Hi, we're the Aida digital libraries research lab

We explore applications of image analysis and machine learning in digital libraries of historic materials. We’re especially interested in what we might learn from the millions of digital images that librarians, archivists, and others are creating as they digitize the cultural record. We’re intrigued by the questions that machine learning approaches might help to surface in these collections and about our professional practices—and also by the questions our collections and professional practices might help to surface about machine learning.

The big "why" for our work is that information—its access, its content, its gaps—structures power and affects individuals' and communities' lives in profound ways. Here's how we put it in a report we wrote for the Library of Congress:

Domains considering implementing machine learning must engage deeply and critically with the technology, what it does, and what it means. For cultural heritage digital libraries, now is a critical moment to grapple with epistemologies of machine learning and the knowledge it structures, shapes, and appears to codify. Some elements of these epistemological conversations may transcend domains and applications, but these conversations also must be rooted in the specificities of the cultural heritage sector. In particular, libraries must grapple with their historical foundations and practices and with the potential consequences of these practices for machine learning. Previous and ongoing collecting and description practices, for example, were and are colonialist, racist, hetero- and gender- normative, and supremacist in other structural and systemic ways. These understandings are the foundation on which training and validation data will be created and assembled; they will become reinscribed as statements of truth, even as we elsewhere champion the potential of computational approaches to uncover hidden histories, identities, and perspectives in collections. To engage machine learning in cultural heritage must mean confronting these histories, committing to the hard work of acknowledgment and rectification, and not simply reproducing them and giving them a whole new scale of power.

Many individuals have contributed to our work in myriad ways over the years. They include (in alphabetical order): Lauren Algee (collaborating partner), Andrew Barrow (core team member), Sarah Berkowitz (core team member), Paul Conway (advisory board member), Ryan Cordell (advisory board member), Maanas Varma Datla (core team member), Jody DeRidder (advisory board member), Mary Ellen Ducey (advisory board member), Adam Farquhar (advisory board member), Meghan Ferriter (collaborating partner),Emily Gore (advisory board member), Patricia Hswe (advisory board member), Natalie Houston (advisory board member), Victoria Van Hyning (collaborating partner), Eileen Jakeway (collaborating partner), Kyle Janvrin (core team member), Spencer Kulwicki (core team member), Joseph Lunde (core team member), Worthy Martin (collaborating partner), Meredith McGill (advisory board member), Jaime Mears (collaborating partner), Andrew Michael (core team member), Bethany Nowviskie (advisory board member), John O'Brien (collaborating partner), Abbey Potter (collaborating partner), Delaram Rahimighazikalayeh (core team member), Ayla Stein (advisory board member), Grace Thomas (core team member), John Unsworth (advisory board member), and Tong Wang (collaborating partner).

We'd love to hear about related work that you're doing, and we're always happy to talk about our team's work as well.

• Liz Lorang
• Leen-Kiat Soh