Library of Congress Labs Releases AI Planning Framework

Excerpted from The LoC Blog Post

The November 15 post announcing the release of the Framework was written by Abigail Potter, Senior Innovation Specialist with LC Labs. It opens with the following: 

LC Labs has been exploring how to use emerging technologies to expand the use of digital materials since our launch in 2016. We quickly saw machine learning (ML), one branch of artificial intelligence (AI), as a potential way to provide more metadata and connections between collection items and users. Experiments and research have shown the risks and benefits of using AI in libraries, archives and museums (LAMs) are both significant yet still largely hypothetical.

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To account for these challenges and realities, LC Labs has been developing a planning framework to support the responsible exploration and potential adoption of AI at the Library. At a high level, the framework includes three planning phases:  1) Understand 2) Experiment and 3) Implement, each supports the evaluation of three elements of ML: 1) Data; 2) Models; and 3) People. We’ve developed a set of worksheets, questionnaires, and workshops to engage stakeholders and staff and identify priorities for future AI enhancements and services. The mechanisms, tools, collaborations, and artifacts together form the AI Planning Framework. Our hope in sharing the framework and associated tools in this initial version is to encourage others to try it out and to solicit additional feedback. We will continue updating and refining the framework as we learn more about the elements and phases of ML planning.

Members of the information community are advised to understand, experiment, and implement with the understanding that collaborative efforts will be needed.

The full text of the original announcement is here.