Access to data is seen as a key priority today. Yet, the vast majority of digital cultural data preserved in archives is inaccessible due to privacy, copyright or technical issues. Emails and other born-digital collections are often uncatalogued, unfindable and unusable. In the case of documents that originated in paper format before being digitised, copyright can be a major obstacle to access. To solve the problem of access to digital archives, cross-disciplinary collaborations are absolutely essential. The big challenges of our time—from global warming to social inequalities—cannot be solved within a single discipline. The same applies to the challenge of “dark” archives closed to users. We cannot expect archivists or digital humanists to find a magical solution that will instantly make digital records more accessible. Instead, we need to set up collaborations across disciplines that seldom talk to each other. Based on 21 interviews with 26 archivists, librarians and other professionals in cultural institutions, we identify key obstacles to making digitised and born-digital collections more accessible to users. We outline current levels of access to a wide range of collections in various cultural organisations, including no access at all and limited access (for example, when users are required to travel on-site to consult documents). We suggest possible solutions to the problems of access—including the ethical use of Artificial Intelligence to unlock “dark” archives inaccessible to users. Finally, we propose the creation of a global user community who would participate in decisions on access to digital collections.
Co-authored by a Computer Scientist and a Digital Humanist, this article examines the challenges faced by cultural heritage institutions in the digital age, which have led to the closure of the vast majority of born-digital archival collections. It focuses particularly on cultural organizations such as libraries, museums and archives, used by historians, literary scholars and other Humanities scholars. Most born-digital records held by cultural organizations are inaccessible due to privacy, copyright, commercial and technical issues. Even when born-digital data are publicly available (as in the case of web archives), users often need to physically travel to repositories such as the British Library or the Bibliothèque Nationale de France to consult web pages. Provided with enough sample data from which to learn and train their models, AI, and more specifically machine learning algorithms, offer the opportunity to improve and ease the access to digital archives by learning to perform complex human tasks. These vary from providing intelligent support for searching the archives to automate tedious and time-consuming tasks. In this article, we focus on sensitivity review as a practical solution to unlock digital archives that would allow archival institutions to make non-sensitive information available. This promise to make archives more accessible does not come free of warnings for potential pitfalls and risks: inherent errors, "black box" approaches that make the algorithm inscrutable, and risks related to bias, fake, or partial information. Our central argument is that AI can deliver its promise to make digital archival collections more accessible, but it also creates new challenges - particularly in terms of ethics. In the conclusion, we insist on the importance of fairness, accountability and transparency in the process of making digital archives more accessible.
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