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 accessAbstract
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…
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“When coupled with validation protocols (e.g., response verification or schema checks in Waitgpt [219]) and observation mechanisms (e.g., feedback loops or audit logs [220, 221]), these boundaries are reinforced, ensuring that each agent not only performs its assigned task but does so transparently and accountably.”
From AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges (2026) · cites this paper as [221]
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Ethical and legal considerations in healthcare AI: innovation and policy for safe and fair use
Pham, T. D. (2025) · Royal Society Open Science · doi:10.1098/rsos.241873 · Cited by 367
AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges
Sapkota, R., Roumeliotis, K. I., & Karkee, M. (2026) · Information Fusion · doi:10.1016/j.inffus.2025.103599 · Cited by 671
“…validation protocols (e.g., response verification or schema checks in Waitgpt [219]) and observation mechanisms (e.g., feedback loops or audit logs [220, 221]), these boundaries are reinforced, ensuring that each agent not only performs its assigned task but does so transparently and accountably.”
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges
Sapkota, R., Roumeliotis, K. I., & Karkee, M. (2025) · SuperIntelligence - Robotics - Safety & Alignment · doi:10.70777/si.v2i3.15161 · Cited by 186
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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
- Venue
- Scientific African
- Publisher
- Elsevier BV
- Published
- 2024-09
- Volume
- 25
- Pages
- e02281
- ISSN
- 2468-2276 (ISSN-L)
- 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
- gold
- doi.org
- 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
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