Marketing + Outreach, Management + Business Acumen

The opinions shared during this program represent the views of the speakers and do not necessarily reflect those of the American Association of Law Libraries (AALL). Recording, capturing, or using AI tools to duplicate, transcribe, or otherwise reproduce an AALL program in any form is strictly prohibited without prior written consent from AALL. This includes, but is not limited to audio, video, or any other content shared. By attending an AALL program or accessing an AALL recording, you agree to adhere to this policy.

This session will feature two presentations centered around AI strategy: 

• Your AI Knows Too Much: Privilege, Confidentiality, and the New Discovery Frontier
• Beyond Hallucinations: What ABA Opinion 512 Really Means for AI & Law Librarians

Your AI Knows Too Much: Privilege, Confidentiality, and the New Discovery Frontier

When a federal judge ruled that a defendant's generative AI prompts and outputs were neither privileged nor protected work product, a new era of privilege risk was born. This session examines the emerging and rapidly diverging case law on attorney-client privilege and work product protection in the age of AI, with a focus on what law librarians need to know to support their students, attorneys, and other stakeholders. Drawing from United States v. Heppner (S.D.N.Y.), Warner v. Gilbarco (E.D. Mich.), and Conservation Law Foundation v. Shell Oil (D. Conn.), we’ll explore how platform terms of service can destroy confidentiality and why privilege and work product doctrine diverge for AI-generated materials. Whether you are curating AI research tools, advising on information governance, or fielding questions about safe AI use, this session will equip you with the doctrinal grounding and practical frameworks to navigate the new landscape confidently.

TARGET AUDIENCE:

All law librarians involved in risk assessment 

TAKEAWAYS:

1. Attendees will gain practical insight into how enterprise versus consumer AI platforms affect privilege analysis
2. Understand  the implications for everyday tools like Gmail
3. Recognize governance protocols that organizations should implement to safeguard confidentiality. 

SPEAKER:

• Cindy Guyer, Practice Innovation Attorney, Foley & Lardner LLP

AALL BODY OF KNOWLEDGE DOMAINS: Information Management

Beyond Hallucinations: What ABA Opinion 512 Really Means for AI & Law Librarians

ABA Formal Opinion 512 laid out the rules of the road for AI in law — and the guardrails go a lot further than "make sure it doesn't hallucinate." Confidentiality risks, fee transparency, supervision gaps: the ethical exposure is real, with major consequences for violations. This session provides law librarians with a practical map for understanding the Rules and bringing them into classrooms, training programs, and their day-to-day work.

TARGET AUDIENCE:

All law librarians involved in vetting AI and/or training users to work with GenAI products.

TAKEAWAYS:

1. Identify the Model Rules implicated by AI use in legal practice and law libraries beyond competence, including confidentiality, fees, and supervisory responsibility.
2. Apply the framework of ABA Formal Opinion 512 to real-world AI use scenarios to spot potential ethical violations.
3. Explore instructional content or training materials that help law students and practitioners navigate AI ethics under the Rules.

SPEAKER:

• Deborah Ginsberg, Manager of Emerging Technologies, Harvard Law School Library

AALL BODY OF KNOWLEDGE DOMAINS: Professionalism + Leadership At Every Level, Teaching + Training

Ahead of the AALL Virtual Exchange, AALL will invite the law librarian community to contribute their ideas for effective, innovative prompts that solve challenges, save time, and create opportunities. This session will highlight some of the Top Rated Responses and considerations when developing prompts, and share prompting trends. Attendees will walk away with tools they can start using immediately to improve their prompts

AALL BODY OF KNOWLEDGE DOMAINS: Research + Analysis

All AALL webinars include live captioning services.

The opinions shared during this program represent the views of the speakers and do not necessarily reflect those of the American Association of Law Libraries (AALL). Recording, capturing, or using AI tools to duplicate, transcribe, or otherwise reproduce an AALL program in any form is strictly prohibited without prior written consent from AALL. This includes, but is not limited to audio, video, or any other content shared. By attending an AALL program or accessing an AALL recording, you agree to adhere to this policy.

This session will feature two presentations centered around building AI skills across organizations and the public. 

• AI Said So: Understanding and Countering Pro Se Overreliance on AI-Generated Legal Information
• Educational program to be announced

AI Said So: Understanding and Countering Pro Se Overreliance on AI-Generated Legal Information

This session explores a novel phenomenon unique to the AI-age: self-represented litigants are increasingly arriving to public law libraries anchored in AI-generated legal information and rejecting law librarians’ expertise and authoritative information. The presenter is an MILS student who has designed a research study regarding this phenomenon and will be conducting the research this coming Spring. Attendees will be introduced to theoretical frameworks and literature underpinning this study, the study’s purpose, design, and research questions, and will feature an opportunity to share firsthand experiences and strategies from your own location.

This session is geared toward legal information professionals who have struggled when encountering an AI-influenced SRL and wants to understand: 1. Why this situation occurred, and 2. What they can do next time—because there will be a next time.

TARGET AUDIENCE:

Public-facing law library professionals

TAKEAWAYS:

1. Attendees will learn what automation bias is and how it manifests in public law libraries.
2. Attendees will learn how affective states (emotions) influence information behavior and increase the likelihood of overreliance on AI and rejection of the law librarian's subject matter authority.
3. Attendees will learn what strategies are positioned to be successful vs. unsuccessful, informing future reference encounters with AI-influenced patrons.

SPEAKER:

• Ella Pieterse, Law Library Assistant, New York State Unified Court System

AALL BODY OF KNOWLEDGE DOMAINS: Professionalism + Leadership At Every Level, Teaching + Training

All AALL webinars include live captioning services.

The opinions shared during this program represent the views of the speakers and do not necessarily reflect those of the American Association of Law Libraries (AALL). Recording, capturing, or using AI tools to duplicate, transcribe, or otherwise reproduce an AALL program in any form is strictly prohibited without prior written consent from AALL. This includes, but is not limited to audio, video, or any other content shared. By attending an AALL program or accessing an AALL recording, you agree to adhere to this policy.