Background

In December 2023, the Task Group on Strategic Planning for AI and Machine
Learning was charged with conducting an environmental scan on the impact of AI
and Machine Learning on library cataloging and metadata operations and
providing evidence on potential directions for PCC. The Task Group submitted
the final report to PoCo on April 15, 2024, based on the outcomes of survey
results. On May 9, 2024, the PCC Policy Committee (PoCo) approved the Task
Group on Strategic Planning for AI and Machine Learning final report and its
recommendations, including the establishment of a new task group to carry out
the deliverables identified in the report. 

Charges

The PCC Task Group on AI and Machine Learning for Cataloging and Metadata
is charged to:

• Compose and distribute a statement of principles on the use of AI and
  Machine Learning technologies in cataloging and metadata work. The goal
  is to emphasize the need for thoughtful consideration and strategic
  planning, highlighting that AI is intended to augment, not replace, the
  valuable work of cataloging professionals (by automating the more
  rudimentary and repetitive aspects of metadata creation and making the
  overall process more efficient), and it is not a viable strategy for reduction
  of personnel. (timeframe: 3 months) [SD2.1]
• Establish a community of practice for catalogers interested in sharing
  knowledge and experimenting with AI. This community should be open to
  both PCC and non-PCC library personnel. (timeframe: 6 months) [SD5.3]
• Reach out to international library communities who have been
  experimenting with and implementing AI-related cataloging projects, for
  the purposes of compiling a knowledge base for the PCC that may inform
  the development of best practices. (timeframe: ongoing) [SD1.1]
• Further flesh out the AI resources on the PCC wiki and update as needed,
  including AI-related cataloging activities happening within other
  international library communities. (timeframe: ongoing) [SD5.3]
• Collaborate with NARDAC, ALA, the Library of Congress, the Advisory
  Committee on Equity, Diversity, Inclusion, Belonging, and Accessibility
  (EDIBA), and other primary stakeholders in the development of cataloging
  standards and platforms, in order to mutually consider the impact of AI on
  the future of cataloging work. (timeframe: ongoing) [SD1.1]
• Develop and distribute a best practices document for incorporating AI and
  Machine Learning into cataloging and metadata work. (timeframe: 1 year)
  [SD2.1]
• Work with the Standing Committee on Training (SCT) to develop
  introductory training resources for learning more about or experimenting
  with AI. (timeframe: 1 year) [SD5.3]
• Provide a report summarizing the work described above. 

PCC Strategic Directions progress 2023- (working document):

• SD 1.1.7. Establish a task group to initiate communication and
  collaboration between stakeholders involved with the development and
  implementation of cataloging and metadata applications of Artificial
  Intelligence (AI) and Machine Learning (ML)
• SD 2.1.6. Support and promote the development of best practices for use
  of Artificial Intelligence (AI) and Machine Learning (ML) for cataloging and
  metadata work
• SD 5.3.3. Develop training resources for learning more about or
  experimenting with AI 

Time Frame:

• Date charged: September 3, 2024
• Date preliminary report due: March 3, 2025
• Date final report due: September 3, 2025

Reports to:
PCC Policy Committee

Roster:

• SCA/NLM representative: Alvin Stockdale (NLM, alvin.stockdale@nih.gov), co-chair (Sept 3, 2024-Jan 22, 2025)
• SCS representative: Liz Miraglia (California Digital Library, elizabeth.miraglia@ucop.edu)
• SCT representative: Kate James (OCLC, jamesk@oclc.org)
• Task Group on Strategic Planning for AI and Machine Learning, former member:
• Caroline Saccucci (Library of Congress, csus@loc.gov)
• PoCo representative: Christine DeZelar-Tiedman (University of Minnesota, dezel002@umn.edu)
• EDIBA representative: Keno Catabay (University of Colorado Boulder, Keno.Catabay@colorado.edu)
• OCLC representative: Inkyung Choi (choii@oclc.org) 
• Clarivate representative: Lili Daie (Lili.Daie@Clarivate.com)
• Library of Congress representative: Heidy Berthoud (hberthoud@loc.gov)
• Joint RDA Board and RSC Working Group on AI representative: Charlene Chou
  (New York University, charlene.chou@nyu.edu), co-chair
• Volunteer in the survey: Giovanni Aldi (Casalini Libri Spa, giovanni.aldi@casalini.it)
• Consultant: Jenny Toves (OCLC, tovesj@oclc.org)