Generous Tools

Responsible operations demand the integration of contextual knowledge. Making ready use of contextual knowledge depends in part on the availability of generous tools. It is often the case that emerging technologies, the methods they enact, and the variety of programming languages they make use of present a steep learning curve for nonexperts. Use of the technology tends to get siloed to a role in a particular part of the library, and the potential for leveraging diverse forms of expertise present across an organization are lost. Generous tools are designed and documented in such a way that they make it possible for users of varying skill levels to contribute to the improvement and/or use of algorithmic methods. Per Scott Weingart’s recommendation, the library community may benefit from seeking out human computer interaction experts to help design generous tools (e.g., human-in-the-loop systems, exploratory visualization environments, GUI-based [graphical user interface] analytics platforms, semiautomated AI model development). These tools could follow in the spirit of Gen (a noviceoriented programming language developed at the Massachusetts Institute of Technology), Zooniverse, and iNaturalist (platforms that can facilitate crowdsourced classification), and resources like those developed by Matthew Reidsma that help librarians audit the product of library discovery systems.


  1. Form a working group focused on studying data science, machine learning, and AI solutions that are designed to accommodate users with varying degrees of technical and methodological experience. Produce high-level synthesis and best practices for solution design in the context of library community need.
  2. Foster partnerships between the library developer community, human computer interaction experts, and computer scientists in order to develop systems that are more readily usable by a broad range of library staff.
Thomas Padilla on Generous Tools for Da…