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On humans, algorithms and data

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. ISSN 1176-6093

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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
Faculty of Social Sciences > Essex Business School > Essex Accounting Centre
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 24 May 2022 13:18
Last Modified: 10 Jun 2022 14:02
URI: http://repository.essex.ac.uk/id/eprint/32889

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