Program recordings from the 2023 AALL Annual Meeting & Conference were sponsored by LexisNexis. Please note the opinions shared during the programs represent the views of the speakers and not of AALL.

Machine learning is now part of all of our work. It is prudent that we all have a foundational understanding of their creation, the related ethical issues, and best practices for investigating machine learning applications. One need only critical thought and curiosity to join this program where we will cover each of these topics and apply them together on machine learning applications. This presentation will serve as an accessible introduction to the topic with a safe space to explore real-world applications.

TARGET AUDIENCE:

Any librarians that want a foundational understanding of machine learning so as to better engage with vendors, teach students, or participate in ml teams.

TAKEAWAYS:

• Participants will be able to describe the various stages of machine learning system development.
• Participants will engage will various machine meaning systems and tools.
• Participants will discuss the various concerns at different stages of development as well as the issues implicated by different machine learning systems (e.g., prediction or computer vision).

SPEAKER:

• Cas Laskowski (she/her/hers), Head of Research, Data, & Instruction, University of Arizona Law Library

AALL BODY OF KNOWLEDGE DOMAINS: Information Management, Teaching + Training