Publication Date
1-1-2024
Document Type
Contribution to a Book
Publication Title
Knowledge Management and Organizational Learning
Volume
13
DOI
10.1007/978-3-031-53946-6_11
First Page
197
Last Page
213
Abstract
This chapter examines how the doings of the algorithm (instantiated through its operations, actions, and steps) and its accompanying algorithmic system are revealed and explored through an engagement with the paradata created as a part of this data-making effort. In doing so, the chapter explores how the concept of paradata helps us understand how information professionals and domain stakeholders conceptualize accountable algorithmic entities and how this influences how they emerge as documented and describable entities. Two complementary frameworks for capturing and preserving paradata for accountability purposes are examined in the process. The first is associated with diplomatic theory and archival notions of context and focuses on the role of paradata for algorithmic transparency. The second is related to knowledge management and to efforts in the AI community to use paradata to create unified reporting models that enhance the explainability of algorithms and algorithmic systems. The chapter concludes by demarcating examples and different use cases for paradata for accountability purposes and the mechanisms by which these agents of transparency and explainability can connect with interested and vested audiences.
Funding Sponsor
University of Texas at Austin
Keywords
Accountability, Algorithmic documentation, Algorithmic systems, Algorithms, Archival science, Digital archives, Explainability, Paradata, Recordkeeping, Transparency
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Information
Recommended Citation
Ciaran B. Trace and James A. Hodges. "The Role of Paradata in Algorithmic Accountability" Knowledge Management and Organizational Learning (2024): 197-213. https://doi.org/10.1007/978-3-031-53946-6_11
