Artificial Intelligence and Machine Learning at the Intersection of Privacy and Archives
Abstrak
As records are increasingly born digital – and thus, at least ostensibly, potentially much more accessible – archivists find themselves struggling to enable general access while providing appropriate privacy protections for the torrent of records being transferred to their care. In this article, the authors report the results of an integrative literature review study, examining the intersection of AI, archives, and privacy in terms of how archives are currently coping with these challenges and what role(s) AI might play in addressing privacy in archival records. The study revealed three major themes: 1) the challenges of – and possibilities beyond – defining “privacy” and “AI”; 2) the need for context-sensitive ways to manage privacy and access decisions; and 3) the lack of adequate “success measures” for ensuring the actual fitness for purpose of privacy AI solutions in the archival context.
Topik & Kata Kunci
Penulis (4)
Iori Khuhro
Erin Gilmore
Jim Suderman
Darra L. Hofman
Akses Cepat
PDF tidak tersedia langsung
Cek di sumber asli →- Tahun Terbit
- 2024
- Sumber Database
- DOAJ
- DOI
- 10.4467/26581264ARC.24.006.20201
- Akses
- Open Access ✓