CoChat
Sign Up
Cited by 200Ethics and Social Impacts of AIRobotic Process Automation ApplicationsAuditing, Earnings Management, Governance

The DOI matches its Crossref record; 112 of the 114 references it cites were found in a registry or an index.

Bias and ethics of AI systems applied in auditing - A systematic review

Open access
Murikah, Wilberforce, Nthenge, Jeff Kimanga, Musyoka, Faith Mueni·2024·Scientific African
DOI 10.1016/j.sciaf.2024.e02281
Open this paper in CoChat — free account

Abstract

The integration of artificial intelligence into auditing shows great potential in enhancing automation and gaining insights from complex data. However, it also presents significant ethical challenges, including algorithmic biases, transparency, accountability, and fairness. This study aimed to investigate the sources of bias and risks posed by AI systems applied in auditing and the complex downstream interactions and effects they have. The study also explored the technical and ethical guardrails proposed and recommendations for translating principles into auditing practice. A systematic methodology was employed to acquire relevant studies across scientific databases. This involved a three-step process, including a targeted search query using Boolean operators and snowballing to yield 310 preliminary publications. A systematic review process was then conducted to identify 123 relevant articles focused on AI's implications for auditing, accounting, finance, or assurance contexts. Finally, screening and filtering on research quality distilled 83 high-quality publications from the year 2018 to 2023 spanning computer science, accounting, management science, and ethics disciplines. The analysis revealed five primary sources driving technical and human biases: data deficiencies, demographic homogeneity, spurious correlations, improper comparators, and cognitive biases. It also highlighted wider issues, such as trade-offs between efficiency and diligence, erosion of human skills and…

Overview

Integrity signals

Registry

Crossref · 10.1016/j.sciaf.2024.e02281

Cites

112 of 112 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

1 retracted

Flagged first, then by citations

Show all 114 references

2 of the 114 references couldn’t be matched to a known paper.

Research works printed but not linked: 7

  1. Ivakhnenkov, 2023, Application of artificial intelligence in auditing, Scientific notes of NaUKMA. Econ. Sci., 8, 54
  2. Mansell, 2018, 22, 305
  3. Muhammad, 2021, Auditing Algorithmic Fairness With Unsupervised Bias Discovery, Amsterdam Intelligence
  4. Puspitasari, 2019, The effect of audit competence, independence, and professional skepticism on audit quality with auditor's ethics as moderation variables, Int. J. Business, Econ. Law, 18, 135
  5. Qayyum, 2020, The data-driven audit: how automation and AI are changing the audit and the role of the auditor, Chartered Professional Accountants of Canada
  6. G. Finocchiaro, “The regulation of artificial intelligence,” AI Soc, vol. 1, pp. 1–8, Apr. 2023, doi: 10.1007/S00146-023-01650-Z/METRICS. · DOI
  7. 2024, Fact sheet: president biden issues executive order on safe, secure, and trustworthy artificial intelligence, The White House

Cited by

Sorted by citations

Items 101–200 of 200

Related

See all

Metadata

Authors
Murikah, W., Nthenge, J. K., & Musyoka, F. M.
Affiliations
  • United States International University Africa (KE)
  • University of Embu (KE)
Corresponding author
Murikah, Wilberforce
ORCID
Venue
Scientific African
Publisher
Elsevier BV
Published
2024-09
Volume
25
Pages
e02281
ISSN
2468-2276 (ISSN-L)
DOI
10.1016/j.sciaf.2024.e02281
OpenAlex
W4399619293
Cited by
148
References
114
Citations by year
2026: 63 · 2025: 76 · 2024: 9
FWCI
11.30
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific African (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Robotic Process Automation Applications
  • Social Sciences › Business, Management and Accounting › Accounting › Auditing, Earnings Management, Governance
Keywords
artificial intelligence in auditing, algorithmic bias, AI ethics, data bias, spurious correlations, cognitive biases, human oversight, fairness and accountability, privacy risks, AI governance, causal models

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review