The Role of Paradata in Algorithmic Accountability

Ciaran B. Trace () and James A. Hodges ()
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Ciaran B. Trace: School of Information, The University of Texas at Austin
James A. Hodges: School of Information, San Jose State University

A chapter in Perspectives on Paradata, 2024, pp 197-213 from Springer

Abstract: 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.

Keywords: Paradata; Algorithms; Algorithmic systems; Algorithmic documentation; Accountability; Transparency; Explainability; Recordkeeping; Digital archives; Archival science (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:kmochp:978-3-031-53946-6_11

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DOI: 10.1007/978-3-031-53946-6_11

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