Thelwall, M. orcid.org/0000-0001-6065-205X and Kousha, K. (2025) Technology assisted research assessment: algorithmic bias and transparency issues. Aslib Journal of Information Management, 77 (1). ISSN 2050-3806
Abstract
Purpose
Technology is sometimes used to support assessments of academic research in the form of automatically generated bibliometrics for reviewers to consult during their evaluations or by replacing some or all human judgements. With artificial intelligence (AI), there is increasing scope to use technology to assist research assessment processes in new ways. Since transparency and fairness are widely considered important for research assessment and AI introduces new issues, this review investigates their implications.
Design/methodology/approach
This article reviews and briefly summarises transparency and fairness concerns in general terms and through the issues that they raise for various types of Technology Assisted Research Assessment (TARA).
Findings
Whilst TARA can have varying levels of problems with both transparency and bias, in most contexts it is unclear whether it worsens the transparency and bias problems that are inherent in peer review.
Originality/value
This is the first analysis that focuses on algorithmic bias and transparency issues for technology assisted research assessment.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2023 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Aslib Journal of Information Management is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Technology Assisted Research Assessment; bibliometrics; research evaluation; machine learning; algorithmic bias; transparency |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Sep 2023 08:50 |
Last Modified: | 12 Feb 2025 11:41 |
Status: | Published |
Publisher: | Emerald |
Refereed: | Yes |
Identification Number: | 10.1108/AJIM-04-2023-0119 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:203219 |