Is AI biased? evidence from FinTech-based innovation in supply chain management companies?
| Autor: | Abdel-Aziz Ahmad Sharabati, Shafiq Ur Rehman, Mubasher H. Malik, Samar Sabra, Maen Al-Sager, Mahmoud Al-lahham |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | International Journal of Data and Network Science, Vol 8, Iss 3, Pp 1839-1852 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2561-8148 2561-8156 |
| DOI: | 10.5267/j.ijdns.2024.2.005 |
| Popis: | This study investigates AI bias in financial technology (FinTech)-based supply chain management in Pakistan. The study employs Structural Equation Modeling (SEM) to analyze data from diverse respondents. Hypotheses examine the relationships between AI integration, algorithm diversity, employee training, data quality, regulatory compliance, organizational culture, and AI bias. The findings reveal that higher AI integration leads to increased AI bias, Algorithm diversity reduces AI bias, while employee training decreases bias, Quality and diversity of data negatively correlate with AI bias, and regulatory compliance lowers bias. In addition, organizational culture mediates the relationship between AI integration and AI bias. This research contributes a holistic understanding of AI bias factors, guiding ethical AI adoption. Policymakers can use these insights to shape regulations, and industry practitioners can make informed decisions. |
| Databáze: | Directory of Open Access Journals |
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