Arnaboldi, Michela and de Bruijn, Hans and Steccolini, Ileana and Van der Voort, Haiko (2022) On humans, algorithms and data. Qualitative Research in Accounting and Management, 19 (3). pp. 241-254. DOI https://doi.org/10.1108/qram-01-2022-0005
Arnaboldi, Michela and de Bruijn, Hans and Steccolini, Ileana and Van der Voort, Haiko (2022) On humans, algorithms and data. Qualitative Research in Accounting and Management, 19 (3). pp. 241-254. DOI https://doi.org/10.1108/qram-01-2022-0005
Arnaboldi, Michela and de Bruijn, Hans and Steccolini, Ileana and Van der Voort, Haiko (2022) On humans, algorithms and data. Qualitative Research in Accounting and Management, 19 (3). pp. 241-254. DOI https://doi.org/10.1108/qram-01-2022-0005
Abstract
Purpose The purpose of this paper is to introduce the papers in this special issue on humans, algorithms and data. The authors first set themselves the task of identifying the main challenges arising from the adoption and use of algorithms and data analytics in management, accounting and organisations in general, many of which have been described in the literature. Design/methodology/approach This paper builds on previous literature and case studies of the application of algorithm logic with artificial intelligence as an exemplar of this innovation. Furthermore, this paper is triangulated with the findings of the papers included in this special issue. Findings Based on prior literature and the concepts set out in the papers published in this special issue, this paper proposes a conceptual framework that can be useful both in the analysis and ordering of the algorithm hype, as well as to identify future research avenues. Originality/value The value of this framework, and that of the papers in this special issue, lies in its ability to shed new light on the (neglected) connections and relationships between algorithmic applications, such as artificial intelligence. The framework developed in this piece should stimulate scholars to explore the intersections between “technical” as well as organisational, social and individual issues that algorithms should help us tackle.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Artificial intelligence; Digital transformation; Algorithm governance; Performance |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 24 May 2022 13:18 |
Last Modified: | 30 Oct 2024 16:54 |
URI: | http://repository.essex.ac.uk/id/eprint/32889 |
Available files
Filename: 10-1108_QRAM-01-2022-0005.pdf
Licence: Creative Commons: Attribution 3.0